1
|
Rivas FWS, Gonçalves R, Mota BS, Sorpreso ICE, Toporcov TN, Filassi JR, Lopes EDT, Schio LR, Comtesse YLP, Baracat EC, Soares Júnior JM. Comprehensive diagnosis of advanced-stage breast cancer: exploring detection methods, molecular subtypes, and demographic influences - A cross-sectional study. Clinics (Sao Paulo) 2024; 79:100510. [PMID: 39413498 DOI: 10.1016/j.clinsp.2024.100510] [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: 09/02/2024] [Accepted: 09/17/2024] [Indexed: 10/18/2024] Open
Abstract
BACKGROUND Brazil faces notable Breast Cancer (BC) mortality despite lower incidence rates versus developed countries. Despite guidelines from medical societies, Brazilian public policy recommends biennial mammographic screening for women aged 50 to 69. This study investigates sociodemographic and clinical factors related to BC detection methods and clinical stage at diagnosis. METHODS The authors conducted a cross-sectional study at a São Paulo tertiary hospital. Patients were divided into 'symptomatic' and 'mammographic' detection groups. Bivariate analyses by detection method and clinical stage compared groups' profiles in terms of sociodemographic and clinical characteristics. Poisson regression analyses assessed sociodemographic and molecular subtypes´ influence on "mammographic detection" prevalence and "advanced-stage BC", reporting prevalence ratios and 95 % Confidence Intervals. RESULTS The authors studied 1,536 BC patients admitted from January 2016 to December 2017. The "mammographic detection" group had a higher proportion of patients aged 50‒69 years (62.9 % vs. 44.1 %), white race (63.3 % vs. 51.6 %), Catholic religion (58.2 % vs. 51.1 %), and Luminal A subtype (25.2 % vs. 13.2 %) compared to the "symptomatic detection" group. Patients with early-stage disease were more likely to have higher education levels (8.1 % vs. 5.5 %) and be married (39.8 % vs. 46.6 %) compared to those with advanced-stage. Molecular subtypes were significantly associated with the detection method and stage. The prevalence of advanced-stage disease in "mammographic" (n=313) and "symptomatic" (n=1191) groups was 18.5 % and 55 %, respectively . Mammographic detection significantly reduced advanced-stage BC prevalence (PR = 0.40, 95 % CI 0.31‒0.51). CONCLUSION Mammographic detection reduces advanced-stage breast cancer prevalence in Brazil, emphasizing the importance of regular screenings, especially among at-risk sociodemographic groups. Enhancing mammographic screening accessibility, lowering the starting age to 40, and extending coverage to include annual mammograms can significantly lower breast cancer mortality in Brazil, benefiting public health and patient outcomes.
Collapse
Affiliation(s)
- Fernando Wladimir Silva Rivas
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Rodrigo Gonçalves
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil; Setor de Mastologia da Disciplina de Ginecologia, Instituto de Câncer do Estado de São Paulo, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil.
| | - Bruna Salani Mota
- Setor de Mastologia da Disciplina de Ginecologia, Instituto de Câncer do Estado de São Paulo, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Isabel Cristina Esposito Sorpreso
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Tatiana Natasha Toporcov
- Departamento de Epidemiologia, Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo, SP, Brazil
| | - José Roberto Filassi
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil; Setor de Mastologia da Disciplina de Ginecologia, Instituto de Câncer do Estado de São Paulo, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Edia di Tullio Lopes
- Registro Hospitalar de Câncer, Serviço de Arquivo Médico, Instituto de Câncer do Estado de São Paulo, São Paulo, SP, Brazil
| | - Laura Raíssa Schio
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Yann-Luc Patrick Comtesse
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - Edmund Chada Baracat
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| | - José Maria Soares Júnior
- Disciplina de Ginecologia, Departamento de Obstetrícia e Ginecologia, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil
| |
Collapse
|
2
|
Haque M, Shyanti RK, Mishra MK. Targeted therapy approaches for epithelial-mesenchymal transition in triple negative breast cancer. Front Oncol 2024; 14:1431418. [PMID: 39450256 PMCID: PMC11499239 DOI: 10.3389/fonc.2024.1431418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Accepted: 09/24/2024] [Indexed: 10/26/2024] Open
Abstract
Triple-negative breast cancer (TNBC) is distinguished by negative expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), making it an aggressive subtype of breast cancer and contributes to 15-20% of the total incidence. TNBC is a diverse disease with various genetic variations and molecular subtypes. The tumor microenvironment involves multiple cells, including immune cells, fibroblast cells, extracellular matrix (ECM), and blood vessels that constantly interact with tumor cells and influence each other. The ECM undergoes significant structural changes, leading to induced cell proliferation, migration, adhesion, invasion, and epithelial-to-mesenchymal transition (EMT). The involvement of EMT in the occurrence and development of tumors through invasion and metastasis in TNBC has been a matter of concern. Therefore, EMT markers could be prognostic predictors and potential therapeutic targets in TNBC. Chemotherapy has been one of the primary options for treating patients with TNBC, but its efficacy against TNBC is still limited. Targeted therapy is a critical emerging option with enhanced efficacy and less adverse effects on patients. Various targeted therapy approaches have been developed based on the specific molecules and the signaling pathways involved in TNBC. These include inhibitors of signaling pathways such as TGF-β, Wnt/β-catenin, Notch, TNF-α/NF-κB and EGFR, as well as immune checkpoint inhibitors, such as pembrolizumab, 2laparib, and talazoparib have been widely explored. This article reviews recent developments in EMT in TNBC invasion and metastasis and potential targeted therapy strategies.
