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Carmona J, Chavarria E, Donoghue K, von Gertten C, Oberrauch P, Pailler E, Scoazec G, Weijer R, Balmaña J, Brana I, Brunelli C, Delaloge S, Deloger M, Delpy P, Ernberg I, Fitzgerald RC, Garralda E, Lablans M, Lëhtio J, Lopez C, Fernández M, Miceli R, Nuciforo P, Perez-Lopez R, Provenzano E, Schmidt MK, Serrano C, Steeghs N, Tamborero D, Wirta V, Baird RD, Barker K, Barlesi F, Baumann M, Bergh J, de Braud F, Fizazi K, Fröhling S, Piris-Giménez A, Seamon K, Van der Heijden MS, Zwart W, Tabernero J. Cancer Core Europe: Leveraging Institutional Synergies to Advance Oncology Research and Care Globally. Cancer Discov 2024; 14:1147-1153. [PMID: 38870393 DOI: 10.1158/2159-8290.cd-24-0377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/26/2024] [Accepted: 05/07/2024] [Indexed: 06/15/2024]
Abstract
Cancer Core Europe brings together the expertise, resources, and interests of seven leading cancer institutes committed to leveraging collective innovation and collaboration in precision oncology. Through targeted efforts addressing key medical challenges in cancer and partnerships with multiple stakeholders, the consortium seeks to advance cancer research and enhance equitable patient care.
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Affiliation(s)
- Javier Carmona
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Elena Chavarria
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Kate Donoghue
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | | | - Petra Oberrauch
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | | | - Giovanni Scoazec
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Ruud Weijer
- Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Judith Balmaña
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Department of Medical Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Irene Brana
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Department of Medical Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Cinzia Brunelli
- Palliative Care, Pain Therapy and Rehabilitation Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Suzette Delaloge
- Interception Programme, Department of Cancer Medicine, Gustave Roussy, Villejuif, France
| | | | - Pierre Delpy
- Federated Information Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Complex Medical Informatics, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany
- German Cancer Consortium (DKTK), Core Center Heidelberg, Heidelberg, Germany
| | - Ingemar Ernberg
- Department of Microbiology, Tumor and Cell Biology (MTC), Cancer Center Karolinska (CCK) & Biomedicum. Karolinska Institutet, Stockholm, Sweden
| | - Rebecca C Fitzgerald
- Department of Oncology, Early Cancer Institute, University of Cambridge, Cambridge, United Kingdom
| | - Elena Garralda
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Department of Medical Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Martin Lablans
- Federated Information Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Complex Medical Informatics, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany
- German Cancer Consortium (DKTK), Core Center Heidelberg, Heidelberg, Germany
| | - Janne Lëhtio
- Department of Oncology and Pathology, Karolinska Institutet, SciLifeLab, Solna, Sweden
- Karolinska University Hospital, Stockholm, Sweden
| | - Carlos Lopez
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | | | - Rosalba Miceli
- Unit of Biostatistics for Clinical Research, Department of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Paolo Nuciforo
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | | | - Elena Provenzano
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Marjanka K Schmidt
- Division of Molecular Pathology, NKI Center for Early Diagnostics, Lead Early Detection Research Theme, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Cesar Serrano
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Department of Medical Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Neeltje Steeghs
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - David Tamborero
- Department of Oncology and Pathology, Karolinska Institutet, SciLifeLab, Solna, Sweden
- Karolinska University Hospital, Stockholm, Sweden
| | - Valtteri Wirta
- Department of Microbiology, Tumor and Cell Biology, Karolinska Instiutet, Stockholm, Sweden
- Genomic Medicine Center Karolinska, Karolinska University Hospital, Stockholm, Sweden
| | - Richard D Baird
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Karen Barker
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Fabrice Barlesi
- Gustave Roussy, Villejuif, France
- Paris Saclay University, Villejuif, France
| | - Michael Baumann
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Jonas Bergh
- Karolinska Institutet, Stockholm, Sweden
- Karolinska Comprehensive Cancer Center, Karolinska University Hospital, Solna, Sweden
| | - Filippo de Braud
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | | | - Stefan Fröhling
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
- Institute of Human Genetics, Heidelberg University, Heidelberg, Germany
| | | | - Kenneth Seamon
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | | | - Wilbert Zwart
- Netherlands Cancer Institute, Amsterdam, the Netherlands
- Oncode Institute, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Josep Tabernero
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Department of Medical Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
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Wright SJ, Gray E, Rogers G, Donten A, Payne K. A structured process for the validation of a decision-analytic model: application to a cost-effectiveness model for risk-stratified national breast screening. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2024; 22:527-542. [PMID: 38755403 PMCID: PMC11178649 DOI: 10.1007/s40258-024-00887-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/30/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Decision-makers require knowledge of the strengths and weaknesses of decision-analytic models used to evaluate healthcare interventions to be able to confidently use the results of such models to inform policy. A number of aspects of model validity have previously been described, but no systematic approach to assessing the validity of a model has been proposed. This study aimed to consolidate the different aspects of model validity into a step-by-step approach to assessing the strengths and weaknesses of a decision-analytic model. METHODS A pre-defined set of steps were used to conduct the validation process of an exemplar early decision-analytic-model-based cost-effectiveness analysis of a risk-stratified national breast cancer screening programme [UK healthcare perspective; lifetime horizon; costs (£; 2021)]. Internal validation was assessed in terms of descriptive validity, technical validity and face validity. External validation was assessed in terms of operational validation, convergent validity (or corroboration) and predictive validity. RESULTS The results outline the findings of each step of internal and external validation of the early decision-analytic-model and present the validated model (called 'MANC-RISK-SCREEN'). The positive aspects in terms of meeting internal validation requirements are shown together with the remaining limitations of MANC-RISK-SCREEN. CONCLUSION Following a transparent and structured validation process, MANC-RISK-SCREEN has been shown to have satisfactory internal and external validity for use in informing resource allocation decision-making. We suggest that MANC-RISK-SCREEN can be used to assess the cost-effectiveness of exemplars of risk-stratified national breast cancer screening programmes (NBSP) from the UK perspective. IMPLICATIONS A step-by-step process for conducting the validation of a decision-analytic model was developed for future use by health economists. Using this approach may help researchers to fully demonstrate the strengths and limitations of their model to decision-makers.
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Affiliation(s)
- Stuart J Wright
- Division of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK.
| | - Ewan Gray
- GRAIL, New Penderel House 4th Floor, 283-288 High Holborn, London, WC1V 7HP, UK
| | - Gabriel Rogers
- Division of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK
| | - Anna Donten
- Division of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK
| | - Katherine Payne
- Division of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK
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Walker MJ, Blackmore KM, Chang A, Lambert-Côté L, Turgeon A, Antoniou AC, Bell KA, Broeders MJM, Brooks JD, Carver T, Chiquette J, Després P, Easton DF, Eisen A, Eloy L, Evans DG, Fienberg S, Joly Y, Kim RH, Kim SJ, Knoppers BM, Lofters AK, Nabi H, Paquette JS, Pashayan N, Sheppard AJ, Stockley TL, Dorval M, Simard J, Chiarelli AM. Implementing Multifactorial Risk Assessment with Polygenic Risk Scores for Personalized Breast Cancer Screening in the Population Setting: Challenges and Opportunities. Cancers (Basel) 2024; 16:2116. [PMID: 38893236 PMCID: PMC11171515 DOI: 10.3390/cancers16112116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/11/2024] [Accepted: 05/18/2024] [Indexed: 06/21/2024] Open
Abstract
Risk-stratified breast screening has been proposed as a strategy to overcome the limitations of age-based screening. A prospective cohort study was undertaken within the PERSPECTIVE I&I project, which will generate the first Canadian evidence on multifactorial breast cancer risk assessment in the population setting to inform the implementation of risk-stratified screening. Recruited females aged 40-69 unaffected by breast cancer, with a previous mammogram, underwent multifactorial breast cancer risk assessment. The adoption of multifactorial risk assessment, the effectiveness of methods for collecting risk factor information and the costs of risk assessment were examined. Associations between participant characteristics and study sites, as well as data collection methods, were assessed using logistic regression; all p-values are two-sided. Of the 4246 participants recruited, 88.4% completed a risk assessment, with 79.8%, 15.7% and 4.4% estimated at average, higher than average and high risk, respectively. The total per-participant cost for risk assessment was CAD 315. Participants who chose to provide risk factor information on paper/telephone (27.2%) vs. online were more likely to be older (p = 0.021), not born in Canada (p = 0.043), visible minorities (p = 0.01) and have a lower attained education (p < 0.0001) and perceived fair/poor health (p < 0.001). The 34.4% of participants requiring risk factor verification for missing/unusual values were more likely to be visible minorities (p = 0.009) and have a lower attained education (p ≤ 0.006). This study demonstrates the feasibility of risk assessment for risk-stratified screening at the population level. Implementation should incorporate an equity lens to ensure cancer-screening disparities are not widened.
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Affiliation(s)
- Meghan J. Walker
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
| | | | - Amy Chang
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
| | | | - Annie Turgeon
- CHU de Québec-Université Laval Research Center, Queébec City, QC G1V 4G2, Canada
| | - Antonis C. Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK
| | - Kathleen A. Bell
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
| | - Mireille J. M. Broeders
- Department for Health Evidence, Radboud University Medical Center, 6525EP Nijmegen, The Netherlands
| | - Jennifer D. Brooks
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Tim Carver
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK
| | - Jocelyne Chiquette
- CHU de Québec-Université Laval Research Center, Queébec City, QC G1V 4G2, Canada
- Department of Family Medicine and Emergency Medicine, Faculty of Medicine, Université Laval, Québec City, QC G1V 0A6, Canada;
| | - Philippe Després
- Department of Physics, Engineering Physics and Optics, Faculty of Science and Engineering, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK
| | - Andrea Eisen
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
- Sunnybrook Health Science Center, Toronto, ON M4N 3M5, Canada
| | - Laurence Eloy
- Québec Cancer Program, Ministère de la Santé et des Services Sociaux, Quebec City, QC G1S 2M1, Canada
| | - D. Gareth Evans
- Division of Evolution Infection and Genomic Sciences, The University of Manchester, Manchester M13 9PL, UK
| | | | - Yann Joly
- Centre of Genomics and Policy, McGill University, Montreal, QC H3A 0G1, Canada
| | - Raymond H. Kim
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Shana J. Kim
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Bartha M. Knoppers
- Centre of Genomics and Policy, McGill University, Montreal, QC H3A 0G1, Canada
| | - Aisha K. Lofters
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
- Women’s College Research Institute, Toronto, ON M5G 1N8, Canada
| | - Hermann Nabi
- CHU de Québec-Université Laval Research Center, Queébec City, QC G1V 4G2, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
- Université Laval Cancer Research Center, Quebec City, QC G1R 3S3, Canada
| | - Jean-Sébastien Paquette
- Department of Family Medicine and Emergency Medicine, Faculty of Medicine, Université Laval, Québec City, QC G1V 0A6, Canada;
| | - Nora Pashayan
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, London WC1E 6BT, UK
| | - Amanda J. Sheppard
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Tracy L. Stockley
- Division of Clinical Laboratory Genetics, University Health Network, Toronto, ON M5G 2C4, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Michel Dorval
- CHU de Québec-Université Laval Research Center, Queébec City, QC G1V 4G2, Canada
- Université Laval Cancer Research Center, Quebec City, QC G1R 3S3, Canada
- Faculty of Pharmacy, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Jacques Simard
- CHU de Québec-Université Laval Research Center, Queébec City, QC G1V 4G2, Canada
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 4G2, Canada
| | - Anna M. Chiarelli
- Ontario Health (Cancer Care Ontario), Toronto, ON M5G 2L3, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
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Vallée A. Envisioning the Future of Personalized Medicine: Role and Realities of Digital Twins. J Med Internet Res 2024; 26:e50204. [PMID: 38739913 PMCID: PMC11130780 DOI: 10.2196/50204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 10/01/2023] [Accepted: 12/29/2023] [Indexed: 05/16/2024] Open
Abstract
Digital twins have emerged as a groundbreaking concept in personalized medicine, offering immense potential to transform health care delivery and improve patient outcomes. It is important to highlight the impact of digital twins on personalized medicine across the understanding of patient health, risk assessment, clinical trials and drug development, and patient monitoring. By mirroring individual health profiles, digital twins offer unparalleled insights into patient-specific conditions, enabling more accurate risk assessments and tailored interventions. However, their application extends beyond clinical benefits, prompting significant ethical debates over data privacy, consent, and potential biases in health care. The rapid evolution of this technology necessitates a careful balancing act between innovation and ethical responsibility. As the field of personalized medicine continues to evolve, digital twins hold tremendous promise in transforming health care delivery and revolutionizing patient care. While challenges exist, the continued development and integration of digital twins hold the potential to revolutionize personalized medicine, ushering in an era of tailored treatments and improved patient well-being. Digital twins can assist in recognizing trends and indicators that might signal the presence of diseases or forecast the likelihood of developing specific medical conditions, along with the progression of such diseases. Nevertheless, the use of human digital twins gives rise to ethical dilemmas related to informed consent, data ownership, and the potential for discrimination based on health profiles. There is a critical need for robust guidelines and regulations to navigate these challenges, ensuring that the pursuit of advanced health care solutions does not compromise patient rights and well-being. This viewpoint aims to ignite a comprehensive dialogue on the responsible integration of digital twins in medicine, advocating for a future where technology serves as a cornerstone for personalized, ethical, and effective patient care.
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Affiliation(s)
- Alexandre Vallée
- Department of Epidemiology and Public Health, Foch Hospital, Suresnes, France
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Gennaro G, Bucchi L, Ravaioli A, Zorzi M, Falcini F, Russo F, Caumo F. The risk-based breast screening (RIBBS) study protocol: a personalized screening model for young women. LA RADIOLOGIA MEDICA 2024; 129:727-736. [PMID: 38512619 PMCID: PMC11088554 DOI: 10.1007/s11547-024-01797-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 02/02/2024] [Indexed: 03/23/2024]
Abstract
The optimal mammography screening strategy for women aged 45-49 years is a matter of debate. We present the RIBBS study protocol, a quasi-experimental, prospective, population-based study comparing a risk- and breast density-stratified screening model (interventional cohort) with annual digital mammography (DM) screening (observational control cohort) in a real-world setting. The interventional cohort consists of 10,269 women aged 45 years enrolled between 2020 and 2021 from two provinces of the Veneto Region (northen Italy). At baseline, participants underwent two-view digital breast tomosynthesis (DBT) and completed the Tyrer-Cuzick risk prediction model. Volumetric breast density (VBD) was calculated from DBT and the lifetime risk (LTR) was estimated by including VBD among the risk factors. Based on VBD and LTR, women were classified into five subgroups with specific screening protocols for subsequent screening rounds: (1) LTR ≤ 17% and nondense breast: biennial DBT; (2) LTR ≤ 17% and dense breast: biennial DBT and ultrasound; (3) LTR 17-30% or LTR > 30% without family history of BC, and nondense breast: annual DBT; (4) LTR 17-30% or > 30% without family history of BC, and dense breast: annual DBT and ultrasound; and (5) LTR > 30% and family history of BC: annual DBT and breast MRI. The interventional cohort is still ongoing. An observational, nonequivalent control cohort of 43,000 women aged 45 years participating in an annual DM screening programme was recruited in three provinces of the neighbouring Emilia-Romagna Region. Cumulative incidence rates of advanced BC at three, five, and ten years between the two cohorts will be compared, adjusting for the incidence difference at baseline.Trial registration This study is registered on Clinicaltrials.gov (NCT05675085).
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Affiliation(s)
| | - Lauro Bucchi
- Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy.
| | - Alessandra Ravaioli
- Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy
| | - Manuel Zorzi
- SER - Servizio Epidemiologico Regionale e Registri, Azienda Zero, Padua, Italy
| | - Fabio Falcini
- Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy
- Cancer Prevention Unit, Local Health Authority, Forlì, Italy
| | - Francesca Russo
- Direzione Prevenzione, Sicurezza Alimentare, Veterinaria, Regione del Veneto, Venice, Italy
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Zhao D, Wu T, Tan Z, Xu J, Lu Z. Role of non-coding RNAs mediated pyroptosis on cancer therapy: a review. Expert Rev Anticancer Ther 2024; 24:239-251. [PMID: 38594965 DOI: 10.1080/14737140.2024.2341737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 04/08/2024] [Indexed: 04/11/2024]
Abstract
INTRODUCTION Non-coding RNAs (ncRNAs), which are incapable of encoding proteins, are involved in the progression of numerous tumors by altering transcriptional and post-transcriptional processing. Recent studies have revealed prominent features of ncRNAs in pyroptosis, a type of non-apoptotic programmed cellular destruction linked to an inflammatory reaction. Drug resistance has arisen gradually as a result of anti-apoptotic proteins, therefore strategies based on pyroptotic cell death have attracted increasing attention. We have observed that ncRNAs may exert significant influence on cancer therapy, chemotherapy, radio- therapy, targeted therapy and immunotherapy, by regulating pyroptosis. AREAS COVERED Literatures were searched (December 2023) for studies on cancer therapy for ncRNAs-mediated pyroptotic cell death. EXPERT OPINION The most universal mechanical strategy for ncRNAs to regulate target genes is competitive endogenous RNAs (ceRNA). Besides, certain ncRNAs could directly interact with proteins and modulate downstream genes to induce pyroptosis, resulting in tumor growth or inhibition. In this review, we aim to display that ncRNAs, predominantly long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and circular RNAs (circRNAs), could function as potential biomarkers for diagnosis and prognosis and produce new insights into anti-cancer strategies modulated by pyroptosis for clinical applications.
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Affiliation(s)
- Dan Zhao
- School of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, China
- Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tangwei Wu
- Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheqiong Tan
- Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia Xu
- School of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, China
- Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhongxin Lu
- School of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, China
- Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Cancer Research Institute of Wuhan, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory for Molecular Diagnosis of Hubei Province, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Rossi M, Radisky DC. Multiplex Digital Spatial Profiling in Breast Cancer Research: State-of-the-Art Technologies and Applications across the Translational Science Spectrum. Cancers (Basel) 2024; 16:1615. [PMID: 38730568 PMCID: PMC11083340 DOI: 10.3390/cancers16091615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/17/2024] [Accepted: 04/21/2024] [Indexed: 05/13/2024] Open
Abstract
While RNA sequencing and multi-omic approaches have significantly advanced cancer diagnosis and treatment, their limitation in preserving critical spatial information has been a notable drawback. This spatial context is essential for understanding cellular interactions and tissue dynamics. Multiplex digital spatial profiling (MDSP) technologies overcome this limitation by enabling the simultaneous analysis of transcriptome and proteome data within the intact spatial architecture of tissues. In breast cancer research, MDSP has emerged as a promising tool, revealing complex biological questions related to disease evolution, identifying biomarkers, and discovering drug targets. This review highlights the potential of MDSP to revolutionize clinical applications, ranging from risk assessment and diagnostics to prognostics, patient monitoring, and the customization of treatment strategies, including clinical trial guidance. We discuss the major MDSP techniques, their applications in breast cancer research, and their integration in clinical practice, addressing both their potential and current limitations. Emphasizing the strategic use of MDSP in risk stratification for women with benign breast disease, we also highlight its transformative potential in reshaping the landscape of breast cancer research and treatment.
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Affiliation(s)
| | - Derek C. Radisky
- Department of Cancer Biology, Mayo Clinic, Jacksonville, FL 32224, USA;
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Guo R, Feng R, Yang J, Xiao Y, Yin C. Genetic correlation and Mendelian randomization analyses support causal relationships between dietary habits and age at menarche. Sci Rep 2024; 14:8425. [PMID: 38600095 PMCID: PMC11006932 DOI: 10.1038/s41598-024-58999-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 04/05/2024] [Indexed: 04/12/2024] Open
Abstract
Dietary habits are essential in the mean age at menarche (AAM). However, the causal relationship between these factors remains unclear. Therefore, this study aimed to elucidate the genetic relationship between dietary habits and AAM. Genetic summary statistics for dietary habits were obtained from the UK Biobank. GWAS summary data for AAM was obtained from the ReproGen Consortium. Linkage disequilibrium score regression was used to test genetic correlations between dietary habits and AAM. The Mendelian randomization (MR) analyses used the inverse-variance weighted method. Genetic correlations with AAM were identified for 29 candi-date dietary habits, such as milk type (skimmed, semi-skimmed, full cream; coefficient = 0.2704, Pldsc = 1.13 × 10-14). MR evaluations revealed that 19 dietary habits were associated with AAM, including bread type (white vs. any other; OR 1.71, 95% CI 1.28-2.29, Pmr = 3.20 × 10-4), tablespoons of cooked vegetables (OR 0.437, 95% CI 0.29-0.67; Pmr = 1.30 × 10-4), and cups of coffee per day (OR 0.72, 95% CI 0.57-0.92, Pmr = 8.31 × 10-3). These results were observed to be stable under the sensitivity analysis. Our study provides potential insights into the genetic mechanisms underlying AAM and evidence that dietary habits are associated with AAM.
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Affiliation(s)
- Ruilong Guo
- Department of Pediatrics, Xi'an Jiaotong University Second Affiliated Hospital, Xi'an, 710054, Shanxi, China
| | - Ruoyang Feng
- Department of Joint Surgery, Xi'an Jiaotong University Hong Hui Hospital, Xi'an, 710054, Shanxi, China
| | - Jiong Yang
- Department of Pediatrics, Xi'an Jiaotong University Second Affiliated Hospital, Xi'an, 710054, Shanxi, China
| | - Yanfeng Xiao
- Department of Pediatrics, Xi'an Jiaotong University Second Affiliated Hospital, Xi'an, 710054, Shanxi, China.
| | - Chunyan Yin
- Department of Pediatrics, Xi'an Jiaotong University Second Affiliated Hospital, Xi'an, 710054, Shanxi, China.
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9
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Gonzalez T, Nie Q, Chaudhary LN, Basel D, Reddi HV. Methylation signatures as biomarkers for non-invasive early detection of breast cancer: A systematic review of the literature. Cancer Genet 2024; 282-283:1-8. [PMID: 38134587 DOI: 10.1016/j.cancergen.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 12/10/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND Early detection of breast cancer would help alleviate the burden of treatment for early-stage breast cancer and help patient prognosis. There is currently no established gene panel that utilizes the potential of DNA methylation as a molecular signature for the early detection of breast cancer. This systematic review aims to identify the optimal methylation biomarkers for a non-invasive liquid biopsy assay and the gaps in knowledge regarding biomarkers for early detection of breast cancer. METHODS Following the PRISMA-ScR method, Pubmed and Google Scholar was searched for publications related to methylation biomarkers in breast cancer over a five-year period. Eligible publications were mined for key data fields such as study aims, cohort demographics, types of breast cancer studied, technologies used, and outcomes. Data was analyzed to address the objectives of the review. RESULTS Literature search identified 112 studies of which based on eligibility criteria, 13 studies were included. 28 potential methylation gene targets were identified, of which 23 were methylated at the promoter region, 1 was methylated in the body of the gene and 4 were methylated at yet to be identified locations. CONCLUSIONS Our evaluation shows that at minimum APC, RASSFI, and FOXA1 genes would be a promising set of genes to start with for the early detection of breast cancer, based on the sensitivity and specificity outlined in the studies. Prospective studies are needed to optimize biomarkers for broader impact in early detection of breast cancer.
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Affiliation(s)
- Tessa Gonzalez
- Division of Precision Medicine and Cytogenetics, Department of Pathology, Medical College of Wisconsin, CT, USA
| | - Qian Nie
- Division of Precision Medicine and Cytogenetics, Department of Pathology, Medical College of Wisconsin, CT, USA
| | - Lubna N Chaudhary
- Division of Division of Hematology/Oncology, Department of Medicine, Medical College of Wisconsin, CT, USA
| | - Donald Basel
- Division of Genetics, Department of Pediatrics, Medical College of Wisconsin, CT, USA
| | - Honey V Reddi
- Division of Precision Medicine and Cytogenetics, Department of Pathology, Medical College of Wisconsin, CT, USA.
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10
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Dunlop KLA, Singh N, Robbins HA, Zahed H, Johansson M, Rankin NM, Cust AE. Implementation considerations for risk-tailored cancer screening in the population: A scoping review. Prev Med 2024; 181:107897. [PMID: 38378124 PMCID: PMC11106520 DOI: 10.1016/j.ypmed.2024.107897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 02/10/2024] [Accepted: 02/14/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Risk-tailored screening has emerged as a promising approach to optimise the balance of benefits and harms of existing population cancer screening programs. It tailors screening (e.g., eligibility, frequency, interval, test type) to individual risk rather than the current one-size-fits-all approach of most organised population screening programs. However, the implementation of risk-tailored cancer screening in the population is challenging as it requires a change of practice at multiple levels i.e., individual, provider, health system levels. This scoping review aims to synthesise current implementation considerations for risk-tailored cancer screening in the population, identifying barriers, facilitators, and associated implementation outcomes. METHODS Relevant studies were identified via database searches up to February 2023. Results were synthesised using Tierney et al. (2020) guidance for evidence synthesis of implementation outcomes and a multilevel framework. RESULTS Of 4138 titles identified, 74 studies met the inclusion criteria. Most studies in this review focused on the implementation outcomes of acceptability, feasibility, and appropriateness, reflecting the pre-implementation stage of most research to date. Only six studies included an implementation framework. The review identified consistent evidence that risk-tailored screening is largely acceptable across population groups, however reluctance to accept a reduction in screening frequency for low-risk informed by cultural norms, presents a major barrier. Limited studies were identified for cancer types other than breast cancer. CONCLUSIONS Implementation strategies will need to address alternate models of delivery, education of health professionals, communication with the public, screening options for people at low risk of cancer, and inequity in outcomes across cancer types.
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Affiliation(s)
- Kate L A Dunlop
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia.
| | - Nehal Singh
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia
| | - Hilary A Robbins
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Hana Zahed
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Mattias Johansson
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Nicole M Rankin
- Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia; Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Anne E Cust
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia; Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
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11
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Pace LE, Keating NL. New Recommendations for Breast Cancer Screening-In Pursuit of Health Equity. JAMA Netw Open 2024; 7:e2411638. [PMID: 38687485 DOI: 10.1001/jamanetworkopen.2024.11638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024] Open
Affiliation(s)
- Lydia E Pace
- Division of Women's Health, Brigham and Women's Hospital, Boston, Massachusetts
- Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Maryland
| | - Nancy L Keating
- Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Maryland
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
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12
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Laza C, Niño de Guzmán E, Gea M, Plazas M, Posso M, Rué M, Castells X, Román M. "For and against" factors influencing participation in personalized breast cancer screening programs: a qualitative systematic review until March 2022. Arch Public Health 2024; 82:23. [PMID: 38389068 PMCID: PMC10882761 DOI: 10.1186/s13690-024-01248-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 02/05/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Personalized breast cancer screening is a novel strategy that estimates individual risk based on age, breast density, family history of breast cancer, personal history of benign breast lesions, and polygenic risk. Its goal is to propose personalized early detection recommendations for women in the target population based on their individual risk. Our aim was to synthesize the factors that influence women's decision to participate in personalized breast cancer screening, from the perspective of women and health care professionals. METHODS Systematic review of qualitative evidence on factors influencing participation in personalized Breast Cancer Screening. We searched in Medline, Web of science, Scopus, EMBASE, CINAHL and PsycINFO for qualitative and mixed methods studies published up to March 2022. Two reviewers conducted study selection and extracted main findings. We applied the best-fit framework synthesis and adopted the Multilevel influences on the cancer care continuum model for analysis. After organizing initial codes into the seven levels of the selected model, we followed thematic analysis and developed descriptive and analytical themes. We assessed the methodological quality with the Critical Appraisal Skills Program tool. RESULTS We identified 18 studies published between 2017 and 2022, conducted in developed countries. Nine studies were focused on women (n = 478) and in four studies women had participated in a personalized screening program. Nine studies focused in health care professionals (n = 162) and were conducted in primary care and breast cancer screening program settings. Factors influencing women's decision to participate relate to the women themselves, the type of program (personalized breast cancer screening) and perspective of health care professionals. Factors that determined women participation included persistent beliefs and insufficient knowledge about breast cancer and personalized screening, variable psychological reactions, and negative attitudes towards breast cancer risk estimates. Other factors against participation were insufficient health care professionals knowledge on genetics related to breast cancer and personalized screening process. The factors that were favourable included the women's perceived benefits for themselves and the positive impact on health systems. CONCLUSION We identified the main factors influencing women's decisions to participate in personalized breast cancer screening. Factors related to women, were the most relevant negative factors. A future implementation requires improving health literacy for women and health care professionals, as well as raising awareness of the strategy in society.
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Affiliation(s)
- Celmira Laza
- Department of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Biomedical Research Institute of Lleida Fundació Dr. Pifarré (IRBLleida), Lleida, Spain
| | - Ena Niño de Guzmán
- Cancer Prevention and Control Program, Institut Català d' Oncologia, Barcelona, Spain
| | - Montserrat Gea
- Department of Nursing and Physiotherapy, University of Lleida, Lleida, Spain
- Biomedical Research Institute of Lleida Fundació Dr. Pifarré (IRBLleida), Lleida, Spain
| | - Merideidy Plazas
- Cochrane Associated Center- University Foundation of Health Sciences, Bogotá, Colombia
| | - Margarita Posso
- Department of Epidemiology and Evaluation, Hospital del Mar Research Institute, Barcelona, Spain
| | - Montserrat Rué
- Biomedical Research Institute of Lleida Fundació Dr. Pifarré (IRBLleida), Lleida, Spain
- Basic Medical Sciences, University of Lleida, Lleida, Spain
| | - Xavier Castells
- Department of Epidemiology and Evaluation, Hospital del Mar Research Institute, Barcelona, Spain
| | - Marta Román
- Department of Epidemiology and Evaluation, Hospital del Mar Research Institute, Barcelona, Spain.
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13
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Piergentili R, Marinelli E, Cucinella G, Lopez A, Napoletano G, Gullo G, Zaami S. miR-125 in Breast Cancer Etiopathogenesis: An Emerging Role as a Biomarker in Differential Diagnosis, Regenerative Medicine, and the Challenges of Personalized Medicine. Noncoding RNA 2024; 10:16. [PMID: 38525735 PMCID: PMC10961778 DOI: 10.3390/ncrna10020016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/10/2024] [Accepted: 02/19/2024] [Indexed: 03/26/2024] Open
Abstract
Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.