Collapse
Affiliation(s)
| | | | - Manoj K. Mishra
- Cancer Research Center, Department of Biological Sciences, Alabama State
University, Montgomery, AL, United States
| |
Collapse
|
3
|
Ahmadi S, Yazdi F, Khastar S, Kaur I, Ahmed MH, Kumar A, Rathore G, Kaur P, Shahsavan M, Dehghani-Ghorbi M, Akhavan-Sigari R. Molecular Mechanism of lncRNAs in Regulation of Breast Cancer Metastasis; a Comprehensive Review. Cell Biochem Biophys 2024:10.1007/s12013-024-01535-y. [PMID: 39367197 DOI: 10.1007/s12013-024-01535-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/07/2024] [Indexed: 10/06/2024]
Abstract
Although the number of breast cancer deaths has decreased, and there have been developments in targeted therapies and combination treatments for the management of metastatic illness, metastatic breast cancer is still the second most common cause of cancer-related deaths in U.S. women. Numerous phases and a vast number of proteins and signaling molecules are involved in the invasion-metastasis cascade. The tumor cells penetrate and enter the blood or lymphatic vessels, and travel to distant organs via the lymphatic or blood vessels. Tumor cells enter cell cycle arrest, adhere to capillary beds in the target organ, and then disseminate throughout the organ's parenchyma, proliferating and enhancing angiogenesis. Each of these processes is regulated by changes in the expression of different genes, in which lncRNAs play a role in this regulation. Transcripts that are longer than 200 nucleotides and do not translate into proteins are called RNAs. LncRNA molecules, whose function depends on their unique molecular structure, play significant roles in controlling the expression of genes at various epigenetic levels, transcription, and so on. LncRNAs have essential functions in regulating the expression of genes linked to cell development in healthy and pathological processes, specialization, programmed cell death, cell division, invasion, DNA damage, and spread to other parts of the body. A number of cancer types have been shown to exhibit aberrant expression of lncRNAs. In this review, we describe the general characteristics, potential molecular mechanisms and targeted therapy of lncRNAs and discuss the emerging functions of lncRNAs in breast cancer.
Collapse
Affiliation(s)
- Shokoufeh Ahmadi
- Department of Microbiology, Rabe'Rashidi University, Tabriz, Iran
| | - Farzaneh Yazdi
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Sahar Khastar
- Department of Immunology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Irwanjot Kaur
- Department of Biotechnology and Genetics, Jain (Deemed-to-be) University, Bengaluru, Karnataka-560069, India
- Department of Allied Healthcare and Sciences, Vivekananda Global University, Jaipur, Rajasthan-303012, India
| | | | - Abhishek Kumar
- School of Pharmacy-Adarsh Vijendra Institute of Pharmaceutical Sciences, Shobhit University, Gangoh, Uttar Pradesh-247341, India
- Department of Pharmacy, Arka Jain University, Jamshedpur, Jharkhand-831001, India
| | - Gulshan Rathore
- Department of Pharmaceutics, NIMS Institute of Pharmacy, NIMS University Rajasthan, Jaipur, India
| | - Parjinder Kaur
- Chandigarh Pharmacy College, Chandigarh Group of Colleges-Jhanjeri, Mohali 140307, Punjab, India
| | - Mohammad Shahsavan
- Department of Orthopedic Surgery, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Mahmoud Dehghani-Ghorbi
- Hematology-Oncology Department, Imam Hossein Educational Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Reza Akhavan-Sigari
- Department of Neurosurgery, University Medical Center, Tuebingen, Germany
- Department of Health Care Management and Clinical Research, Collegium Humanum Warsaw Management University Warsaw, Warsaw, Poland
| |
Collapse
|
4
|
Stout NK, Miglioretti DL, Su YR, Lee CI, Abraham L, Alagoz O, de Koning HJ, Hampton JM, Henderson L, Lowry KP, Mandelblatt JS, Onega T, Schechter CB, Sprague BL, Stein S, Trentham-Dietz A, van Ravesteyn NT, Wernli KJ, Kerlikowske K, Tosteson ANA. Breast Cancer Screening Using Mammography, Digital Breast Tomosynthesis, and Magnetic Resonance Imaging by Breast Density. JAMA Intern Med 2024; 184:1222-1231. [PMID: 39186304 PMCID: PMC11348087 DOI: 10.1001/jamainternmed.2024.4224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/01/2024] [Indexed: 08/27/2024]
Abstract
Importance Information on long-term benefits and harms of screening with digital breast tomosynthesis (DBT) with or without supplemental breast magnetic resonance imaging (MRI) is needed for clinical and policy discussions, particularly for patients with dense breasts. Objective To project long-term population-based outcomes for breast cancer mammography screening strategies (DBT or digital mammography) with or without supplemental MRI by breast density. Design, Setting, and Participants Collaborative modeling using 3 Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer simulation models informed by US Breast Cancer Surveillance Consortium data. Simulated women born in 1980 with average breast cancer risk were included. Modeling analyses were conducted from January 2020 to December 2023. Intervention Annual or biennial mammography screening with or without supplemental MRI by breast density starting at ages 40, 45, or 50 years through age 74 years. Main outcomes and Measures Lifetime breast cancer deaths averted, false-positive recall and false-positive biopsy recommendations per 1000 simulated women followed-up from age 40 years to death summarized as means and ranges across models. Results Biennial DBT screening for all simulated women started at age 50 vs 40 years averted 7.4 vs 8.5 breast cancer deaths, respectively, and led to 884 vs 1392 false-positive recalls and 151 vs 221 false-positive biopsy recommendations, respectively. Biennial digital mammography had similar deaths averted and slightly more false-positive test results than DBT screening. Adding MRI for women with extremely dense breasts to biennial DBT screening for women aged 50 to 74 years increased deaths averted (7.6 vs 7.4), false-positive recalls (919 vs 884), and false-positive biopsy recommendations (180 vs 151). Extending supplemental MRI to women with heterogeneously or extremely dense breasts further increased deaths averted (8.0 vs 7.4), false-positive recalls (1088 vs 884), and false-positive biopsy recommendations (343 vs 151). The same strategy for women aged 40 to 74 years averted 9.5 deaths but led to 1850 false-positive recalls and 628 false-positive biopsy recommendations. Annual screening modestly increased estimated deaths averted but markedly increased estimated false-positive results. Conclusions and relevance In this model-based comparative effectiveness analysis, supplemental MRI for women with dense breasts added to DBT screening led to greater benefits and increased harms. The balance of this trade-off for supplemental MRI use was more favorable when MRI was targeted to women with extremely dense breasts who comprise approximately 10% of the population.
Collapse
Affiliation(s)
- Natasha K. Stout
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Diana L. Miglioretti
- Department of Public Health Sciences, University of California Davis School of Medicine, Davis
| | - Yu-Ru Su
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Christoph I. Lee
- Fred Hutchinson Cancer Center, University of Washington School of Medicine, Seattle
| | - Linn Abraham
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Oguzhan Alagoz
- Department of Industrial and Systems Engineering and Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin–Madison, Madison
| | - Harry J. de Koning
- Department of Public Health, Erasmus University Medical Center Rotterdam, the Netherlands
| | - John M. Hampton
- Department of Industrial and Systems Engineering and Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin–Madison, Madison
| | - Louise Henderson
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill
| | - Kathryn P. Lowry
- Fred Hutchinson Cancer Center University of Washington School of Medicine, Seattle
| | - Jeanne S. Mandelblatt
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Department of Oncology and Georgetown Lombardi Institute for Cancer and Aging REsearch (I-CARE), Georgetown University, Washington, DC
| | - Tracy Onega
- Department of Population Health Sciences, and the Huntsman Cancer Institute, University of Utah, Salt Lake City
| | - Clyde B. Schechter
- Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, New York
| | - Brian L. Sprague
- Department of Surgery, University of Vermont Cancer Center, Burlington, Vermont
- University of Vermont Larner College of Medicine, Burlington
- Department of Radiology, University of Vermont Cancer Center, Burlington, Vermont
| | - Sarah Stein
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin–Madison, Madison
| | | | - Karen J. Wernli
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Karla Kerlikowske
- Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Anna N. A. Tosteson
- The Dartmouth Institute for Health Policy and Clinical Practice, Departments of Medicine and of Community and Family Medicine, and Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
| |
Collapse
|
5
|
Gopalani SV, Qin J, Baksa J, Thompson TD, Senkomago V, Pordell P, Jeong Y, Reichhardt M, Palafox N, Buenconsejo-Lum L. Breast cancer incidence and stage at diagnosis in the six US-Affiliated Pacific Islands. Cancer Epidemiol 2024; 92:102611. [PMID: 38996557 PMCID: PMC11402563 DOI: 10.1016/j.canep.2024.102611] [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: 04/16/2024] [Revised: 07/01/2024] [Accepted: 07/03/2024] [Indexed: 07/14/2024]
Abstract
BACKGROUND Breast cancer is the most common cancer diagnosed among women globally and in the United States (US); however, its incidence in the six US-Affiliated Pacific Islands (USAPI) remains less characterized. METHODS We analyzed data from a population-based cancer registry using different population estimates to calculate incidence rates for breast cancer among women aged >20 years in the USAPI. Rate ratios and 95 % confidence intervals (CI) were calculated to compare incidence rates between the USAPI and the US (50 states and the District of Columbia). RESULTS From 2007-2020, 1118 new cases of breast cancer were diagnosed in the USAPI, with 66.3 % (n = 741) of cases reported in Guam. Age-standardized incidence rates ranged from 66.4 to 68.7 per 100,000 women in USAPI and 101.1-110.5 per 100,000 women in Guam. Compared to the US, incidence rates were lower in USAPI, with rate ratios ranging from 0.38 (95 % CI: 0.36, 0.40) to 0.39 (95 % CI: 0.37, 0.42). The proportion of late-stage cancer was significantly higher in the USAPI (48.7 %) than in the US (34.0 %), particularly in the Federated States of Micronesia (78.7 %) and Palau (73.1 %). CONCLUSIONS Breast cancer incidence rates were lower in the USAPI than in the US; however, late-stage diagnoses were disproportionately higher. Low incidence and late-stage cancers may signal challenges in screening, cancer surveillance, and health care access and resources. Expanding access to timely breast cancer screening, diagnosis, and treatment could reduce the proportion of late-stage cancers and improve survival in the USAPI.
Collapse
Affiliation(s)
- Sameer V Gopalani
- Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, United States; Oak Ridge Institute for Science and Education, Oak Ridge, TN, United States
| | - Jin Qin
- Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Janos Baksa
- John A Burns School of Medicine, University of University of Hawaii at Manoa, Honolulu, HI, United States
| | - Trevor D Thompson
- Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Virginia Senkomago
- Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Paran Pordell
- Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Youngju Jeong
- John A Burns School of Medicine, University of University of Hawaii at Manoa, Honolulu, HI, United States
| | - Martina Reichhardt
- Yap State Department of Health Services, Yap, Federated States of Micronesia
| | - Neal Palafox
- John A Burns School of Medicine, University of University of Hawaii at Manoa, Honolulu, HI, United States
| | - Lee Buenconsejo-Lum
- John A Burns School of Medicine, University of University of Hawaii at Manoa, Honolulu, HI, United States.
| |
Collapse
|
6
|
Moriakov N, Peters J, Mann R, Karssemeijer N, van Dijck J, Broeders M, Teuwen J. Improving lesion volume measurements on digital mammograms. Med Image Anal 2024; 97:103269. [PMID: 39024973 DOI: 10.1016/j.media.2024.103269] [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: 08/30/2023] [Revised: 06/23/2024] [Accepted: 07/08/2024] [Indexed: 07/20/2024]
Abstract
Lesion volume is an important predictor for prognosis in breast cancer. However, it is currently impossible to compute lesion volumes accurately from digital mammography data, which is the most popular and readily available imaging modality for breast cancer. We make a step towards a more accurate lesion volume measurement on digital mammograms by developing a model that allows to estimate lesion volumes on processed mammogram. Processed mammograms are the images routinely used by radiologists in clinical practice as well as in breast cancer screening and are available in medical centers. Processed mammograms are obtained from raw mammograms, which are the X-ray data coming directly from the scanner, by applying certain vendor-specific non-linear transformations. At the core of our volume estimation method is a physics-based algorithm for measuring lesion volumes on raw mammograms. We subsequently extend this algorithm to processed mammograms via a deep learning image-to-image translation model that produces synthetic raw mammograms from processed mammograms in a multi-vendor setting. We assess the reliability and validity of our method using a dataset of 1778 mammograms with an annotated mass. Firstly, we investigate the correlations between lesion volumes computed from mediolateral oblique and craniocaudal views, with a resulting Pearson correlation of 0.93 [95% confidence interval (CI) 0.92 - 0.93]. Secondly, we compare the resulting lesion volumes from true and synthetic raw data, with a resulting Pearson correlation of 0.998 [95%CI 0.998 - 0.998] . Finally, for a subset of 100 mammograms with a malignant mass and concurrent MRI examination available, we analyze the agreement between lesion volume on mammography and MRI, resulting in an intraclass correlation coefficient of 0.81 [95%CI 0.73 - 0.87] for consistency and 0.78 [95%CI 0.66 - 0.86] for absolute agreement. In conclusion, we developed an algorithm to measure mammographic lesion volume that reached excellent reliability and good validity, when using MRI as ground truth. The algorithm may play a role in lesion characterization and breast cancer prognostication on mammograms.