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Affiliation(s)
- Roberto Piergentili
- Institute of Molecular Biology and Pathology, Italian National Research Council (CNR-IBPM), 00185 Rome, Italy;
| | - Enrico Marinelli
- Department of Medico-Surgical Sciences and Biotechnologies, “Sapienza” University of Rome, 04100 Latina, Italy;
| | - Gaspare Cucinella
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.C.); (A.L.); (G.G.)
| | - Alessandra Lopez
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.C.); (A.L.); (G.G.)
| | - Gabriele Napoletano
- Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Section of Forensic Medicine, “Sapienza” University of Rome, 00161 Rome, Italy;
| | - Giuseppe Gullo
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.C.); (A.L.); (G.G.)
| | - Simona Zaami
- Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Section of Forensic Medicine, “Sapienza” University of Rome, 00161 Rome, Italy;
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14
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LA Dunlop K, Smit AK, Keogh LA, Newson AJ, Rankin NM, Cust AE. Acceptability of risk-tailored cancer screening among Australian GPs: a qualitative study. Br J Gen Pract 2024; 74:BJGP.2023.0117. [PMID: 38373853 PMCID: PMC10904141 DOI: 10.3399/bjgp.2023.0117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 05/22/2023] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Cancer screening that is tailored to individual risk has the potential to improve health outcomes and reduce screening-related harms, if implemented well. However, successful implementation depends on acceptability, particularly as this approach will require GPs to change their practice. AIM To explore Australian GPs' views about the acceptability of risk-tailored screening across cancer types and to identify barriers to and facilitators of implementation. DESIGN AND SETTING A qualitative study using semi-structured interviews with Australian GPs. METHOD Interviews were carried out with GPs and audio-recorded and transcribed. Data were first analysed inductively then deductively using an implementation framework. RESULTS Participants (n = 20) found risk-tailored screening to be acceptable in principle, recognising potential benefits in offering enhanced screening to those at highest risk. However, they had significant concerns that changes in screening advice could potentially cause confusion. They also reported that a reduced screening frequency or exclusion from a screening programme for those deemed low risk may not initially be acceptable, especially for common cancers with minimally invasive screening. Other reservations about implementing risk-tailored screening in general practice included a lack of high-quality evidence of benefit, fear of missing the signs or symptoms of a patient's cancer, and inadequate time with patients. While no single preferred approach to professional education was identified, education around communicating screening results and risk stratification was considered important. CONCLUSION GPs may not currently be convinced of the net benefits of risk-tailored screening. Development of accessible evidence-based guidelines, professional education, risk calculators, and targeted public messages will increase its feasibility in general practice.
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Affiliation(s)
- Kate LA Dunlop
- The Daffodil Centre, a joint venture with Cancer Council NSW and Melanoma Institute Australia, University of Sydney, Sydney
| | - Amelia K Smit
- The Daffodil Centre, a joint venture with Cancer Council NSW and Melanoma Institute Australia, University of Sydney, Sydney
| | - Louise A Keogh
- Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne
| | - Ainsley J Newson
- Faculty of Medicine and Health, Sydney School of Public Health, Sydney Health Ethics, University of Sydney, Sydney
| | - Nicole M Rankin
- Evaluation and Implementation Science Unit, Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne
| | - Anne E Cust
- The Daffodil Centre, a joint venture with Cancer Council NSW and Melanoma Institute Australia, University of Sydney, Sydney
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15
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Yiangou K, Mavaddat N, Dennis J, Zanti M, Wang Q, Bolla MK, Abubakar M, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Baten A, Behrens S, Bermisheva M, de Gonzalez AB, Białkowska K, Boddicker N, Bodelon C, Bogdanova NV, Bojesen SE, Brantley KD, Brauch H, Brenner H, Camp NJ, Canzian F, Castelao JE, Cessna MH, Chang-Claude J, Chenevix-Trench G, Chung WK, Colonna SV, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dunning AM, Eccles DM, Eliassen AH, Engel C, Eriksson M, Evans DG, Fasching PA, Fletcher O, Flyger H, Fritschi L, Gago-Dominguez M, Gentry-Maharaj A, González-Neira A, Guénel P, Hahnen E, Haiman CA, Hamann U, Hartikainen JM, Ho V, Hodge J, Hollestelle A, Honisch E, Hooning MJ, Hoppe R, Hopper JL, Howell S, Howell A, Jakovchevska S, Jakubowska A, Jernström H, Johnson N, Kaaks R, Khusnutdinova EK, Kitahara CM, Koutros S, Kristensen VN, Lacey JV, Lambrechts D, Lejbkowicz F, Lindblom A, Lush M, Mannermaa A, Mavroudis D, Menon U, Murphy RA, Nevanlinna H, Obi N, Offit K, Park-Simon TW, Patel AV, Peng C, Peterlongo P, Pita G, Plaseska-Karanfilska D, Pylkäs K, Radice P, Rashid MU, Rennert G, Roberts E, Rodriguez J, Romero A, Rosenberg EH, Saloustros E, Sandler DP, Sawyer EJ, Schmutzler RK, Scott CG, Shu XO, Southey MC, Stone J, Taylor JA, Teras LR, van de Beek I, Willett W, Winqvist R, Zheng W, Vachon CM, Schmidt MK, Hall P, MacInnis RJ, Milne RL, Pharoah PD, Simard J, Antoniou AC, Easton DF, Michailidou K. Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.12.24302043. [PMID: 38410445 PMCID: PMC10896416 DOI: 10.1101/2024.02.12.24302043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
The 313-variant polygenic risk score (PRS313) provides a promising tool for breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. Here, we explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 225,105 female participants from the UK Biobank. The mean PRS313 differed markedly across European countries, being highest in south-eastern Europe and lowest in north-western Europe. Using the overall European PRS313 distribution to categorise individuals leads to overestimation and underestimation of risk in some individuals from south-eastern and north-western countries, respectively. Adjustment for principal components explained most of the observed heterogeneity in mean PRS. Country-specific PRS distributions may be used to calibrate risk categories in individuals from different countries.
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Affiliation(s)
- Kristia Yiangou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus, 2371
| | - Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Maria Zanti
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus, 2371
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Mustapha Abubakar
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA, 20850
| | - Thomas U. Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA, 20850
| | - Irene L. Andrulis
- Fred A, Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada, M5G 1X5
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, M5S 1A8
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA, 92617
| | - Natalia N. Antonenkova
- NN Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus, 223040
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Kristan J. Aronson
- Department of Public Health Sciences, and Cancer Research Institute, Queen’s University, Kingston, ON, Canada, K7L 3N6
| | | | - Adinda Baten
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium, 3000
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia, 450054
- St Petersburg State University, St, Petersburg, Russia, 199034
| | | | - Katarzyna Białkowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland, 71-252
| | - Nicholas Boddicker
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA, 55905
| | - Clara Bodelon
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Natalia V. Bogdanova
- NN Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus, 223040
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany, 30625
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany, 30625
| | - Stig E. Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark, 2730
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark, 2730
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, 2200
| | - Kristen D. Brantley
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
| | - Hiltrud Brauch
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany, 70376
- iFIT-Cluster of Excellence, University of Tübingen, Tübingen, Germany, 72074
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner Site Tübingen, Tübingen, Germany, 72074
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany, 69120
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Nicola J. Camp
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA, 84112
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Jose E. Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS) Foundation, Complejo Hospitalario Universitario de Santiago, SERGAS, Vigo, Spain, 36312
| | - Melissa H. Cessna
- Department of Pathology, Intermountain Healthcare, Salt Lake City, UT, USA, 84143
- Intermountain Biorepository, Intermountain Healthcare, Salt Lake City, UT, USA, 84143
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 20246
| | - Georgia Chenevix-Trench
- Cancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia, 4006
| | - Wendy K. Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA, 10032
| | - NBCS Collaborators
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet, Oslo, Norway, 0379
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway, 0450
- Department of Research, Vestre Viken Hospital, Drammen, Norway, 3019
- Section for Breast- and Endocrine Surgery, Department of Cancer, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital-Ullevål, Oslo, Norway, 0450
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway, 0379
- Department of Pathology, Akershus University Hospital, Lørenskog, Norway, 1478
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway, 0379
- Department of Oncology, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital-Radiumhospitalet, Oslo, Norway, 0379
- National Advisory Unit on Late Effects after Cancer Treatment, Oslo University Hospital, Oslo, Norway, 0379
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway, 1478
- Oslo Breast Cancer Research Consortium, Oslo University Hospital, Oslo, Norway, 0379
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway, 0379
| | - Sarah V. Colonna
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA, 84112
| | - Fergus J. Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA, 55905
| | - Angela Cox
- Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK, S10 2TN
| | - Simon S. Cross
- Division of Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, UK, S10 2TN
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
| | - Mary B. Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA, 19111
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands, 2333 ZA
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands, 2333 ZA
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany, 30625
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Diana M. Eccles
- Faculty of Medicine, University of Southampton, Southampton, UK, SO17 1BJ
| | - A. Heather Eliassen
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA, 02115
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany, 04107
- LIFE - Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany, 04103
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
| | - D. Gareth Evans
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK, M13 9WL
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK, M13 9WL
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany, 91054
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK, SW7 3RP
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark, 2730
| | - Lin Fritschi
- School of Population Health, Curtin University, Perth, Western Australia, Australia, 6102
| | - Manuela Gago-Dominguez
- Cancer Genetics and Epidemiology Group, Genomic Medicine Group, Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain, 15706
| | - Aleksandra Gentry-Maharaj
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK, WC1V 6LJ
- Department of Women’s Cancer, Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK
| | - Anna González-Neira
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain, 28029
- Spanish Network on Rare Diseases (CIBERER)
| | - Pascal Guénel
- Team ‘Exposome and Heredity’, CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France, 94805
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA, 90033
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Jaana M. Hartikainen
- Cancer RC, University of Eastern Finland, Kuopio, Finland, 70210
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland, 70210
| | - Vikki Ho
- Health Innovation and Evaluation Hub, Université de Montréal Hospital Research Centre (CRCHUM), Montréal, Québec, Canada
| | - James Hodge
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Antoinette Hollestelle
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands, 3015 GD
| | - Ellen Honisch
- Department of Gynecology and Obstetrics, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany, 40225
| | - Maartje J. Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands, 3015 GD
| | - Reiner Hoppe
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany, 70376
- University of Tübingen, Tübingen, Germany, 72074
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
| | - Sacha Howell
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK
| | - Anthony Howell
- Division of Cancer Sciences, University of Manchester, Manchester, UK, M13 9PL
| | - ABCTB Investigators
- Australian Breast Cancer Tissue Bank, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia, 2145
| | - kConFab Investigators
- Research Department, Peter MacCallum Cancer Center, Melbourne, Victoria, Australia, 3000
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia, 3000
| | - Simona Jakovchevska
- Research Centre for Genetic Engineering and Biotechnology ‘Georgi D, Efremov’, MASA, Skopje, Republic of North Macedonia, 1000
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland, 71-252
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland, 171-252
| | - Helena Jernström
- Oncology, Clinical Sciences in Lund, Lund University, Lund, Sweden, 221 85
| | - Nichola Johnson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK, SW7 3RP
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Elza K. Khusnutdinova
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia, 450054
- Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, Ufa, Russia, 450076
| | - Cari M. Kitahara
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA, 20892
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA, 20850
| | - Vessela N. Kristensen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway, 0450
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway, 0379
| | - James V. Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA, 91010
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA, 91010
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium, 3000
- VIB Center for Cancer Biology, VIB, Leuven, Belgium, 3001
| | | | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden, 171 76
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden, 171 76
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Arto Mannermaa
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland, 70210
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland, 70210
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece, 711 10
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK, WC1V 6LJ
| | - Rachel A. Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4
- Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada, V5Z 1L3
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland, 00290
| | - Nadia Obi
- Institute for Occupational and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 20246
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 20246
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA, 10065
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, 10065
| | | | - Alpa V. Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Cheng Peng
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA, 02115
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy, 20139
| | - Guillermo Pita
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain, 28029
| | - Dijana Plaseska-Karanfilska
- Research Centre for Genetic Engineering and Biotechnology ‘Georgi D, Efremov’, MASA, Skopje, Republic of North Macedonia, 1000
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland, 90220
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland, 90220
| | - Paolo Radice
- Unit of Predictice Medicine, Molecular Bases of Genetic Risk, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy, 20133
| | - Muhammad U. Rashid
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
- Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Centre (SKMCH & RC), Lahore, Pakistan, 54000
| | - Gad Rennert
- Technion, Faculty of Medicine and Association for Promotion of Research in Precision Medicine, Haifa, Israel
| | - Eleanor Roberts
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Juan Rodriguez
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
| | - Atocha Romero
- Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid, Spain, 28222
| | - Efraim H. Rosenberg
- Department of Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands, 1066 CX
| | | | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA, 27709
| | - Elinor J. Sawyer
- School of Cancer & Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy’s Campus, King’s College London, London, UK
| | - Rita K. Schmutzler
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
- Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50931
| | - Christopher G. Scott
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA, 55905
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA, 37232
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia, 3168
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia, 3004
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia, 6000
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA, 27709
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA, 27709
| | - Lauren R. Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Irma van de Beek
- Department of Clinical Genetics, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands, 1066 CX
| | - Walter Willett
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA, 02115
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland, 90220
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland, 90220
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA, 37232
| | - Celine M. Vachon
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA, 55905
| | - Marjanka K. Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands, 1066 CX
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands, 1066 CX
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands, 2333 ZA
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
- Department of Oncology, Södersjukhuset, Stockholm, Sweden, 118 83
| | - Robert J. MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia, 3004
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia, 3168
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia, 3004
| | - Paul D.P. Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA, USA, 90069
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec – Université Laval Research Center, Québec City, Québec, Canada, G1V 4G2
| | - Antonis C. Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus, 2371
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
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16
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Eriksson M, Román M, Gräwingholt A, Castells X, Nitrosi A, Pattacini P, Heywang-Köbrunner S, Rossi PG. European validation of an image-derived AI-based short-term risk model for individualized breast cancer screening-a nested case-control study. THE LANCET REGIONAL HEALTH. EUROPE 2024; 37:100798. [PMID: 38362558 PMCID: PMC10866984 DOI: 10.1016/j.lanepe.2023.100798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 02/17/2024]
Abstract
Background Image-derived artificial intelligence (AI)-based risk models for breast cancer have shown high discriminatory performances compared with clinical risk models based on family history and lifestyle factors. However, little is known about their generalizability across European screening settings. We therefore investigated the discriminatory performances of an AI-based risk model in European screening settings. Methods Using four European screening populations in three countries (Italy, Spain, Germany) screened between 2009 and 2020 for women aged 45-69, we performed a nested case-control study to assess the predictive performance of an AI-based risk model. In total, 739 women with incident breast cancers were included together with 7812 controls matched on year of study-entry. Mammographic features (density, microcalcifications, masses, left-right breast asymmetries of these features) were extracted using AI from negative digital mammograms at study-entry. Two-year absolute risks of breast cancer were predicted and assessed after two years of follow-up. Adjusted risk stratification performance metrics were reported per clinical guidelines. Findings The overall adjusted Area Under the receiver operating characteristic Curve (aAUC) of the AI risk model was 0.72 (95% CI 0.70-0.75) for breast cancers developed in four screening populations. In the 6.2% [529/8551] of women at high risk using the National Institute of Health and Care Excellence (NICE) guidelines thresholds, cancers were more likely diagnosed after 2 years follow-up, risk-ratio (RR) 6.7 (95% CI 5.6-8.0), compared with the 69% [5907/8551] of women classified at general risk by the model. Similar risk-ratios were observed across levels of mammographic density. Interpretation The AI risk model showed generalizable discriminatory performances across European populations and, predicted ∼30% of clinically relevant stage 2 and higher breast cancers in ∼6% of high-risk women who were sent home with a negative mammogram. Similar results were seen in women with fatty and dense breasts. Funding Swedish Research Council.
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Affiliation(s)
- Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Public Health and Primary Care, University of Cambridge, UK
| | - Marta Román
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | | | - Xavier Castells
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Andrea Nitrosi
- Azienda Unitá Sanitaria Locale-IRCCS di Reggio Emilia, Reggia Emilia, Italy
| | | | | | - Paolo G. Rossi
- Azienda Unitá Sanitaria Locale-IRCCS di Reggio Emilia, Reggia Emilia, Italy
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17
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Valentini V, Bucalo A, Conti G, Celli L, Porzio V, Capalbo C, Silvestri V, Ottini L. Gender-Specific Genetic Predisposition to Breast Cancer: BRCA Genes and Beyond. Cancers (Basel) 2024; 16:579. [PMID: 38339330 PMCID: PMC10854694 DOI: 10.3390/cancers16030579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/12/2024] Open
Abstract
Among neoplastic diseases, breast cancer (BC) is one of the most influenced by gender. Despite common misconceptions associating BC as a women-only disease, BC can also occur in men. Additionally, transgender individuals may also experience BC. Genetic risk factors play a relevant role in BC predisposition, with important implications in precision prevention and treatment. The genetic architecture of BC susceptibility is similar in women and men, with high-, moderate-, and low-penetrance risk variants; however, some sex-specific features have emerged. Inherited high-penetrance pathogenic variants (PVs) in BRCA1 and BRCA2 genes are the strongest BC genetic risk factor. BRCA1 and BRCA2 PVs are more commonly associated with increased risk of female and male BC, respectively. Notably, BRCA-associated BCs are characterized by sex-specific pathologic features. Recently, next-generation sequencing technologies have helped to provide more insights on the role of moderate-penetrance BC risk variants, particularly in PALB2, CHEK2, and ATM genes, while international collaborative genome-wide association studies have contributed evidence on common low-penetrance BC risk variants, on their combined effect in polygenic models, and on their role as risk modulators in BRCA1/2 PV carriers. Overall, all these studies suggested that the genetic basis of male BC, although similar, may differ from female BC. Evaluating the genetic component of male BC as a distinct entity from female BC is the first step to improve both personalized risk assessment and therapeutic choices of patients of both sexes in order to reach gender equality in BC care. In this review, we summarize the latest research in the field of BC genetic predisposition with a particular focus on similarities and differences in male and female BC, and we also discuss the implications, challenges, and open issues that surround the establishment of a gender-oriented clinical management for BC.
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Affiliation(s)
- Virginia Valentini
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
| | - Agostino Bucalo
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
| | - Giulia Conti
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
| | - Ludovica Celli
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
| | - Virginia Porzio
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
| | - Carlo Capalbo
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
- Medical Oncology Unit, Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Valentina Silvestri
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
| | - Laura Ottini
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy; (V.V.); (A.B.); (G.C.); (L.C.); (V.P.); (C.C.); (V.S.)
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18
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Zhao T, Wang C, Zhao N, Qiao G, Hua J, Meng D, Liu L, Zhong B, Liu M, Wang Y, Bai C, Li Y. CYB561 promotes HER2+ breast cancer proliferation by inhibiting H2AFY degradation. Cell Death Discov 2024; 10:38. [PMID: 38245506 PMCID: PMC10799939 DOI: 10.1038/s41420-024-01804-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 12/23/2023] [Accepted: 01/04/2024] [Indexed: 01/22/2024] Open
Abstract
Breast cancer (BRCA) has a high incidence and mortality rate among women. Different molecular subtypes of breast cancer have different prognoses and require personalized therapies. It is imperative to find novel therapeutic targets for different molecular subtypes of BRCA. Here, we demonstrated for the first time that Cytochromeb561 (CYB561) is highly expressed in BRCA and correlates with poor prognosis, especially in HER2-positive BRCA. Overexpression of CYB561 could upregulate macroH2A (H2AFY) expression in HER2-positive BRCA cells through inhibition of H2AFY ubiquitination, and high expression of CYB561 in HER2-positive BRCA cells could promote the proliferation and migration of cells. Furthermore, we have demonstrated that CYB561 regulates H2AFY expression, thereby influencing the expression of NF-κB, a downstream molecule of H2AFY. These findings have been validated through in vivo experiments. In conclusion, we propose that CYB561 may represent a novel therapeutic target for the treatment of HER2-positive BRCA. Graphical abstract CYB561 promotes the proliferation of HER2+ BRCA cells: CYB561 enhances the expression of H2AFY by inhibiting its ubiquitination, which leads to an increase expression of NF-κB in the nucleus. H2AFY, together with NF-κB, promotes the proliferation of HER2+ BRCA cells.
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Affiliation(s)
- Ting Zhao
- Department of Clinical Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Chaomin Wang
- Department of Clinical Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Na Zhao
- Department of Clinical Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ge Qiao
- Department of Pathology, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Jialei Hua
- Department of Clinical Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Donghua Meng
- Department of Radiology, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Liming Liu
- Department of Public Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Benfu Zhong
- Department of Pediatric Oncology, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Miao Liu
- Department of Radiotherapy, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yichao Wang
- Department of Clinical Laboratory Medicine, The First People's Hospital of Xianyang, Xianyang, China.
| | - Changsen Bai
- Department of Clinical Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
| | - Yueguo Li
- Department of Clinical Laboratory, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
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19
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Shi A, Liu L, Li S, Qi B. Natural products targeting the MAPK-signaling pathway in cancer: overview. J Cancer Res Clin Oncol 2024; 150:6. [PMID: 38193944 PMCID: PMC10776710 DOI: 10.1007/s00432-023-05572-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 11/17/2023] [Indexed: 01/10/2024]
Abstract
PURPOSE This article summarizes natural products that target the MAPK-signaling pathway in cancer therapy. The classification, chemical structures, and anti-cancer mechanisms of these natural products are elucidated, and comprehensive information is provided on their potential use in cancer therapy. METHODS Using the PubMed database, we searched for keywords, including "tumor", "cancer", "natural product", "phytochemistry", "plant chemical components", and "MAPK-signaling pathway". We also screened for compounds with well-defined structures that targeting the MAPK-signaling pathway and have anti-cancer effects. We used Kingdraw software and Adobe Photoshop software to draw the chemical compound structural diagrams. RESULTS A total of 131 papers were searched, from which 85 compounds with well-defined structures were selected. These compounds have clear mechanisms for targeting cancer treatment and are mainly related to the MAPK-signaling pathway. Examples include eupatilin, carvacrol, oridonin, sophoridine, diosgenin, and juglone. These chemical components are classified as flavonoids, phenols, terpenoids, alkaloids, steroidal saponins, and quinones. CONCLUSIONS Certain MAPK pathway inhibitors have been used for clinical treatment. However, the clinical feedback has not been promising because of genomic instability, drug resistance, and side effects. Natural products have few side effects, good medicinal efficacy, a wide range of sources, individual heterogeneity of biological activity, and are capable of treating disease from multiple targets. These characteristics make natural products promising drugs for cancer treatment.
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Affiliation(s)
- Aiwen Shi
- Changchun University of Chinese Medicine, School of Phharmacy, 1035 Boshuo Road, Jingyue Street, Nanguan District, Changchun City, Jilin Province, China
| | - Li Liu
- Changchun University of Chinese Medicine, School of Phharmacy, 1035 Boshuo Road, Jingyue Street, Nanguan District, Changchun City, Jilin Province, China.
| | - Shuang Li
- Changchun University of Chinese Medicine, School of Phharmacy, 1035 Boshuo Road, Jingyue Street, Nanguan District, Changchun City, Jilin Province, China
| | - Bin Qi
- Changchun University of Chinese Medicine, School of Phharmacy, 1035 Boshuo Road, Jingyue Street, Nanguan District, Changchun City, Jilin Province, China.
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Yamaguchi H, Chang LC, Chang OSS, Chen YF, Hsiao YC, Wu CS, Hung MC. MRCK as a Potential Target for Claudin-Low Subtype of Breast Cancer. Int J Biol Sci 2024; 20:1-14. [PMID: 38164185 PMCID: PMC10750295 DOI: 10.7150/ijbs.88285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/09/2023] [Indexed: 01/03/2024] Open
Abstract
To find new molecular targets for triple negative breast cancer (TNBC), we analyzed a large-scale drug screening dataset based on breast cancer subtypes. We discovered that BDP-9066, a specific MRCK inhibitor (MRCKi), may be an effective drug against TNBC. After confirming the efficacy and specificity of BDP-9066 against TNBC in vitro and in vivo, we further analyzed the underlying mechanism of specific activity of BDP-9066 against TNBC. Comparing the transcriptome of BDP-9066-sensitive and -resistant cells, the activation of the focal adhesion and YAP/TAZ pathway were found to play an important role in the sensitive cells. Furthermore, YAP/TAZ is indeed repressed by BDP-9066 in the sensitive cells, and active form of YAP suppresses the effects of BDP-9066. YAP/TAZ expression and activity are high in TNBC, especially the Claudin-low subtype, consistent with the expression of focal adhesion-related genes. Interestingly, NF-κB functions downstream of YAP/TAZ in TNBC cells and is suppressed by BDP-9066. Furthermore, the PI3 kinase pathway adversely affected the effects of BDP-9066 and that alpelisib, a PI3 kinase inhibitor, synergistically increased the effects of BDP-9066, in PIK3CA mutant TNBC cells. Taken together, we have shown for the first time that MRCKi can be new drugs against TNBC, particularly the Claudin-low subtype.
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Affiliation(s)
- Hirohito Yamaguchi
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung City 406040, Taiwan R.O.C
- Center for Molecular Medicine, China Medical University Hospital, Taichung City 40402, Taiwan R.O.C
- Research Center for Cancer Biology, China Medical University, Taichung City 40402, Taiwan R.O.C
| | - Ling-Chu Chang
- Center for Molecular Medicine, China Medical University Hospital, Taichung City 40402, Taiwan R.O.C
- Research Center for Cancer Biology, China Medical University, Taichung City 40402, Taiwan R.O.C
| | - Olin Shih-Shin Chang
- Department of Molecular and Cellular Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Bristol-Myers Squibb, Redwood City, CA 94063, USA
| | - Yu-Fu Chen
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung City 406040, Taiwan R.O.C
| | - Yu-Chun Hsiao
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung City 406040, Taiwan R.O.C
- Center for Molecular Medicine, China Medical University Hospital, Taichung City 40402, Taiwan R.O.C
- Research Center for Cancer Biology, China Medical University, Taichung City 40402, Taiwan R.O.C
| | - Chen-Shiou Wu
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung City 406040, Taiwan R.O.C
- Center for Molecular Medicine, China Medical University Hospital, Taichung City 40402, Taiwan R.O.C
- Research Center for Cancer Biology, China Medical University, Taichung City 40402, Taiwan R.O.C
| | - Mien-Chie Hung
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung City 406040, Taiwan R.O.C
- Center for Molecular Medicine, China Medical University Hospital, Taichung City 40402, Taiwan R.O.C
- Research Center for Cancer Biology, China Medical University, Taichung City 40402, Taiwan R.O.C
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21
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Chen X, Chaimongkol N, Hengudomsub P. Effects of a Phone-Based Support Program for Women With Breast Cancer Undergoing Chemotherapy: A Pilot Study. SAGE Open Nurs 2024; 10:23779608241231176. [PMID: 38415216 PMCID: PMC10898293 DOI: 10.1177/23779608241231176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/21/2023] [Accepted: 01/20/2024] [Indexed: 02/29/2024] Open
Abstract
Introduction The increasing number of women with breast cancer undergoing chemotherapy may result in long-lasting, adverse physical side effects and reduced quality of life. Objective This study aimed to develop and assess the feasibility and preliminary effects of the Phone-Based Support Program for women with breast cancer undergoing chemotherapy. The primary outcome was self-care self-efficacy; secondary outcomes were symptom distress and quality of life. Methods This pilot study was conducted at a tertiary hospital in Jiangsu province, China, from February to March 2023. The Phone-Based Support Program was delivered to 20 participants through the smartphone application WeChat, consisting of learning, discussion, ask-the-expert, and personal stories components. Outcome measures were assessed at three time points: preintervention, postintervention, and follow-up. Results The Phone-Based Support Program was feasible and could improve self-care self-efficacy, decrease symptom distress, and promote quality of life. The program was well-accepted, and participants engaged actively in the online discussion and sought expert advice. Conclusions The Phone-Based Support Program showed feasibility and effectiveness in improving self-care self-efficacy, reducing symptom distress, and enhancing quality of life.
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Affiliation(s)
- Xi Chen
- Faculty of Nursing, Burapha University, Chon Buri, Thailand
- Yancheng NO.1 People's Hospital in Jiangsu, Jiangsu, China
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22
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Dunlop KLA, Keogh LA, Smith AL, Aranda S, Aitken J, Watts CG, Smit AK, Janda M, Mann GJ, Cust AE, Rankin NM. Acceptability and appropriateness of a risk-tailored organised melanoma screening program: Qualitative interviews with key informants. PLoS One 2023; 18:e0287591. [PMID: 38091281 PMCID: PMC10718433 DOI: 10.1371/journal.pone.0287591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 06/08/2023] [Indexed: 12/18/2023] Open
Abstract
INTRODUCTION In Australia, opportunistic screening (occurring as skin checks) for the early detection of melanoma is common, and overdiagnosis is a recognised concern. Risk-tailored cancer screening is an approach to cancer control that aims to provide personalised screening tailored to individual risk. This study aimed to explore the views of key informants in Australia on the acceptability and appropriateness of risk-tailored organised screening for melanoma, and to identify barriers, facilitators and strategies to inform potential future implementation. Acceptability and appropriateness are crucial, as successful implementation will require a change of practice for clinicians and consumers. METHODS This was a qualitative study using semi-structured interviews. Key informants were purposively selected to ensure expertise in melanoma early detection and screening, prioritising senior or executive perspectives. Consumers were expert representatives. Data were analysed deductively using the Tailored Implementation for Chronic Diseases (TICD) checklist. RESULTS Thirty-six participants were interviewed (10 policy makers; 9 consumers; 10 health professionals; 7 researchers). Key informants perceived risk-tailored screening for melanoma to be acceptable and appropriate in principle. Barriers to implementation included lack of trial data, reluctance for low-risk groups to not screen, variable skill level in general practice, differing views on who to conduct screening tests, confusing public health messaging, and competing health costs. Key facilitators included the perceived opportunity to improve health equity and the potential cost-effectiveness of a risk-tailored screening approach. A range of implementation strategies were identified including strengthening the evidence for cost-effectiveness, engaging stakeholders, developing pathways for people at low risk, evaluating different risk assessment criteria and screening delivery models and targeted public messaging. CONCLUSION Key informants were supportive in principle of risk-tailored melanoma screening, highlighting important next steps. Considerations around risk assessment, policy and modelling the costs of current verses future approaches will help inform possible future implementation of risk-tailored population screening for melanoma.
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Affiliation(s)
- Kate L. A. Dunlop
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
| | - Louise A. Keogh
- Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Andrea L. Smith
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
| | - Sanchia Aranda
- School of Health Sciences, University of Melbourne, Melbourne, Australia
| | - Joanne Aitken
- Viertel Cancer Research Centre, Cancer Council Queensland, Brisbane, Queensland, Australia
| | - Caroline G. Watts
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Surveillance, Evaluation & Research Program, Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia
| | - Amelia K. Smit
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
| | - Monika Janda
- Centre for Health Services Research, The University of Queensland, St Lucia, Queensland, Australia
| | - Graham J. Mann
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- John Curtin School of Medical Research, Australian National University, Acton, Australian Capital Territory, Australia
- Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Westmead, Sydney, New South Wales, Australia
| | - Anne E. Cust
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
| | - Nicole M. Rankin
- Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
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Speiser D, Bick U. Primary Prevention and Early Detection of Hereditary Breast Cancer. Breast Care (Basel) 2023; 18:448-454. [PMID: 38125920 PMCID: PMC10730103 DOI: 10.1159/000533391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 08/01/2023] [Indexed: 12/23/2023] Open
Abstract
Background Primary prevention and early detection of hereditary breast cancer has been one of the main topics of breast cancer research in recent decades. The knowledge of risk factors for breast cancer has been increasing continuously just like the recommendations for risk management. Pathogenic germline variants (mutations, class 4/5) of risk genes are significant susceptibility factors in healthy individuals. At the same time, germline mutations serve as biomarkers for targeted therapy in breast cancer treatment. Therefore, management of healthy mutation carriers to enable primary prevention is in the focus as much as the consideration of pathogenic germline variants for therapeutic decisions. Since 1996, the German Consortium has provided quality-assured care for counselees and patients with familial burden of breast and ovarian cancer. Summary Currently, there are 23 university centers with over 100 cooperating DKG-certified breast and gynecological cancer centers. These centers provide standardized, evidence-based, and knowledge-generating care, which includes aspects of primary as well as secondary and tertiary prevention. An important aspect of quality assurance and development was the inclusion of the HBOC centers in the certification system of the German Cancer Society (GCS). Since 2020, the centers have been regularly audited and their quality standards continuously reviewed according to quality indicators adapted to the current state of research. The standard of care at GC-HBOC' centers involves the evaluation as well as evolution of various aspects of care like inclusion criteria, identification of new risk genes, management of variants of unknown significance (class 3), evaluation of risk-reducing options, intensified surveillance, and communication of risks. Among these, the possibility of intensified surveillance in the GC-HBOC for early detection of breast cancer is an important component of individual risk management for many counselees. As has been shown in recent years, in carriers of pathogenic variants in high-risk genes, this approach enables the detection of breast cancer at very early, more favorable stages although no reduction of mortality has been demonstrated yet. The key component of the intensified surveillance is annual contrast-enhanced breast MRI, supplemented by up to biannual breast ultrasound and mammography usually starting at age 40. Key Messages Apart from early detection, the central goal of care is the prevention of cancer. By utilizing individualized risk calculation, the optimal timeframe for risk-reducing surgery can be estimated, and counselees can be supported in reaching preference-sensitive decisions.