Collapse
Affiliation(s)
- Nikita Moriakov
- Department of Radiation Oncology, Netherlands Cancer Institute, The Netherlands; Department of Medical Imaging, Radboud University Medical Center, The Netherlands; Institute for Informatics, University of Amsterdam, The Netherlands.
| | - Jim Peters
- Department for Health Evidence, Radboud University Medical Center, The Netherlands
| | - Ritse Mann
- Department of Medical Imaging, Radboud University Medical Center, The Netherlands
| | - Nico Karssemeijer
- Department of Medical Imaging, Radboud University Medical Center, The Netherlands
| | - Jos van Dijck
- Department for Health Evidence, Radboud University Medical Center, The Netherlands
| | - Mireille Broeders
- Department for Health Evidence, Radboud University Medical Center, The Netherlands
| | - Jonas Teuwen
- Department of Radiation Oncology, Netherlands Cancer Institute, The Netherlands; Department of Medical Imaging, Radboud University Medical Center, The Netherlands
| |
Collapse
|
7
|
Peters J, van Dijck JA, Elias SG, Otten JD, Broeders MJ. The prognostic potential of mammographic growth rate of invasive breast cancer in the Nijmegen breast cancer screening cohort. J Med Screen 2024; 31:166-175. [PMID: 38295359 PMCID: PMC11330081 DOI: 10.1177/09691413231222765] [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: 09/07/2023] [Accepted: 11/15/2023] [Indexed: 02/02/2024]
Abstract
OBJECTIVES Insight into the aggressiveness of potential breast cancers found in screening may optimize recall decisions. Specific growth rate (SGR), measured on mammograms, may provide valuable prognostic information. This study addresses the association of SGR with prognostic factors and overall survival in patients with invasive carcinoma of no special type (NST) from a screened population. METHODS In this historic cohort study, 293 women with NST were identified from all participants in the Nijmegen screening program (2003-2007). Information on clinicopathological factors was retrieved from patient files and follow-up on vital status through municipalities. On consecutive mammograms, tumor volumes were estimated. After comparing five growth functions, SGR was calculated using the best-fitting function. Regression and multivariable survival analyses described associations between SGR and prognostic factors as well as overall survival. RESULTS Each one standard deviation increase in SGR was associated with an increase in the Nottingham prognostic index by 0.34 [95% confidence interval (CI): 0.21-0.46]. Each one standard deviation increase in SGR increased the odds of a tumor with an unfavorable subtype (based on histologic grade and hormone receptors; odds ratio 2.14 [95% CI: 1.45-3.15]) and increased the odds of diagnosis as an interval cancer (versus screen-detected; odds ratio 1.57 [95% CI: 1.20-2.06]). After a median of 12.4 years of follow-up, 78 deaths occurred. SGR was not associated with overall survival (hazard ratio 1.12 [95% CI: 0.87-1.43]). CONCLUSIONS SGR may indicate prognostically relevant differences in tumor aggressiveness if serial mammograms are available. A potential association with cause-specific survival could not be determined and is of interest for future research.
Collapse
Affiliation(s)
- Jim Peters
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jos A.A.M. van Dijck
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sjoerd G. Elias
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Johannes D.M. Otten
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mireille J.M. Broeders
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
- Dutch Expert Centre for Screening (LRCB), Nijmegen, The Netherlands
| | | |
Collapse
|
8
|
Stearns SA, Lee D, Bustos VP, Haddad A, Hassell N, Kim E, Foppiani JA, Lee TC, Lin SJ, Lee BT. Enhancing Post-Mastectomy Care: Telehealth's Impact on Breast Reconstruction Accessibility for Breast Cancer Patients. Cancers (Basel) 2024; 16:2555. [PMID: 39061194 PMCID: PMC11274770 DOI: 10.3390/cancers16142555] [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: 06/13/2024] [Revised: 07/08/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
OBJECTIVE To examine how the recent sharp rise in telemedicine has impacted trends in accessibility of breast reconstruction (BR). PATIENTS AND METHODS A retrospective study reviewed patients who underwent a total mastectomy at our institution from 1 August 2016 to 31 January 2022. By comparing cohorts before and during the widespread implementation of telemedicine, we assessed telehealth's impact on healthcare accessibility, measured by distance from patients' residences to our institution. RESULTS A total of 359 patients were included in this study. Of those, 176 received total mastectomy prior to the availability of telemedicine, and 183 in the subsequent period. There were similar baseline characteristics among patients undergoing mastectomy, including distance from place of residence to hospital (p = 0.67). The same proportion elected to receive BR between groups (p = 0.22). Those declining BR traveled similar distances as those electing the procedure, both before the era of widespread telemedicine adoption (40.3 and 35.6 miles, p = 0.56) and during the height of telemedicine use (22.3 and 61.3 miles, p = 0.26). When tracking follow-up care, significantly more patients during the pandemic pursued at least one follow-up visit with their original surgical team, indicative of the increased utilization of telehealth services. CONCLUSIONS While the rate of BR remained unchanged during the pandemic, our findings reveal significant shifts in healthcare utilization, highly attributed to the surge in telehealth adoption. This suggests a transformative impact on breast cancer care, emphasizing the need for continued exploration of telemedicine's role in enhancing accessibility and patient follow-up in the post-pandemic era.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | - Samuel J. Lin