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Affiliation(s)
- Dorothee Speiser
- HBOC-Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Gynecology with Breast Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ulrich Bick
- HBOC-Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Shanazarov N, Zhapparov Y, Kumisbekova R, Turzhanova D, Zulkhash N. Association of Gene Polymorphisms with Breast Cancer Risk in the Kazakh Population. Asian Pac J Cancer Prev 2023; 24:4195-4207. [PMID: 38156855 PMCID: PMC10909110 DOI: 10.31557/apjcp.2023.24.12.4195] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 12/18/2023] [Indexed: 01/03/2024] Open
Abstract
OBJECTIVE The research aim is analyzing and identify reliable genetic markers of breast cancer risk in the Kazakh population. METHODS The databases were analyzed with the selection of polymorphisms associated with the development of breast cancer and further genotypic study of a group of women with a confirmed diagnosis of breast adenocarcinoma (group No. 1) and a group of relatively healthy women (group No. 2). RESULT The research presents the results of a study on the frequency of certain single-nucleotide polymorphisms in patients with breast cancer in the Republic of Kazakhstan. The frequency of single-nucleotide polymorphisms rs4646, rs1065852, rs4244285, rs67376798, rs6504950, rs2229774, rs1800056, rs16942, rs4987047 is statistically significant compared to the control group of patients. These polymorphisms in the Kazakh population have a direct association with an increased risk of breast cancer in women and may be used as cancer indicators during the genetic screening of patients with a complicated family history. Single-nucleotide polymorphisms such as rs55886062, rs3918290, rs12721655, rs4987117, rs2229774, rs11203289, rs137852576, rs11571833, rs80359062 and rs11571746 were found in more than 40. Zero percent of patients with breast cancer may be used as markers for detecting patients at increased risk of breast malignancy in the Kazakh population without a history of poor family history. CONCLUSION The usage of the data obtained in a set of state programs for early screening of patients will improve the rates of early breast tumor detection, form groups of patients with a high risk of disease development and improve the quality and expectancy of life.
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Affiliation(s)
- Nasrulla Shanazarov
- Department of Strategic Development, Science and Education, Medical Centre Hospital of President’s Affairs Administration of the Republic of Kazakhstan, Astana, Republic of Kazakhstan.
- Center for Photodynamic Therapy, Medical Centre Hospital of President’s Affairs Administration of the Republic of Kazakhstan, Astana, Republic of Kazakhstan.
| | - Yerbol Zhapparov
- Clinical and Diagnostic Department, “UMIT” International Oncological Tomotherapy Center, Astana, Republic of Kazakhstan.
| | - Raushan Kumisbekova
- Department of Chemotherapy, Multidisciplinary Medical Center of the Akimat of Astana, Astana, Republic of Kazakhstan.
| | - Dinara Turzhanova
- Department of Radiology named after Academician Zh.Kh. Khamzabaev, Astana Medical University, Astana, Republic of Kazakhstan.
| | - Nargiz Zulkhash
- Department of Public Health, Astana Medical University, Astana Medical University, Astana, Republic of Kazakhstan.
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Liu Y, Chu Y, Liu J, Ge X, Ding M, Li P, Liu F, Zhou X, Wang X. Incidence and mortality of second primary malignancies after lymphoma: a population-based analysis. Ann Med 2023; 55:2282652. [PMID: 38010751 PMCID: PMC10836242 DOI: 10.1080/07853890.2023.2282652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Second primary malignancies (SPMs) account for an increasing proportion of human malignancies. We estimated the incidence, risk factors and outcomes in lymphoma survivors with SPMs. METHODS Patients diagnosed with SPMs after primary lymphoma from 2010 to 2021 were included in this study. The incidence, mortality and clinical characteristics of SPMs in our center and Surveillance, Epidemiology, and End Results database were delineated and analyzed. Standardized incidence ratio quantified second cancer risk. RESULTS A total of 2912 patients of lymphoma were included, 63 cases of SPM met the inclusion criteria, with the prevalence of SPMs after lymphoma was 2.16%. The male-to-female ratio of 2.32:1. The majority of these patients were older (≥60 years old, 61.90%) and previously treated with chemotherapy (68.25%). The common types among SPMs were digestive system tumors (42.86%), respiratory system tumors (20.63%) and urinary system tumors (12.70%). Additionally, cancer risks were significantly elevated after specific lymphoma though calculating the expected incidence. In terms of mortality, the diagnosis of SPMs was significantly associated with an increased risk of death over time. Moreover, although the outcome was favorable in some SPM subtypes (thyroid and breast cancer), other SPMs such as stomach and lung tumors had a dismal prognosis. CONCLUSION With the improvement of medical standards, the survival of lymphoma patients has been prolonged. However, the incidence of SPM is increasing, particularly among men and older lymphoma survivors. Therefore, more attention should be invested in the SPM to further improve the prognosis of these patients.
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Affiliation(s)
- Yingyue Liu
- Department of Hematology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yurou Chu
- Department of Hematology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Jiarui Liu
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Xueling Ge
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Mei Ding
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Peipei Li
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Fang Liu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Xiangxiang Zhou
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Branch of National Clinical Research Center for Hematologic Diseases, Jinan, Shandong, China
- National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xin Wang
- Department of Hematology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Branch of National Clinical Research Center for Hematologic Diseases, Jinan, Shandong, China
- National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, Suzhou, China
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Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel) 2023; 15:5380. [PMID: 38001640 PMCID: PMC10670420 DOI: 10.3390/cancers15225380] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/26/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.
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Affiliation(s)
- Cynthia Mbuya-Bienge
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London WC1E 6BT, UK;
| | - Cornelia D. Kazemali
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Jacques Simard
- Endocrinology and Nephology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1V 4G2, Canada;
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Hermann Nabi
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
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Amato O, Guarneri V, Girardi F. Epidemiology trends and progress in breast cancer survival: earlier diagnosis, new therapeutics. Curr Opin Oncol 2023; 35:612-619. [PMID: 37681462 PMCID: PMC10566595 DOI: 10.1097/cco.0000000000000991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
PURPOSE OF REVIEW In this review we will critically appraise the latest evidence on breast cancer (BC) survival trends and discuss how these may reflect breakthroughs in early diagnosis and treatment approaches. We will address the wide global inequalities in BC survival and review the ongoing initiatives aimed at improving cancer control worldwide. RECENT FINDINGS BC outcomes have improved in high-income countries during the last decades, following the implementation of strategies for early detection and optimal multimodality treatment. Novel therapeutics, such as anti-HER2 targeted treatments, have also contributed to the progress in BC survival. However, BC mortality is still high in low-income countries, due to the lack of optimal healthcare infrastructures. In the context of marked inequities in BC management across world regions, international collaborations such as the Global Breast Cancer Initiative and the Global Initiative for Cancer Registry Development work to foster capacity-building in developing countries, tackle the burden of BC and deliver the Sustainable Development Goals by 2030. SUMMARY Collection of robust, high-quality data from population-based cancer registries is crucial to drive and refine public health interventions. Population-based data are also the litmus paper to evaluate the real-world impact of clinical advances and monitor progress.
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Affiliation(s)
- Ottavia Amato
- Division of Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
- Department of Surgery, Oncology and Gastroenterology (DISCOG), University of Padova, Padova, Italy
| | - Valentina Guarneri
- Division of Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
- Department of Surgery, Oncology and Gastroenterology (DISCOG), University of Padova, Padova, Italy
| | - Fabio Girardi
- Division of Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
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Anandarajah A, Chen Y, Stoll C, Hardi A, Jiang S, Colditz GA. Repeated measures of mammographic density and texture to evaluate prediction and risk of breast cancer: a systematic review of the methods used in the literature. Cancer Causes Control 2023; 34:939-948. [PMID: 37340148 PMCID: PMC10533570 DOI: 10.1007/s10552-023-01739-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 06/14/2023] [Indexed: 06/22/2023]
Abstract
PURPOSE It may be important for women to have mammograms at different points in time to track changes in breast density, as fluctuations in breast density can affect breast cancer risk. This systematic review aimed to assess methods used to relate repeated mammographic images to breast cancer risk. METHODS The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021. Eligibility criteria included published articles in English describing the relationship of change in mammographic features with risk of breast cancer. Risk of bias was assessed using the Quality in Prognostic Studies tool. RESULTS Twenty articles were included. The Breast Imaging Reporting and Data System and Cumulus were most commonly used for classifying mammographic density and automated assessment was used on more recent digital mammograms. Time between mammograms varied from 1 year to a median of 4.1, and only nine of the studies used more than two mammograms. Several studies showed that adding change of density or mammographic features improved model performance. Variation in risk of bias of studies was highest in prognostic factor measurement and study confounding. CONCLUSION This review provided an updated overview and revealed research gaps in assessment of the use of texture features, risk prediction, and AUC. We provide recommendations for future studies using repeated measure methods for mammogram images to improve risk classification and risk prediction for women to tailor screening and prevention strategies to level of risk.
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Affiliation(s)
- Akila Anandarajah
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Yongzhen Chen
- Saint Louis University School of Medicine, Saint Louis, MO, USA
| | - Carolyn Stoll
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Angela Hardi
- Bernard Becker Medical Library, Washington University School of Medicine, MSC 8132-12-01, 660 S Euclid Ave, Saint Louis, MO, 63110, USA
| | - Shu Jiang
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Graham A Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA.
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29
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Yala A, Hughes KS. Rethinking Risk Modeling with Machine Learning. Ann Surg Oncol 2023; 30:6950-6952. [PMID: 37574515 DOI: 10.1245/s10434-023-14144-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 07/31/2023] [Indexed: 08/15/2023]
Affiliation(s)
- Adam Yala
- UC Berkeley, Berkeley, USA.
- UCSF, San Francisco, USA.
| | - Kevin S Hughes
- Surgical Oncology, Medical University of South Carolina, Charleston, USA
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Heine J, Fowler EEE, Weinfurtner RJ, Hume E, Tworoger SS. Breast density analysis of digital breast tomosynthesis. Sci Rep 2023; 13:18760. [PMID: 37907569 PMCID: PMC10618274 DOI: 10.1038/s41598-023-45402-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 10/19/2023] [Indexed: 11/02/2023] Open
Abstract
Mammography shifted to digital breast tomosynthesis (DBT) in the US. An automated percentage of breast density (PD) technique designed for two-dimensional (2D) applications was evaluated with DBT using several breast cancer risk prediction measures: normalized-volumetric; dense volume; applied to the volume slices and averaged (slice-mean); and applied to synthetic 2D images. Volumetric measures were derived theoretically. PD was modeled as a function of compressed breast thickness (CBT). The mean and standard deviation of the pixel values were investigated. A matched case-control (CC) study (n = 426 pairs) was evaluated. Odd ratios (ORs) were estimated with 95% confidence intervals. ORs were significant for PD: identical for volumetric and slice-mean measures [OR = 1.43 (1.18, 1.72)] and [OR = 1.44 (1.18, 1.75)] for synthetic images. A 2nd degree polynomial (concave-down) was used to model PD as a function of CBT: location of the maximum PD value was similar across CCs, occurring at 0.41 × CBT, and PD was significant [OR = 1.47 (1.21, 1.78)]. The means from the volume and synthetic images were also significant [ORs ~ 1.31 (1.09, 1.57)]. An alternative standardized 2D synthetic image was constructed, where each pixel value represents the percentage of breast density above its location. Several measures were significant and an alternative method for constructing a standardized 2D synthetic image was produced.
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Affiliation(s)
- John Heine
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA.
| | - Erin E E Fowler
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
| | - R Jared Weinfurtner
- Diagnostic Imaging and Interventional Radiology, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
| | - Emma Hume
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
| | - Shelley S Tworoger
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
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Chen C, Qin N, Wang M, Dong Q, Tithi SS, Hui Y, Chen W, Wu G, Kennetz D, Edmonson MN, Rusch MC, Thrasher A, Easton J, Mulder HL, Song N, Plonski NM, Shelton K, Im C, Ehrhardt MJ, Nichols KE, Leisenring WM, Stratton KL, Howell R, Yasui Y, Bhatia S, Armstrong GT, Ness KK, Hudson MM, Zhang J, Wang H, Srivastava DK, Robison LL, Wang Z. Cancer germline predisposing variants and late mortality from subsequent malignant neoplasms among long-term childhood cancer survivors: a report from the St Jude Lifetime Cohort and the Childhood Cancer Survivor Study. Lancet Oncol 2023; 24:1147-1156. [PMID: 37797633 PMCID: PMC10712938 DOI: 10.1016/s1470-2045(23)00403-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Carriers of cancer predisposing variants are at an increased risk of developing subsequent malignant neoplasms among those who have survived childhood cancer. We aimed to investigate whether cancer predisposing variants contribute to the risk of subsequent malignant neoplasm-related late mortality (5 years or more after diagnosis). METHODS In this analysis, data were included from two retrospective cohort studies, St Jude Lifetime Cohort (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), with prospective follow-up of patients who were alive for at least 5 years after diagnosis with childhood cancer (ie, long-term childhood cancer survivors) with corresponding germline whole genome or whole exome sequencing data. Cancer predisposing variants affecting 60 genes associated with well-established autosomal-dominant cancer-predisposition syndromes were characterised. Subsequent malignant neoplasms were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 with modifications. Cause-specific late mortality was based on linkage with the US National Death Index and systematic cohort follow up. Fine-Gray subdistribution hazard models were used to estimate subsequent malignant neoplasm-related late mortality starting from the first biospecimen collection, treating non-subsequent malignant neoplasm-related deaths as a competing risk, adjusting for genetic ancestry, sex, age at diagnosis, and cancer treatment exposures. SJLIFE (NCT00760656) and CCSS (NCT01120353) are registered with ClinicalTrials.gov. FINDINGS 12 469 (6172 male and 6297 female) participants were included, 4402 from the SJLIFE cohort (median follow-up time since collection of the first biospecimen 7·4 years [IQR 3·1-9·4]) and 8067 from the CCSS cohort (median follow-up time since collection of the first biospecimen 12·6 years [2·2-16·6]). 641 (5·1%) of 12 469 participants carried cancer predisposing variants (294 [6·7%] in the SJLIFE cohort and 347 [4·3%] in the CCSS cohort), which were significantly associated with an increased severity of subsequent malignant neoplasms (CTCAE grade ≥4 vs grade <4: odds ratio 2·15, 95% CI 1·18-4·19, p=0·0085). 263 (2·1%) subsequent malignant neoplasm-related deaths (44 [1·0%] in the SJLIFE cohort; and 219 [2·7%] in the CCSS cohort) and 426 (3·4%) other-cause deaths (103 [2·3%] in SJLIFE; and 323 [4·0%] in CCSS) occurred. Cumulative subsequent malignant neoplasm-related mortality at 10 years after the first biospecimen collection in carriers of cancer predisposing variants was 3·7% (95% CI 1·2-8·5) in SJLIFE and 6·9% (4·1-10·7) in CCSS versus 1·5% (1·0-2·1) in SJLIFE and 2·1% (1·7-2·5) in CCSS in non-carriers. Carrying a cancer predisposing variant was associated with an increased risk of subsequent malignant neoplasm-related mortality (SJLIFE: subdistribution hazard ratio 3·40 [95% CI 1·37-8·43]; p=0·0082; CCSS: 3·58 [2·27-5·63]; p<0·0001). INTERPRETATION Identifying participants at increased risk of subsequent malignant neoplasms via genetic counselling and clinical genetic testing for cancer predisposing variants and implementing early personalised cancer surveillance and prevention strategies might reduce the substantial subsequent malignant neoplasm-related mortality burden. FUNDING American Lebanese Syrian Associated Charities and US National Institutes of Health.
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Affiliation(s)
- Cheng Chen
- State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Na Qin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Mingjuan Wang
- Department of Biostatistics, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Qian Dong
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Saima Sultana Tithi
- Department of Cell and Molecular Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Yawei Hui
- High-Performance Computing Facility, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Wenan Chen
- Center for Applied Bioinformatics, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Gang Wu
- Center for Applied Bioinformatics, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Dennis Kennetz
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Michael N Edmonson
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Michael C Rusch
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Andrew Thrasher
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - John Easton
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Heather L Mulder
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Nan Song
- College of Pharmacy, Chungbuk National University, Cheongju, South Korea
| | - Noel-Marie Plonski
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Kyla Shelton
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Cindy Im
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Matthew J Ehrhardt
- Department of Oncology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Kim E Nichols
- Department of Oncology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Wendy M Leisenring
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Kayla L Stratton
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Rebecca Howell
- Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Smita Bhatia
- Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Gregory T Armstrong
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Kirsten K Ness
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Melissa M Hudson
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA; Department of Oncology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Jinghui Zhang
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Hui Wang
- State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Deo Kumar Srivastava
- Department of Biostatistics, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Leslie L Robison
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Zhaoming Wang
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA; Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA.
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Brockhoven F, Raphael M, Currier J, Jäderholm C, Mody P, Shannon J, Starling B, Turner-Uaandja H, Pashayan N, Arteaga I. REPRESENT recommendations: improving inclusion and trust in cancer early detection research. Br J Cancer 2023; 129:1195-1208. [PMID: 37689805 PMCID: PMC10575902 DOI: 10.1038/s41416-023-02414-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 08/01/2023] [Accepted: 08/21/2023] [Indexed: 09/11/2023] Open
Abstract
Detecting cancer early is essential to improving cancer outcomes. Minoritized groups remain underrepresented in early detection cancer research, which means that findings and interventions are not generalisable across the population, thus exacerbating disparities in cancer outcomes. In light of these challenges, this paper sets out twelve recommendations to build relations of trust and include minoritized groups in ED cancer research. The Recommendations were formulated by a range of stakeholders at the 2022 REPRESENT consensus-building workshop and are based on empirical data, including a systematic literature review and two ethnographic case studies in the US and the UK. The recommendations focus on: Long-term relationships that build trust; Sharing available resources; Inclusive and accessible communication; Harnessing community expertise; Unique risks and benefits; Compensation and support; Representative samples; Demographic data; Post-research support; Sharing results; Research training; Diversifying research teams. For each recommendation, the paper outlines the rationale, specifications for how different stakeholders may implement it, and advice for best practices. Instead of isolated recruitment, public involvement and engagement activities, the recommendations here aim to advance mutually beneficial and trusting relationships between researchers and research participants embedded in ED cancer research institutions.
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Grants
- EICEDAAP\100011 Cancer Research UK
- Cancer Research UK (CRUK)
- The International Alliance for Cancer Early Detection, an alliance between Cancer Research UK [EICEDAAP\100011], Canary Center at Stanford University, the University of Cambridge, OHSU Knight Cancer Institute, University College London and the University of Manchester.
- This work was supported by the International Alliance for Cancer Early Detection, an alliance between Cancer Research UK [EICEDAAP\100011], Canary Center at Stanford University, the University of Cambridge, OHSU Knight Cancer Institute, University College London and the University of Manchester.
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Affiliation(s)
| | - Maya Raphael
- Department of Social Anthropology, University of Cambridge, Cambridge, UK
| | - Jessica Currier
- Division of Oncological Sciences, Oregon Health & Science University, Portland, OR, USA
| | - Christina Jäderholm
- School of Public Health, Oregon Health & Science University-Portland State University, Portland, OR, USA
| | - Perveez Mody
- Department of Social Anthropology, University of Cambridge, Cambridge, UK
| | - Jackilen Shannon
- Division of Oncological Sciences, Oregon Health & Science University, Portland, OR, USA
| | - Bella Starling
- Vocal, Manchester University NHS Foundation Trust, Manchester, UK
| | | | - Nora Pashayan
- Department of Applied Health Research, University College London, London, UK
| | - Ignacia Arteaga
- Department of Social Anthropology, University of Cambridge, Cambridge, UK.
- Early Cancer Institute, University of Cambridge, Cambridge, UK.
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33
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Tsarouchi MI, Hoxhaj A, Mann RM. New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening. J Magn Reson Imaging 2023; 58:987-1010. [PMID: 37040474 DOI: 10.1002/jmri.28731] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/23/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Marialena I Tsarouchi
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Alma Hoxhaj
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ritse M Mann
- Department of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Herzog C, Jones A, Evans I, Zikan M, Cibula D, Harbeck N, Colombo N, Rådestad AF, Gemzell-Danielsson K, Pashayan N, Widschwendter M. DNA methylation at quantitative trait loci (mQTLs) varies with cell type and nonheritable factors and may improve breast cancer risk assessment. NPJ Precis Oncol 2023; 7:99. [PMID: 37758816 PMCID: PMC10533818 DOI: 10.1038/s41698-023-00452-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023] Open
Abstract
To individualise breast cancer (BC) prevention, markers to follow a person's changing environment and health extending beyond static genetic risk scores are required. Here, we analysed cervical and breast DNA methylation (n = 1848) and single nucleotide polymorphisms (n = 1442) and demonstrate that a linear combination of methylation levels at 104 BC-associated methylation quantitative trait loci (mQTL) CpGs, termed the WID™-qtBC index, can identify women with breast cancer in hormone-sensitive tissues (AUC = 0.71 [95% CI: 0.65-0.77] in cervical samples). Women in the highest combined risk group (high polygenic risk score and WID™-qtBC) had a 9.6-fold increased risk for BC [95% CI: 4.7-21] compared to the low-risk group and tended to present at more advanced stages. Importantly, the WID™-qtBC is influenced by non-genetic BC risk factors, including age and body mass index, and can be modified by a preventive pharmacological intervention, indicating an interaction between genome and environment recorded at the level of the epigenome. Our findings indicate that methylation levels at mQTLs in relevant surrogate tissues could enable integration of heritable and non-heritable factors for improved disease risk stratification.
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Affiliation(s)
- Chiara Herzog
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria
- Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria
| | - Allison Jones
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK
| | - Iona Evans
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK
| | - Michal Zikan
- Department of Gynecology and Obstetrics, Charles University in Prague, First Faculty of Medicine and Hospital Na Bulovce, Prague, Czech Republic
| | - David Cibula
- Gynaecologic Oncology Center, Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University in Prague, General University Hospital in Prague, Prague, Czech Republic
| | - Nadia Harbeck
- Breast Center, Department of Obstetrics and Gynecology and CCC Munich, LMU University Hospital, Munich, Germany
| | - Nicoletta Colombo
- Istituto Europeo di Oncologia, Milan, Italy
- University of Milano-Bicocca, Milan, Italy
| | | | | | - Nora Pashayan
- Department of Applied Health Research, University College London, London, UK
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria.
- Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria.
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK.
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.
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Liu M, Pan X, Gan Y, Gao M, Li X, Liu Z, Ma X, Geng M, Meng X, Ma N, Li J. Titanium Carbide MXene Quantum Dots-Modified Hydroxyapatite Hollow Microspheres as pH/Near-Infrared Dual-Response Drug Carriers. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2023; 39:13325-13334. [PMID: 37612781 DOI: 10.1021/acs.langmuir.3c01959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
Titanium carbide MXene quantum dots (MQDs) possess intrinsic regulatory properties and selective toxicity to cancer cells. Here, MDQs were selected for the modification of hydroxyapatite (HA) microspheres, and MXene quantum dots-modified hydroxyapatite (MQDs-HA) hollow microspheres with controllable shapes and sizes were prepared as bone drug carriers. The results show that the prepared MQDs-HA hollow microspheres had a large BET surface area (231.2 m2/g), good fluorescence, and low toxicity. In addition, MQDs-HA showed a mild storage-release behavior and good responsiveness of pH and near-infrared (NIR). Thus, the MQDs-HA hollow microspheres have broad application prospects in the field of drug delivery and photothermal therapy.
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Affiliation(s)
- Miaomiao Liu
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Xiaosen Pan
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Yuanjing Gan
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Meng Gao
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Xinran Li
- College of Biotechnology, Tianjin University of Science and Technology, Tianjin 300222, China
| | - Zhen Liu
- College of Biotechnology, Tianjin University of Science and Technology, Tianjin 300222, China
| | - Xiaojun Ma
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Mengru Geng
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Xiangqi Meng
- Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266400, China
| | - Ning Ma
- Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266400, China
| | - Jie Li
- College of Light Industry Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
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Lin J, Tu R, Lu Z. Prediabetes and the risk of breast cancer: a meta-analysis. Front Oncol 2023; 13:1238845. [PMID: 37790752 PMCID: PMC10544966 DOI: 10.3389/fonc.2023.1238845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/31/2023] [Indexed: 10/05/2023] Open
Abstract
Background Diabetes has been related to a higher risk of breast cancer (BC) in women. However, it remains unknown whether the incidence of BC is increased in women with prediabetes. A systematic review and meta-analysis was therefore performed to evaluate the relationship between prediabetes and risk of BC. Methods Observational studies with longitudinal follow-up relevant to the objective were found via searching Medline, Embase, Cochrane Library, and Web of Science. A fixed- or random-effects model was used to pool the results depending on heterogeneity. Results Eight prospective cohort studies and two nest case-control studies were included. A total of 1069079 community women were involved, and 72136 (6.7%) of them had prediabetes at baseline. During a mean duration follow-up of 9.6 years, 9960 (0.93%) patients were diagnosed as BC. Pooled results with a fixed-effects model showed that women with prediabetes were not associated with a higher incidence of BC as compared to those with normoglycemia (risk ratio: 0.99, 95% confidence interval: 0.93 to 1.05, p = 0.72) with mild heterogeneity (p for Cochrane Q test = 0.42, I2 = 3%). Subgroup analyses showed that study characteristics such as study design, menopausal status of the women, follow-up duration, diagnostic criteria for prediabetes, methods for validation of BC cases, and study quality scores did not significantly affect the results (p for subgroup analyses all > 0.05). Conclusion Women with prediabetes may not be associated with an increased risk of BC as compared to women with normoglycemia.
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Affiliation(s)
- Jing Lin
- Health Management Center, Ningbo Women and Children’s Hospital, Ningbo, China
| | - Rongzu Tu
- Department of Internal Medicine, Ningbo Women and Children’s Hospital, Ningbo, China
| | - Zhai’e Lu
- Department of Obstetrics, Ningbo Women and Children’s Hospital, Ningbo, China
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Louro J, Román M, Moshina N, Olstad CF, Larsen M, Sagstad S, Castells X, Hofvind S. Personalized Breast Cancer Screening: A Risk Prediction Model Based on Women Attending BreastScreen Norway. Cancers (Basel) 2023; 15:4517. [PMID: 37760486 PMCID: PMC10526465 DOI: 10.3390/cancers15184517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/06/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND We aimed to develop and validate a model predicting breast cancer risk for women targeted by breast cancer screening. METHOD This retrospective cohort study included 57,411 women screened at least once in BreastScreen Norway during the period from 2007 to 2019. The prediction model included information about age, mammographic density, family history of breast cancer, body mass index, age at menarche, alcohol consumption, exercise, pregnancy, hormone replacement therapy, and benign breast disease. We calculated a 4-year absolute breast cancer risk estimates for women and in risk groups by quartiles. The Bootstrap resampling method was used for internal validation of the model (E/O ratio). The area under the curve (AUC) was estimated with a 95% confidence interval (CI). RESULTS The 4-year predicted risk of breast cancer ranged from 0.22-7.33%, while 95% of the population had a risk of 0.55-2.31%. The thresholds for the quartiles of the risk groups, with 25% of the population in each group, were 0.82%, 1.10%, and 1.47%. Overall, the model slightly overestimated the risk with an E/O ratio of 1.10 (95% CI: 1.09-1.11) and the AUC was 62.6% (95% CI: 60.5-65.0%). CONCLUSIONS This 4-year risk prediction model showed differences in the risk of breast cancer, supporting personalized screening for breast cancer in women aged 50-69 years.
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Affiliation(s)
- Javier Louro
- Department of Epidemiology and Evaluation, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (J.L.); (M.R.); (X.C.)
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 48902 Barakaldo, Spain
| | - Marta Román
- Department of Epidemiology and Evaluation, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (J.L.); (M.R.); (X.C.)
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 48902 Barakaldo, Spain
| | - Nataliia Moshina
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Camilla F. Olstad
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Marthe Larsen
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Silje Sagstad
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Xavier Castells
- Department of Epidemiology and Evaluation, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (J.L.); (M.R.); (X.C.)
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 48902 Barakaldo, Spain
| | - Solveig Hofvind
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
- Department of Health and Care Sciences, Faculty of Health Sciences, UiT, The Arctic University of Norway, 9037 Tromsø, Norway
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Jarm K, Zadnik V, Birk M, Vrhovec M, Hertl K, Klanecek Z, Studen A, Sval C, Krajc M. Breast cancer risk assessment and risk distribution in 3,491 Slovenian women invited for screening at the age of 50; a population-based cross-sectional study. Radiol Oncol 2023; 57:337-347. [PMID: 37665745 PMCID: PMC10476908 DOI: 10.2478/raon-2023-0039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 07/06/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND The evidence shows that risk-based strategy could be implemented to avoid unnecessary harm in mammography screening for breast cancer (BC) using age-only criterium. Our study aimed at identifying the uptake of Slovenian women to the BC risk assessment invitation and assessing the number of screening mammographies in case of risk-based screening. PATIENTS AND METHODS A cross-sectional population-based study enrolled 11,898 women at the age of 50, invited to BC screening. The data on BC risk factors, including breast density from the first 3,491 study responders was collected and BC risk was assessed using the Tyrer-Cuzick algorithm (version 8) to classify women into risk groups (low, population, moderately increased, and high risk group). The number of screening mammographies according to risk stratification was simulated. RESULTS 57% (6,785) of women returned BC risk questionnaires. When stratifying 3,491 women into risk groups, 34.0% were assessed with low, 62.2% with population, 3.4% with moderately increased, and 0.4% with high 10-year BC risk. In the case of potential personalised screening, the number of screening mammographies would drop by 38.6% compared to the current screening policy. CONCLUSIONS The study uptake showed the feasibility of risk assessment when inviting women to regular BC screening. 3.8% of Slovenian women were recognised with higher than population 10-year BC risk. According to Slovenian BC guidelines they may be screened more often. Overall, personalised screening would decrease the number of screening mammographies in Slovenia. This information is to be considered when planning the pilot and assessing the feasibility of implementing population risk-based screening.