- Beth Israel Deaconess Medical Center, Division of Plastic and Reconstructive Surgery, Harvard Medical School, Boston, MA 02215, USA
| | - Bernard T. Lee
- Beth Israel Deaconess Medical Center, Division of Plastic and Reconstructive Surgery, Harvard Medical School, Boston, MA 02215, USA
| |
Collapse
|
9
|
Banday SZ, Ayub M, Rasool MT, Ahmed SZ, Banday AZ, Naveed S, Guru FR, Mir MH, Akhter S, Bhat MH, Yaseen SB, Afroz F, Bhat GM, Lone MM, Aziz SA. Receptor subtype and outcome of breast cancer - Single-center experience from North India. J Cancer Res Ther 2024; 20:1486-1493. [PMID: 39412912 DOI: 10.4103/jcrt.jcrt_56_23] [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: 01/08/2023] [Accepted: 03/11/2023] [Indexed: 10/18/2024]
Abstract
AIMS/OBJECTIVES In resource-limited settings, data regarding the impact of molecular/receptor subtypes on breast cancer (BC) are sparse. In this single-center retrospective study from north India, we analyze the outcomes of various molecular subtypes of BC. MATERIALS AND METHODS Females with biopsy-proven BC who were treated at our State Cancer Institute from 2014-2018 were included. Data regarding clinicopathological parameters and follow-up details were evaluated. For data analysis, cancers were categorized into 4 subtypes: HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-. RESULTS Among 944 patients included, HR+HER2- (49.1%) and HR+HER2+ (13.1%) were the most and least common subtypes, respectively. The receptor subtype significantly impacted overall survival (OS). HR+HER2- cancers had the best outcomes while HR-HER2- cancers fared worst (3-yr OS of 94.3% and 69.1%, respectively). On subgroup analysis, the molecular subtype continued to significantly impact OS in patients with tumor grades II and III, disease stages II and III, and age groups of <40 and 40-60 years, respectively (HR-HER2- cancers had the lowest cumulative survival in each subgroup). In patients with metastatic BC, all molecular subtypes except HR+HER2- had a dismal prognosis. CONCLUSIONS Overall and across various subgroups, patients with triple-negative BC had the poorest outcomes. Ensuring optimal treatment utilization including affordable access to personalized tailored therapy is the need of the hour to improve long-term outcomes in these patients.
Collapse
Affiliation(s)
- Saquib Z Banday
- Department of Medical Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Maniza Ayub
- Department of Pathology, Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Malik T Rasool
- Department of Radiation Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Sheikh Z Ahmed
- Department of Surgical Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Aaqib Z Banday
- Department of Pediatrics, Government Medical College (GMC), Srinagar, Jammu and Kashmir, India
| | - Shah Naveed
- Department of Surgical Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Faisal R Guru
- Department of Medical Oncology (Pediatrics), State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Mohmad H Mir
- Department of Medical Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Shareefa Akhter
- Department of Pathology, Government Medical College (GMC), Srinagar, Jammu and Kashmir, India
| | - Mudasir H Bhat
- Department of Radiodiagnosis and Imaging, Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Syed B Yaseen
- Department of Pathology, Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Fir Afroz
- Department of Radiation Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Gull M Bhat
- Department of Medical Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Mohammad M Lone
- Department of Radiation Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| | - Shiekh A Aziz
- Department of Medical Oncology, State Cancer Institute (SCI), Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, India
| |
Collapse
|
10
|
Zhu A, Patel BK, Khurana A, Maxwell RW, Ellis RL, Fazzio RT, Sharpe RE. Breast Cancer Method of Detection: 5-Year Outcomes Across a Multisite Health Care Enterprise. J Am Coll Radiol 2024; 21:993-1000. [PMID: 38176672 DOI: 10.1016/j.jacr.2023.12.026] [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: 09/28/2023] [Revised: 12/13/2023] [Accepted: 12/26/2023] [Indexed: 01/06/2024]
Abstract
PURPOSE To investigate the feasibility and accuracy of radiologists categorizing the method of detection (MOD) when performing image-guided breast biopsies. METHODS This retrospective, observational study was conducted across a health care enterprise that provides breast imaging services at 18 imaging sites across four US states. Radiologists used standardized templates to categorize the MOD, defined as the first test, sign, or symptom that triggered the subsequent workup and recommendation for biopsy. All image-guided breast biopsies since the implementation of the MOD-inclusive standardized template-from October 31, 2017 to July 6, 2023-were extracted. A random sample of biopsy reports was manually reviewed to evaluate the accuracy of MOD categorization. RESULTS A total of 29,999 biopsies were analyzed. MOD was reported in 29,423 biopsies (98.1%) at a sustained rate that improved over time. The 10 MOD categories in this study included the following: 15,184 mammograms (51.6%); 4,561 MRIs (15.5%); 3,473 ultrasounds (11.8%); 2,382 self-examinations (8.1%); 2,073 tomosynthesis studies (7.0%); 432 clinical examinations (1.5%); 421 molecular breast imaging studies (1.4%); 357 other studies (1.2%); 338 contrast-enhanced digital mammograms (1.1%); and 202 PET studies (0.7%). Original assignments of the MOD agreed with author assignments in 87% of manually reviewed biopsies (n = 100, 95% confidence interval: [80.4%, 93.6%]). CONCLUSIONS This study demonstrates that US radiologists can consistently and accurately categorize the MOD over an extended time across a health care enterprise.