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Affiliation(s)
- Katja Jarm
- Sector for Cancer Screening and Clinical Genetics, Institute of Oncology Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Health Sciences, University of Primorska, Izola, Slovenia
| | - Vesna Zadnik
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Health Sciences, University of Primorska, Izola, Slovenia
- Sector for Oncology Epidemiology and Cancer Registry, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Mojca Birk
- Sector for Oncology Epidemiology and Cancer Registry, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Milos Vrhovec
- Sector for Cancer Screening and Clinical Genetics, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Kristijana Hertl
- Sector for Cancer Screening and Clinical Genetics, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Zan Klanecek
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - Andrej Studen
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - Cveto Sval
- Sector for Cancer Screening and Clinical Genetics, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - Mateja Krajc
- Sector for Cancer Screening and Clinical Genetics, Institute of Oncology Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Health Sciences, University of Primorska, Izola, Slovenia
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Bae MS. Mammography-based Deep Learning for Breast Cancer Risk Assessment for Supplemental MRI Screening. Radiology 2023; 308:e232226. [PMID: 37724962 DOI: 10.1148/radiol.232226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Affiliation(s)
- Min Sun Bae
- From the Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, 123 Jeokgeum-ro, Danwon-gu, Ansan, Gyeonggi-do 15355, Republic of Korea
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Clift AK, Collins GS, Lord S, Petrou S, Dodwell D, Brady M, Hippisley-Cox J. Predicting 10-year breast cancer mortality risk in the general female population in England: a model development and validation study. Lancet Digit Health 2023; 5:e571-e581. [PMID: 37625895 DOI: 10.1016/s2589-7500(23)00113-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 04/06/2023] [Accepted: 06/12/2023] [Indexed: 08/27/2023]
Abstract
BACKGROUND Identifying female individuals at highest risk of developing life-threatening breast cancers could inform novel stratified early detection and prevention strategies to reduce breast cancer mortality, rather than only considering cancer incidence. We aimed to develop a prognostic model that accurately predicts the 10-year risk of breast cancer mortality in female individuals without breast cancer at baseline. METHODS In this model development and validation study, we used an open cohort study from the QResearch primary care database, which was linked to secondary care and national cancer and mortality registers in England, UK. The data extracted were from female individuals aged 20-90 years without previous breast cancer or ductal carcinoma in situ who entered the cohort between Jan 1, 2000, and Dec 31, 2020. The primary outcome was breast cancer-related death, which was assessed in the full dataset. Cox proportional hazards, competing risks regression, XGBoost, and neural network modelling approaches were used to predict the risk of breast cancer death within 10 years using routinely collected health-care data. Death due to causes other than breast cancer was the competing risk. Internal-external validation was used to evaluate prognostic model performance (using Harrell's C, calibration slope, and calibration in the large), performance heterogeneity, and transportability. Internal-external validation involved dataset partitioning by time period and geographical region. Decision curve analysis was used to assess clinical utility. FINDINGS We identified data for 11 626 969 female individuals, with 70 095 574 person-years of follow-up. There were 142 712 (1·2%) diagnoses of breast cancer, 24 043 (0·2%) breast cancer-related deaths, and 696 106 (6·0%) deaths from other causes. Meta-analysis pooled estimates of Harrell's C were highest for the competing risks model (0·932, 95% CI 0·917-0·946). The competing risks model was well calibrated overall (slope 1·011, 95% CI 0·978-1·044), and across different ethnic groups. Decision curve analysis suggested favourable clinical utility across all age groups. The XGBoost and neural network models had variable performance across age and ethnic groups. INTERPRETATION A model that predicts the combined risk of developing and then dying from breast cancer at the population level could inform stratified screening or chemoprevention strategies. Further evaluation of the competing risks model should comprise effect and health economic assessment of model-informed strategies. FUNDING Cancer Research UK.
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Affiliation(s)
- Ash Kieran Clift
- Cancer Research UK Oxford Centre, University of Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK.
| | - Gary S Collins
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, UK
| | - Simon Lord
- Department of Oncology, University of Oxford, UK
| | - Stavros Petrou
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - David Dodwell
- Nuffield Department of Population Health, University of Oxford, UK
| | | | - Julia Hippisley-Cox
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
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Sijben J, Peters Y, Rainey L, Gashi M, Broeders MJ, Siersema PD. Professionals' views on the justification for esophageal adenocarcinoma screening: A systematic literature search and qualitative analysis. Prev Med Rep 2023; 34:102264. [PMID: 37273526 PMCID: PMC10236474 DOI: 10.1016/j.pmedr.2023.102264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/26/2023] [Accepted: 05/22/2023] [Indexed: 06/06/2023] Open
Abstract
Screening for early esophageal adenocarcinoma (EAC), including screening for its precursor Barrett's esophagus (BE), has the potential to reduce EAC-related mortality and morbidity. This literature review aimed to explore professionals' views on the justification for EAC screening. A systematic search of Ovid Medline, EMBASE, and PsycInfo, from January 1, 2000 to September 22, 2022, identified 5 original studies and 63 expert opinion articles reporting professionals' perspectives on EAC screening. Included articles were qualitatively analyzed using the framework method, which was deductively led by modernized screening principles. The analyses showed that many professionals are optimistic about technological advancements in BE detection and treatment. However, views on whether the societal burden of EAC merits screening were contradictory. In addition, knowledge of the long-term benefits and risks of EAC screening is still considered insufficient. There is no consensus on who to screen, how often to screen, which screening test to use, and how to manage non-dysplastic BE. Professionals further point out the need to develop technology that facilitates automated test sample processing and public education strategies that avoid causing disproportionately high cancer worry and social stigma. In conclusion, modernized screening principles are currently insufficiently fulfilled to justify widespread screening for EAC. Results from future clinical screening trials and risk prediction modeling studies may shift professionals' thoughts regarding justification for EAC screening.
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Affiliation(s)
- Jasmijn Sijben
- Department of Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yonne Peters
- Department of Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Linda Rainey
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mejdan Gashi
- Department of Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mireille J.M. Broeders
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
- Dutch Expert Center for Screening, Nijmegen, The Netherlands
| | - Peter D. Siersema
- Department of Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Gastroenterology and Hepatology, Erasmus MC - University Medical Center, Rotterdam, The Netherlands
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Mertens E, Barrenechea-Pulache A, Sagastume D, Vasquez MS, Vandevijvere S, Peñalvo JL. Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe. BMC Cancer 2023; 23:687. [PMID: 37480028 PMCID: PMC10360320 DOI: 10.1186/s12885-023-11174-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/12/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND Breast cancer (BC) is a significant health concern among European women, with the highest prevalence rates among all cancers. Existing BC prediction models account for major risks such as hereditary, hormonal and reproductive factors, but research suggests that adherence to a healthy lifestyle can reduce the risk of developing BC to some extent. Understanding the influence and predictive role of lifestyle variables in current risk prediction models could help identify actionable, modifiable, targets among high-risk population groups. PURPOSE To systematically review population-based BC risk prediction models applicable to European populations and identify lifestyle predictors and their corresponding parameter values for a better understanding of their relative contribution to the prediction of incident BC. METHODS A systematic review was conducted in PubMed, Embase and Web of Science from January 2000 to August 2021. Risk prediction models were included if (i) developed and/or validated in adult cancer-free women in Europe, (ii) based on easily ascertained information, and (iii) reported models' final predictors. To investigate further the comparability of lifestyle predictors across models, estimates were standardised into risk ratios and visualised using forest plots. RESULTS From a total of 49 studies, 33 models were developed and 22 different existing models, mostly from Gail (22 studies) and Tyrer-Cuzick and co-workers (12 studies) were validated or modified for European populations. Family history of BC was the most frequently included predictor (31 models), while body mass index (BMI) and alcohol consumption (26 and 21 models, respectively) were the lifestyle predictors most often included, followed by smoking and physical activity (7 and 6 models respectively). Overall, for lifestyle predictors, their modest predictive contribution was greater for riskier lifestyle levels, though highly variable model estimates across different models. CONCLUSIONS Given the increasing BC incidence rates in Europe, risk models utilising readily available risk factors could greatly aid in widening the population coverage of screening efforts, while the addition of lifestyle factors could help improving model performance and serve as intervention targets of prevention programmes.
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Affiliation(s)
- Elly Mertens
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Nationalestraat 155, 2000, Antwerp, Belgium.
| | - Antonio Barrenechea-Pulache
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Nationalestraat 155, 2000, Antwerp, Belgium
| | - Diana Sagastume
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Nationalestraat 155, 2000, Antwerp, Belgium
| | - Maria Salve Vasquez
- Health Information, Scientific Institute of Public Health (Sciensano), Brussels, Belgium
| | - Stefanie Vandevijvere
- Health Information, Scientific Institute of Public Health (Sciensano), Brussels, Belgium
| | - José L Peñalvo
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Nationalestraat 155, 2000, Antwerp, Belgium
- Global Health Institute, University of Antwerp, Antwerp, Belgium
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Aguilera-Eguía RA, Gutiérrez-Arias R, Zaror C, Seron P. Effectiveness of physical exercise programmes in reducing complications associated with secondary lymphoedema to breast cancer: a protocol for an overview of systematic reviews. BMJ Open 2023; 13:e071630. [PMID: 37429694 DOI: 10.1136/bmjopen-2023-071630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/12/2023] Open
Abstract
INTRODUCTION Breast cancer-related lymphoedema (BCRL) is one of the most underestimated and debilitating complications associated with the treatment that women with breast cancer receive. Several systematic reviews (SRs) of different physical exercise programmes have been published, presenting disperse and contradictory clinical results. Therefore, there is a need for access to the best available and summarised evidence to capture and evaluate all the physical exercise programmes that focus on reducing BCRL. OBJECTIVE To evaluate the effectiveness of different physical exercise programmes in reducing the volume of lymphoedema, pain intensity and improving quality of life. METHOD AND ANALYSIS The protocol of this overview is reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols, and its methodology is based on Cochrane Handbook for Systematic Reviews of Interventions. Only those SRs involving physical exercise by patients with BCRL will be included, whether on its own or combined with other exercises or other physical therapy interventions.The outcomes of interest to be considered will be lymphoedema volume, quality of life, pain intensity, grip strength, range of motion, upper limb function and any adverse event. The MEDLINE/PubMed, Lilacs, Cochrane Library, PEDro and Embase databases will be searched for reports published from database inception to April 2023.Two researchers will perform study selection, data extraction and risk of bias assessment independently. Any discrepancy will be resolved by consensus, or ultimately, by a third-party reviewer. We will use Grading of Recommendations Assessment, Development and Evaluation System to assess the overall quality of the body of evidence. ETHICS AND DISSEMINATION The results of this overview will be published in peer-reviewed scholarly journals and the scientific dissemination will take place in national or international conferences. This study does not require approval from an ethics committee, as it does not directly collect information from patients. PROSPERO REGISTRATION NUMBER CRD42022334433.
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Affiliation(s)
- Raúl Alberto Aguilera-Eguía
- Departamento de Salud Pública, Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepcion, Chile
- Department of Paediatrics, Obstetrics and Gynaecology and Preventive Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ruvistay Gutiérrez-Arias
- Departamento de Apoyo en Rehabilitación Cardiopulmonar Integral, Instituto Nacional del Tórax, Santiago, Chile
- Exercise and Rehabilitation Sciences Institute, Faculty of Rehabilitation Sciences, Universidad Andres Bello, Santiago 7591538, Santiago, Chile
| | - Carlos Zaror
- Pediatric Dentist and Orthodontic, Universidad de La Frontera, Temuco, Chile
| | - Pamela Seron
- CIGES, Universidad de La Frontera, Temuco, Chile
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Dennison RA, Usher-Smith JA, John SD. The ethics of risk-stratified cancer screening. Eur J Cancer 2023; 187:1-6. [PMID: 37094523 DOI: 10.1016/j.ejca.2023.03.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/08/2023] [Accepted: 03/21/2023] [Indexed: 03/29/2023]
Abstract
Cancer screening programmes aim to save lives and reduce cancer burden through prevention or early detection of specific cancers. Risk stratification, where one or more elements of a screening programme are systematically tailored based on multiple individual-level risk factors, could improve the balance of screening benefits and harms and programme efficiency. In this article, we explore the resulting ethical issues and how they impact risk-stratified screening policymaking using Beauchamp and Childress's principles of medical ethics. First, in line with universal screening programme principles, we acknowledge that risk-stratified screening should be introduced only when the expected total benefits outweigh the harms, and where it has a favourable overall impact compared to alternative options. We then discuss how these are difficult to both value and quantify, and that risk models typically perform differently in sub-populations. Second, we consider whether screening is an individual right and whether it is fair to offer more or less intensive screening to some and not others based on personal characteristics. Third, we discuss the need to maintain respect for autonomy, including ensuring informed consent and considering the screening implications for those who cannot or choose not to participate in the risk assessment. In summary, from an ethical perspective, focusing on population-level effectiveness alone is insufficient when planning risk-stratified screening programmes and the range of ethical principles must be considered.
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Affiliation(s)
- Rebecca A Dennison
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.
| | - Juliet A Usher-Smith
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - Stephen D John
- Department of History and Philosophy of Science, University of Cambridge, Cambridge CB2 3RH, UK
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Lapointe J, Côté JM, Mbuya-Bienge C, Dorval M, Pashayan N, Chiquette J, Eloy L, Turgeon A, Lambert-Côté L, Brooks JD, Walker MJ, Blackmore KM, Joly Y, Knoppers BM, Chiarelli AM, Simard J, Nabi H. Canadian Healthcare Professionals' Views and Attitudes toward Risk-Stratified Breast Cancer Screening. J Pers Med 2023; 13:1027. [PMID: 37511640 PMCID: PMC10381377 DOI: 10.3390/jpm13071027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/02/2023] [Accepted: 06/19/2023] [Indexed: 07/30/2023] Open
Abstract
Given the controversy over the effectiveness of age-based breast cancer (BC) screening, offering risk-stratified screening to women may be a way to improve patient outcomes with detection of earlier-stage disease. While this approach seems promising, its integration requires the buy-in of many stakeholders. In this cross-sectional study, we surveyed Canadian healthcare professionals about their views and attitudes toward a risk-stratified BC screening approach. An anonymous online questionnaire was disseminated through Canadian healthcare professional associations between November 2020 and May 2021. Information collected included attitudes toward BC screening recommendations based on individual risk, comfort and perceived readiness related to the possible implementation of this approach. Close to 90% of the 593 respondents agreed with increased frequency and earlier initiation of BC screening for women at high risk. However, only 9% agreed with the idea of not offering BC screening to women at very low risk. Respondents indicated that primary care physicians and nurse practitioners should play a leading role in the risk-stratified BC screening approach. This survey identifies health services and policy enhancements that would be needed to support future implementation of a risk-stratified BC screening approach in healthcare systems in Canada and other countries.
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Affiliation(s)
- Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
| | - Jean-Martin Côté
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
| | - Cynthia Mbuya-Bienge
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, 1050, Av de la Médecine, Québec City, QC G1V 0A6, Canada
| | - Michel Dorval
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
- Faculty of Pharmacy, Université Laval, 1050, Av de la Médecine, Québec City, QC G1V 0A6, Canada
- CISSS de Chaudière-Appalaches Research Center, 143 Rue Wolfe, Lévis, QC G6V 3Z1, Canada
| | - Nora Pashayan
- Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, Gower Street, London WC1E 6BT, UK
| | - Jocelyne Chiquette
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
- CHU de Québec-Université Laval, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
| | - Laurence Eloy
- Programme Québécois de Cancérologie, Ministère de la Santé et des Services Sociaux, 1075, Chemin Sainte-Foy, Québec City, QC G1S 2M1, Canada
| | - Annie Turgeon
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
| | - Laurence Lambert-Côté
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
| | - Jennifer D Brooks
- Dalla Lana School of Public Health, University of Toronto, 155, College Street, Toronto, ON M5T 3M7, Canada
| | - Meghan J Walker
- Dalla Lana School of Public Health, University of Toronto, 155, College Street, Toronto, ON M5T 3M7, Canada
- Cancer Care Ontario, Ontario Health, 525, University Avenue, Toronto, ON M5G 2L3, Canada
| | | | - Yann Joly
- Centre of Genomics and Policy, McGill University, 740, Ave Penfield, Montreal, QC H3A 0G1, Canada
- Human Genetics Department and Bioethics Unit, Faculty of Medicine, McGill University, 3647, Peel Street, Montreal, QC G1V 0A6, Canada
| | - Bartha Maria Knoppers
- Centre of Genomics and Policy, McGill University, 740, Ave Penfield, Montreal, QC H3A 0G1, Canada
| | - Anna Maria Chiarelli
- Dalla Lana School of Public Health, University of Toronto, 155, College Street, Toronto, ON M5T 3M7, Canada
- Cancer Care Ontario, Ontario Health, 525, University Avenue, Toronto, ON M5G 2L3, Canada
| | - Jacques Simard
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, 1050, Avenue de la Médecine, Québec City, QC G1V 0A6, Canada
| | - Hermann Nabi
- Oncology Division, CHU de Québec-Université Laval Research Center, 1050, Chemin Sainte-Foy, Québec City, QC G1S 4L8, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, 1050, Av de la Médecine, Québec City, QC G1V 0A6, Canada
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Chung FFL, Maldonado SG, Nemc A, Bouaoun L, Cahais V, Cuenin C, Salle A, Johnson T, Ergüner B, Laplana M, Datlinger P, Jeschke J, Weiderpass E, Kristensen V, Delaloge S, Fuks F, Risch A, Ghantous A, Plass C, Bock C, Kaaks R, Herceg Z. Buffy coat signatures of breast cancer risk in a prospective cohort study. Clin Epigenetics 2023; 15:102. [PMID: 37309009 PMCID: PMC10262593 DOI: 10.1186/s13148-023-01509-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/20/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Epigenetic alterations are a near-universal feature of human malignancy and have been detected in malignant cells as well as in easily accessible specimens such as blood and urine. These findings offer promising applications in cancer detection, subtyping, and treatment monitoring. However, much of the current evidence is based on findings in retrospective studies and may reflect epigenetic patterns that have already been influenced by the onset of the disease. METHODS Studying breast cancer, we established genome-scale DNA methylation profiles of prospectively collected buffy coat samples (n = 702) from a case-control study nested within the EPIC-Heidelberg cohort using reduced representation bisulphite sequencing (RRBS). RESULTS We observed cancer-specific DNA methylation events in buffy coat samples. Increased DNA methylation in genomic regions associated with SURF6 and REXO1/CTB31O20.3 was linked to the length of time to diagnosis in the prospectively collected buffy coat DNA from individuals who subsequently developed breast cancer. Using machine learning methods, we piloted a DNA methylation-based classifier that predicted case-control status in a held-out validation set with 76.5% accuracy, in some cases up to 15 years before clinical diagnosis of the disease. CONCLUSIONS Taken together, our findings suggest a model of gradual accumulation of cancer-associated DNA methylation patterns in peripheral blood, which may be detected long before clinical manifestation of cancer. Such changes may provide useful markers for risk stratification and, ultimately, personalized cancer prevention.
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Affiliation(s)
- Felicia Fei-Lei Chung
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France.
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, 5, Jalan Universiti, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia.
| | | | - Amelie Nemc
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Liacine Bouaoun
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France
| | - Vincent Cahais
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France
| | - Cyrille Cuenin
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France
| | - Aurelie Salle
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France
| | - Theron Johnson
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bekir Ergüner
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Marina Laplana
- Division of Cancer Epigenomics, German Cancer Research Center, Heidelberg, Germany
- Department of Basic Medical Sciences, University of Lleida, IRBLleida, 25198, Lleida, Spain
| | - Paul Datlinger
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Jana Jeschke
- Laboratory of Cancer Epigenetics, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Elisabete Weiderpass
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France
| | - Vessela Kristensen
- Faculty of Medicine, Institute for Clinical Epidemiology and Molecular Biology, University of Oslo, Oslo, Norway
| | - Suzette Delaloge
- Department of Cancer Medicine, Institut Gustave Roussy, Villejuif, France
| | - François Fuks
- Laboratory of Cancer Epigenetics, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Angela Risch
- Division of Cancer Epigenomics, German Cancer Research Center, Heidelberg, Germany
- Department of Biosciences and Medical Biology, Allergy-Cancer-BioNano Research Centre, University of Salzburg, 5020, Salzburg, Austria
- Cancer Cluster Salzburg, Salzburg, Austria
| | - Akram Ghantous
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France
| | - Christoph Plass
- Division of Cancer Epigenomics, German Cancer Research Center, Heidelberg, Germany
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
- Medical University of Vienna, Institute of Artificial Intelligence, Center for Medical Data Science, Vienna, Austria
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zdenko Herceg
- International Agency for Research On Cancer (IARC), 25 avenue Tony Garnier, CS 90627, 69366, Lyon, France.
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47
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Ruiz-Manriquez LM, Villarreal-Garza C, Benavides-Aguilar JA, Torres-Copado A, Isidoro-Sánchez J, Estrada-Meza C, Arvizu-Espinosa MG, Paul S, Cuevas-Diaz Duran R. Exploring the Potential Role of Circulating microRNAs as Biomarkers for Predicting Clinical Response to Neoadjuvant Therapy in Breast Cancer. Int J Mol Sci 2023; 24:9984. [PMID: 37373139 PMCID: PMC10297903 DOI: 10.3390/ijms24129984] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/08/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
Breast cancer (BC) is a leading cause of cancer-related deaths among women worldwide. Neoadjuvant therapy (NAT) is increasingly being used to reduce tumor burden prior to surgical resection. However, current techniques for assessing tumor response have significant limitations. Additionally, drug resistance is commonly observed, raising a need to identify biomarkers that can predict treatment sensitivity and survival outcomes. Circulating microRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and have been shown to play a significant role in cancer progression as tumor inducers or suppressors. The expression of circulating miRNAs has been found to be significantly altered in breast cancer patients. Moreover, recent studies have suggested that circulating miRNAs can serve as non-invasive biomarkers for predicting response to NAT. Therefore, this review provides a brief overview of recent studies that have demonstrated the potential of circulating miRNAs as biomarkers for predicting the clinical response to NAT in BC patients. The findings of this review will strengthen future research on developing miRNA-based biomarkers and their translation into medical practice, which could significantly improve the clinical management of BC patients undergoing NAT.
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Affiliation(s)
- Luis M. Ruiz-Manriquez
- School of Medicine and Health Sciences, Tecnologico de Monterrey, Monterrey 64700, Mexico;
- School of Engineering and Sciences, Tecnologico de Monterrey, Queretaro 76130, Mexico
| | - Cynthia Villarreal-Garza
- Breast Cancer Center, Hospital Zambrano Hellion TecSalud, Tecnologico de Monterrey, Monterrey 64700, Mexico;
| | | | - Andrea Torres-Copado
- School of Engineering and Sciences, Tecnologico de Monterrey, Queretaro 76130, Mexico
| | - José Isidoro-Sánchez
- School of Engineering and Sciences, Tecnologico de Monterrey, Queretaro 76130, Mexico
| | - Carolina Estrada-Meza
- School of Engineering and Sciences, Tecnologico de Monterrey, Queretaro 76130, Mexico
| | | | - Sujay Paul
- School of Engineering and Sciences, Tecnologico de Monterrey, Queretaro 76130, Mexico
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48
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Arasu VA, Habel LA, Achacoso NS, Buist DSM, Cord JB, Esserman LJ, Hylton NM, Glymour MM, Kornak J, Kushi LH, Lewis DA, Liu VX, Lydon CM, Miglioretti DL, Navarro DA, Pu A, Shen L, Sieh W, Yoon HC, Lee C. Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study. Radiology 2023; 307:e222733. [PMID: 37278627 PMCID: PMC10315521 DOI: 10.1148/radiol.222733] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 04/05/2023] [Accepted: 04/18/2023] [Indexed: 06/07/2023]
Abstract
Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Vignesh A. Arasu
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Laurel A. Habel
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Ninah S. Achacoso
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Diana S. M. Buist
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Jason B. Cord
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Laura J. Esserman
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Nola M. Hylton
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - M. Maria Glymour
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - John Kornak
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Lawrence H. Kushi
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Donald A. Lewis
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Vincent X. Liu
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Caitlin M. Lydon
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Diana L. Miglioretti
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Daniel A. Navarro
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Albert Pu
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Li Shen
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Weiva Sieh
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Hyo-Chun Yoon
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
| | - Catherine Lee
- From the Division of Research, Kaiser Permanente Northern California,
2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L.,
C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California,
Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington
Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology,
Southern California Permanente Medical Group, Orange County, Irvine, Calif
(J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical
Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G.,
J.K.), University of California–San Francisco, San Francisco, Calif;
Department of Medical Imaging Technology and Informatics, Southern California
Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics,
University of California–Davis, Davis, Calif (D.L.M.); The Technology
Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information
Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals,
Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health
and Nash Family Department of Neuroscience (L.S.) and Department of Population
Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.),
Icahn School of Medicine at Mount Sinai, New York, NY; and Department of
Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu,
Hawaii (H.C.Y.)
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49
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Zappe K, Kopic A, Scheichel A, Schier AK, Schmidt LE, Borutzki Y, Miedl H, Schreiber M, Mendrina T, Pirker C, Pfeiler G, Hacker S, Haslik W, Pils D, Bileck A, Gerner C, Meier-Menches S, Heffeter P, Cichna-Markl M. Aberrant DNA Methylation, Expression, and Occurrence of Transcript Variants of the ABC Transporter ABCA7 in Breast Cancer. Cells 2023; 12:1462. [PMID: 37296582 PMCID: PMC10252461 DOI: 10.3390/cells12111462] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/09/2023] [Accepted: 05/16/2023] [Indexed: 06/12/2023] Open
Abstract
The ABC transporter ABCA7 has been found to be aberrantly expressed in a variety of cancer types, including breast cancer. We searched for specific epigenetic and genetic alterations and alternative splicing variants of ABCA7 in breast cancer and investigated whether these alterations are associated with ABCA7 expression. By analyzing tumor tissues from breast cancer patients, we found CpGs at the exon 5-intron 5 boundary aberrantly methylated in a molecular subtype-specific manner. The detection of altered DNA methylation in tumor-adjacent tissues suggests epigenetic field cancerization. In breast cancer cell lines, DNA methylation levels of CpGs in promoter-exon 1, intron 1, and at the exon 5-intron 5 boundary were not correlated with ABCA7 mRNA levels. By qPCR involving intron-specific and intron-flanking primers, we identified intron-containing ABCA7 mRNA transcripts. The occurrence of intron-containing transcripts was neither molecular subtype-specific nor directly correlated with DNA methylation at the respective exon-intron boundaries. Treatment of breast cancer cell lines MCF-7, BT-474, SK-BR3, and MDA-MB-231 with doxorubicin or paclitaxel for 72 h resulted in altered ABCA7 intron levels. Shotgun proteomics revealed that an increase in intron-containing transcripts was associated with significant dysregulation of splicing factors linked to alternative splicing.
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Affiliation(s)
- Katja Zappe
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Antonio Kopic
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Alexandra Scheichel
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Ann-Katrin Schier
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Lukas Emanuel Schmidt
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Yasmin Borutzki
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
- Department of Inorganic Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
| | - Heidi Miedl
- Department of Obstetrics and Gynecology and Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
| | - Martin Schreiber
- Department of Obstetrics and Gynecology and Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
| | - Theresa Mendrina
- Department of Inorganic Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
- Center for Cancer Research and Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
| | - Christine Pirker
- Center for Cancer Research and Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
| | - Georg Pfeiler
- Division of Gynecology and Gynecological Oncology, Department of Obstetrics and Gynecology, Medical University of Vienna, 1090 Vienna, Austria
| | - Stefan Hacker
- Department of Plastic and Reconstructive Surgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Werner Haslik
- Department of Plastic and Reconstructive Surgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Dietmar Pils
- Division of Visceral Surgery, Department of General Surgery and Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
| | - Andrea Bileck
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
- Joint Metabolome Facility, University of Vienna and Medical University of Vienna, 1090 Vienna, Austria
| | - Christopher Gerner
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
- Joint Metabolome Facility, University of Vienna and Medical University of Vienna, 1090 Vienna, Austria
| | - Samuel Meier-Menches
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
- Department of Inorganic Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
- Joint Metabolome Facility, University of Vienna and Medical University of Vienna, 1090 Vienna, Austria
| | - Petra Heffeter
- Center for Cancer Research and Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
| | - Margit Cichna-Markl
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria
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50
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Wu M, Zhu Q, Huang Y, Tang W, Dai J, Guo Y, Xiong J, Zhang J, Zhou S, Fu F, Wu M, Wang S. Ovarian reserve in reproductive-aged patients with cancer before gonadotoxic treatment: a systematic review and meta-analysis. Hum Reprod Open 2023; 2023:hoad024. [PMID: 37325546 PMCID: PMC10266964 DOI: 10.1093/hropen/hoad024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 05/06/2023] [Indexed: 06/17/2023] Open
Abstract
STUDY QUESTION Does cancer itself, before any gonadotoxic treatment, affect ovarian function in reproductive-aged patients? SUMMARY ANSWER Our study revealed that women with cancer may have decreased ovarian reserve markers even before cancer therapy. WHAT IS KNOWN ALREADY With the field 'oncofertility' improving rapidly, cancer therapy-mediated ovarian damage is well characterized. However, there is a controversy about whether cancer itself affects ovarian function before gonadotoxic treatment. STUDY DESIGN SIZE DURATION We conducted a systematic meta-analysis investigating the association between cancer and ovarian function prior to gonadotoxic treatment. Titles or abstracts related to ovarian reserve (e.g. anti-Müllerian hormone (AMH), antral follicle count (AFC), or basal follicle-stimulating hormone (FSH)) combined with titles or abstracts related to the exposure (e.g. cancer*, oncolog*, or malignan*) were searched in PubMed, Embase, and Web of Science databases from inception to 1 February 2022. PARTICIPANTS/MATERIALS SETTING METHODS We included cohort, case-control, and cross-sectional studies in English that examined ovarian reserve in reproductive-aged patients (18-45 years) with cancer compared to age-matched controls before cancer treatment. The quality of the included studies was assessed by ROBINS-I. Fixed or random effects were conducted to estimate standard or weighted mean difference (SMD or WMD, respectively) and CI. Heterogeneity was assessed by the Q test and I2 statistics, and publication bias was evaluated by Egger's and Begg's tests. MAIN RESULTS AND THE ROLE OF CHANCE The review identified 17 eligible studies for inclusion. The results showed that cancer patients had lower serum AMH levels compared to healthy controls (SMD = -0.19, 95% CI = -0.34 to -0.03, P = 0.001), especially women with hematological malignancies (SMD = -0.62, 95% CI = -0.99 to -0.24, P = 0.001). The AFC was also decreased in patients with cancer (WMD = -0.93, 95% CI = -1.79 to -0.07, P = 0.033) compared to controls, while inhibin B and basal FSH levels showed no statistically significant differences. LIMITATIONS REASONS FOR CAUTION Serum AMH and basal FSH levels in this meta-analysis showed high heterogeneity, and the small number of studies contributing to most subgroup analyses limited the heterogeneity analysis. Moreover, the studies for specific cancer subtypes may be too small to draw conclusions; more studies are needed to investigate the possible impact of cancer type and stage on ovarian function. WIDER IMPLICATIONS OF THE FINDINGS Our study confirmed the findings that cancer per se, especially hematological malignancies, negatively affects serum AMH level, and AFC values of reproductive-aged women. However, the lower AMH levels and AFC values may also be due to the changes in ovarian physiology under oncological conditions, rather than actual lower ovarian reserves. Based on the meta-analysis, clinicians should raise awareness about the possible need for personalized approaches for young women with cancer who are interested in pursuing fertility preservation strategies before anticancer treatments. STUDY FUNDING/COMPETING INTERESTS This work was financially supported by the National Natural Science Foundation of China (nos 81873824, 82001514, and 81902669) and the Applied Basic Research Program of Wuhan Municipal Bureau of Science and Technology (2019020701011436). The authors declare that they have no conflicts of interest. REGISTRATION NUMBER PROSPERO (CRD42021235954).
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Affiliation(s)
- Meng Wu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qingqing Zhu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yibao Huang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Weicheng Tang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jun Dai
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yican Guo
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiaqiang Xiong
- Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Jinjin Zhang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Su Zhou
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fangfang Fu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mingfu Wu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shixuan Wang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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