Collapse
Affiliation(s)
- Alan Zhu
- Mayo Clinic Alix School of Medicine, Phoenix, Arizona.
| | - Bhavika K Patel
- Vice Chair of Research, Division of Breast Imaging and Intervention, Mayo Clinic Arizona, Phoenix, Arizona; Co-chair, ACR Data Science Institute Breast Panel; and Co-chair, ACR Breast Imaging Research Registry
| | - Aditya Khurana
- Division of Breast Imaging and Intervention, Mayo Clinic Rochester, Rochester, Minnesota
| | - Robert W Maxwell
- Division Chair, Division of Breast Imaging and Intervention, Mayo Clinic Florida, Jacksonville, Florida
| | - Richard L Ellis
- Division Chair, Division of Breast Imaging and Intervention, Mayo Clinic Health Systems, LaCrosse, Wisconsin
| | - Robert T Fazzio
- Division Chair, Division of Breast Imaging and Intervention, Mayo Clinic Rochester, Rochester, Minnesota
| | - Richard E Sharpe
- Division Chair, Division of Breast Imaging and Intervention, Mayo Clinic Arizona, Phoenix, Arizona; Chair, Mayo Clinic Enterprise Breast Imaging Collaboration Team; Member, ACR Screening and Emerging Technology Committee; Member, ACR Peer Learning Committee; and Member, ACR Breast Imaging Appropriateness Panel
| |
Collapse
|
11
|
Trentham-Dietz A, Chapman CH, Jayasekera J, Lowry KP, Heckman-Stoddard BM, Hampton JM, Caswell-Jin JL, Gangnon RE, Lu Y, Huang H, Stein S, Sun L, Gil Quessep EJ, Yang Y, Lu Y, Song J, Muñoz DF, Li Y, Kurian AW, Kerlikowske K, O'Meara ES, Sprague BL, Tosteson ANA, Feuer EJ, Berry D, Plevritis SK, Huang X, de Koning HJ, van Ravesteyn NT, Lee SJ, Alagoz O, Schechter CB, Stout NK, Miglioretti DL, Mandelblatt JS. Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force. JAMA 2024; 331:1947-1960. [PMID: 38687505 DOI: 10.1001/jama.2023.24766] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Importance The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective To estimate outcomes of various mammography screening strategies. Design, Setting, and Population Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.
Collapse
Affiliation(s)
- Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Christina Hunter Chapman
- Department of Radiation Oncology and Center for Innovations in Quality, Safety, and Effectiveness, Baylor College of Medicine, Houston, Texas
| | - Jinani Jayasekera
- Health Equity and Decision Sciences (HEADS) Research Laboratory, Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland
| | | | - Brandy M Heckman-Stoddard
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - John M Hampton
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison
| | | | - Ronald E Gangnon
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Ying Lu
- Stanford University, Stanford, California
| | - Hui Huang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sarah Stein
- Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Liyang Sun
- Stanford University, Stanford, California
| | | | | | - Yifan Lu
- Department of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison
| | - Juhee Song
- University of Texas MD Anderson Cancer Center, Houston
| | | | - Yisheng Li
- University of Texas MD Anderson Cancer Center, Houston
| | - Allison W Kurian
- Departments of Medicine and Epidemiology and Population Health, Stanford University, Stanford, California
| | - Karla Kerlikowske
- Departments of Medicine and Epidemiology and Biostatistics, University of California San Francisco
| | - Ellen S O'Meara
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | | | - Anna N A Tosteson
- Dartmouth Institute for Health Policy and Clinical Practice and Departments of Medicine and Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, New Hampshire
| | - Eric J Feuer
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Donald Berry
- University of Texas MD Anderson Cancer Center, Houston
| | - Sylvia K Plevritis
- Departments of Biomedical Data Science and Radiology, Stanford University, Stanford, California
| | - Xuelin Huang
- University of Texas MD Anderson Cancer Center, Houston
| | | | | | - Sandra J Lee
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Oguzhan Alagoz
- Department of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison
| | | | - Natasha K Stout
- Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Diana L Miglioretti
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Public Health Sciences, University of California Davis
| | - Jeanne S Mandelblatt
- Departments of Oncology and Medicine, Georgetown University Medical Center, and Georgetown Lombardi Comprehensive Institute for Cancer and Aging Research at Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC
| |
Collapse
|
12
|
Nicholson WK, Silverstein M, Wong JB, Barry MJ, Chelmow D, Coker TR, Davis EM, Jaén CR, Krousel-Wood M, Lee S, Li L, Mangione CM, Rao G, Ruiz JM, Stevermer JJ, Tsevat J, Underwood SM, Wiehe S. Screening for Breast Cancer: US Preventive Services Task Force Recommendation Statement. JAMA 2024; 331:1918-1930. [PMID: 38687503 DOI: 10.1001/jama.2024.5534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Importance Among all US women, breast cancer is the second most common cancer and the second most common cause of cancer death. In 2023, an estimated 43 170 women died of breast cancer. Non-Hispanic White women have the highest incidence of breast cancer and non-Hispanic Black women have the highest mortality rate. Objective The USPSTF commissioned a systematic review to evaluate the comparative effectiveness of different mammography-based breast cancer screening strategies by age to start and stop screening, screening interval, modality, use of supplemental imaging, or personalization of screening for breast cancer on the incidence of and progression to advanced breast cancer, breast cancer morbidity, and breast cancer-specific or all-cause mortality, and collaborative modeling studies to complement the evidence from the review. Population Cisgender women and all other persons assigned female at birth aged 40 years or older at average risk of breast cancer. Evidence Assessment The USPSTF concludes with moderate certainty that biennial screening mammography in women aged 40 to 74 years has a moderate net benefit. The USPSTF concludes that the evidence is insufficient to determine the balance of benefits and harms of screening mammography in women 75 years or older and the balance of benefits and harms of supplemental screening for breast cancer with breast ultrasound or magnetic resonance imaging (MRI), regardless of breast density. Recommendation The USPSTF recommends biennial screening mammography for women aged 40 to 74 years. (B recommendation) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening mammography in women 75 years or older. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of supplemental screening for breast cancer using breast ultrasonography or MRI in women identified to have dense breasts on an otherwise negative screening mammogram. (I statement).
Collapse
Affiliation(s)
| | | | - John B Wong
- Tufts University School of Medicine, Boston, Massachusetts
| | | | | | | | - Esa M Davis
- University of Maryland School of Medicine, Baltimore
| | | | | | - Sei Lee
- University of California, San Francisco
| | - Li Li
- University of Virginia, Charlottesville
| | | | - Goutham Rao
- Case Western Reserve University, Cleveland, Ohio
| | | | | | - Joel Tsevat
- The University of Texas Health Science Center, San Antonio
| | | | | |
Collapse
|
13
|
Zhu S, Wang S, Guo S, Wu R, Zhang J, Kong M, Pan L, Gu Y, Yu S. Contrast-Enhanced Mammography Radiomics Analysis for Preoperative Prediction of Breast Cancer Molecular Subtypes. Acad Radiol 2024; 31:2228-2238. [PMID: 38142176 DOI: 10.1016/j.acra.2023.12.005] [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: 09/27/2023] [Revised: 11/28/2023] [Accepted: 12/01/2023] [Indexed: 12/25/2023]
Abstract
BACKGROUND Predicting breast cancer molecular subtypes can help guide individualised clinical treatment of patients who need the rational preoperative treatment. This study aimed to investigate the efficacy of preoperative prediction of breast cancer molecular subtypes by contrast-enhanced mammography (CEM) radiomic features. METHODS This retrospective two-centre study included women with breast cancer who underwent CEM preoperatively between August 2016 and May 2022. We included 356 patients with 386 lesions, which were grouped into training (n = 162), internal test (n = 160) and external test sets (n = 64). Radiomics features were extracted from low-energy (LE) images and recombined (RC) images and selected. Three dichotomous tasks were established according to postoperative immunohistochemical results: Luminal vs. non-Luminal, human epidermal growth factor receptor (HER2)-enriched vs. non-HER2-enriched, and triple-negative breast cancer (TNBC) vs. non-TNBC. For each dichotomous task, the LE, RC, and LE+RC radiomics models were built by the support vector machine classifier. The prediction performance of the models was assessed by the area under the receiver operating characteristic curve (AUC). Then, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the models. DeLong's test was utilised to compare the AUCs. RESULTS Radiomics models based on CEM are valuable for predicting breast cancer molecular subtypes. The LE+RC model achieved the best performance in the test set. The LE+RC model predicted Luminal, HER2-enriched, and TNBC subtypes with AUCs of 0.93, 0.89, and 0.87 in the internal test set and 0.82, 0.83, and 0.69 in the external test set, respectively. In addition, the LE model performed more satisfactorily than the RC model. CONCLUSION CEM radiomics features can effectively predict breast cancer molecular subtypes preoperatively, and the LE+RC model has the best predictive performance.
Collapse
Affiliation(s)
- Shuangshuang Zhu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.)
| | - Simin Wang
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China (S.W., Y.G.)
| | - Sailing Guo
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.)
| | - Ruoxi Wu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.)
| | - Jinggang Zhang
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.)
| | - Mengyu Kong
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.)
| | - Liang Pan
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.)
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China (S.W., Y.G.)
| | - Shengnan Yu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China (S.Z., S.G., R.W., J.Z., M.K., L.P., S.Y.).
| |
Collapse
|
14
|
Duffy MJ, Crown J. Circulating tumor DNA (ctDNA): can it be used as a pan-cancer early detection test? Crit Rev Clin Lab Sci 2024; 61:241-253. [PMID: 37936529 DOI: 10.1080/10408363.2023.2275150] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/21/2023] [Indexed: 11/09/2023]
Abstract
Circulating tumor DNA (ctDNA, DNA shed by cancer cells) is emerging as one of the most transformative cancer biomarkers discovered to-date. Although potentially useful at all the phases of cancer detection and patient management, one of its most exciting possibilities is as a relatively noninvasive pan-cancer screening test. Preliminary findings with ctDNA tests such as Galleri or CancerSEEK suggest that they have high specificity (> 99.0%) for malignancy. Their sensitivity varies depending on the type of cancer and stage of disease but it is generally low in patients with stage I disease. A major advantage of ctDNA over existing screening strategies is the potential ability to detect multiple cancer types in a single test. A limitation of most studies published to-date is that they are predominantly case-control investigations that were carried out in patients with a previous diagnosis of malignancy and that used apparently healthy subjects as controls. Consequently, the reported sensitivities, specificities and positive predictive values might be lower if the tests are used for screening in asymptomatic populations, that is, in the population where these tests are likely be employed. To demonstrate clinical utility in an asymptomatic population, these tests must be shown to reduce cancer mortality without causing excessive overdiagnosis in a large randomized prospective randomized trial. Such trials are currently ongoing for Galleri and CancerSEEK.
Collapse
Affiliation(s)
- Michael J Duffy
- UCD School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
- UCD Clinical Research Centre, St. Vincent's University Hospital, Dublin, Ireland
| | - John Crown
- Department of Medical Oncology, St Vincent's University Hospital, Dublin, Ireland
| |
Collapse
|
15
|
Kuklinski D, Blum M, Subelack J, Geissler A, Eichenberger A, Morant R. Breast cancer patients enrolled in the Swiss mammography screening program "donna" demonstrate prolonged survival. Breast Cancer Res 2024; 26:84. [PMID: 38802897 PMCID: PMC11131279 DOI: 10.1186/s13058-024-01841-6] [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: 01/22/2024] [Accepted: 05/16/2024] [Indexed: 05/29/2024] Open
Abstract
STUDY GOAL We compared the survival rates of women with breast cancer (BC) detected within versus outside the mammography screening program (MSP) "donna". METHODS We merged data from the MSP with the data from corresponding cancer registries to categorize BC cases as within MSP (screen-detected and interval carcinomas) and outside the MSP. We analyzed the tumor stage distribution, tumor characteristics and the survival of the women. We further estimated hazard ratios using Cox-regressions to account for different characteristics between groups and corrected the survival rates for lead-time bias. RESULTS We identified 1057 invasive (ICD-10: C50) and in-situ (D05) BC cases within the MSP and 1501 outside the MSP between 2010 and 2019 in the Swiss cantons of St. Gallen and Grisons. BC within the MSP had a higher share of stage I carcinoma (46.5% vs. 33.0%; p < 0.01), a smaller (mean) tumor size (19.1 mm vs. 24.9 mm, p < 0.01), and fewer recurrences and metastases in the follow-up period (6.7% vs. 15.6%, p < 0.01). The 10-year survival rates were 91.4% for women within and 72.1% for women outside the MSP (p < 0.05). Survival difference persisted but decreased when women within the same tumor stage were compared. Lead-time corrected hazard ratios for the MSP accounted for age, tumor size and Ki-67 proliferation index were 0.550 (95% CI 0.389, 0.778; p < 0.01) for overall survival and 0.469 (95% CI 0.294, 0.749; p < 0.01) for BC related survival. CONCLUSION Women participating in the "donna" MSP had a significantly higher overall and BC related survival rate than women outside the program. Detection of BC at an earlier tumor stage only partially explains the observed differences.
Collapse
Affiliation(s)
- David Kuklinski
- Chair of Health Economics, Policy and Management, School of Medicine, University of St. Gallen, St. Jakobstr. 21, 9000, St. Gallen, Switzerland.
| | - Marcel Blum
- Cancer League of Eastern Switzerland, St. Gallen, Switzerland
| | - Jonas Subelack
- Chair of Health Economics, Policy and Management, School of Medicine, University of St. Gallen, St. Jakobstr. 21, 9000, St. Gallen, Switzerland
| | - Alexander Geissler
- Chair of Health Economics, Policy and Management, School of Medicine, University of St. Gallen, St. Jakobstr. 21, 9000, St. Gallen, Switzerland
| | | | - Rudolf Morant
- Cancer League of Eastern Switzerland, St. Gallen, Switzerland
| |
Collapse
|
16
|
Palomba G, Fernicola A, Corte MD, Capuano M, De Palma GD, Aprea G. Artificial intelligence in screening and diagnosis of surgical diseases: A narrative review. AIMS Public Health 2024; 11:557-576. [PMID: 39027395 PMCID: PMC11252578 DOI: 10.3934/publichealth.2024028] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/29/2024] [Accepted: 04/02/2024] [Indexed: 07/20/2024] Open
Abstract
Artificial intelligence (AI) is playing an increasing role in several fields of medicine. It is also gaining popularity among surgeons as a valuable screening and diagnostic tool for many conditions such as benign and malignant colorectal, gastric, thyroid, parathyroid, and breast disorders. In the literature, there is no review that groups together the various application domains of AI when it comes to the screening and diagnosis of main surgical diseases. The aim of this review is to describe the use of AI in these settings. We performed a literature review by searching PubMed, Web of Science, Scopus, and Embase for all studies investigating the role of AI in the surgical setting, published between January 01, 2000, and June 30, 2023. Our focus was on randomized controlled trials (RCTs), meta-analysis, systematic reviews, and observational studies, dealing with large cohorts of patients. We then gathered further relevant studies from the reference list of the selected publications. Based on the studies reviewed, it emerges that AI could strongly enhance the screening efficiency, clinical ability, and diagnostic accuracy for several surgical conditions. Some of the future advantages of this technology include implementing, speeding up, and improving the automaticity with which AI recognizes, differentiates, and classifies the various conditions.
Collapse
Affiliation(s)
- Giuseppe Palomba
- Department of Clinical Medicine and Surgery, University of Naples, “Federico II”, Sergio Pansini 5, 80131, Naples, Italy
| | - Agostino Fernicola
- Department of Clinical Medicine and Surgery, University of Naples, “Federico II”, Sergio Pansini 5, 80131, Naples, Italy
| | - Marcello Della Corte
- Azienda Ospedaliera Universitaria San Giovanni di Dio e Ruggi d'Aragona - OO. RR. Scuola Medica Salernitana, Salerno, Italy
| | - Marianna Capuano
- Department of Clinical Medicine and Surgery, University of Naples, “Federico II”, Sergio Pansini 5, 80131, Naples, Italy
| | - Giovanni Domenico De Palma
- Department of Clinical Medicine and Surgery, University of Naples, “Federico II”, Sergio Pansini 5, 80131, Naples, Italy
| | - Giovanni Aprea
- Department of Clinical Medicine and Surgery, University of Naples, “Federico II”, Sergio Pansini 5, 80131, Naples, Italy
| |
Collapse
|
17
|
Jin Y, Wang L, Jin C, Zhang N, Shimizu S, Xiao W, Guo C, Liu X, Si H. A Novel Inhibitor of Poly( ADP- Ribose) Polymerase-1 Inhibits Proliferation of a BRCA-Deficient Breast Cancer Cell Line via the DNA Damage- Activated cGAS-STING Pathway. Chem Res Toxicol 2024; 37:561-570. [PMID: 38534178 DOI: 10.1021/acs.chemrestox.3c00343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
Loss-of-function mutations in the Breast Cancer Susceptibility Gene (BRCA1 and BRCA2) are often detected in patients with breast cancer. Poly(ADP-ribose) polymerase-1 (PARP1) plays a key role in the repair of DNA strand breaks, and PARP inhibitors have been shown to induce highly selective killing of BRCA1/2-deficient tumor cells, a mechanism termed synthetic lethality. In our previous study, a novel PARP1 inhibitor─(E)-2-(2,3-dibromo-4,5-dimethoxybenzylidene)-N-(4-fluorophenyl) hydrazine-1-carbothioamide (4F-DDC)─was synthesized, which significantly inhibited PARP1 activity with an IC50 value of 82 ± 9 nM. The current study aimed to explore the mechanism(s) underlying the antitumor activity of 4F-DDC under in vivo and in vitro conditions. 4F-DDC was found to selectively inhibit the proliferation of BRCA mutant cells, with highly potent effects on HCC-1937 (BRCA1-/-) cells. Furthermore, 4F-DDC was found to induce apoptosis and G2/M cell cycle arrest in HCC-1937 cells. Interestingly, immunofluorescence and Western blot results showed that 4F-DDC induced DNA double strand breaks and further activated the cGAS-STING pathway in HCC-1937 cells. In vivo analysis results revealed that 4F-DDC inhibited the growth of HCC-1937-derived tumor xenografts, possibly via the induction of DNA damage and activation of the cGAS-STING pathway. In summary, the current study provides a new perspective on the antitumor mechanism of PARP inhibitors and showcases the therapeutic potential of 4F-DDC in the treatment of breast cancer.
Collapse
Affiliation(s)
- Yonglong Jin
- Department of Radiotherapy, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
- School of Public Health, Qingdao University, Qingdao 266071, China
| | - Lijie Wang
- Department of Radiotherapy, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Chengxue Jin
- Department of Molecular Craniofacial Embryology and Oral Histology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Bunkyo-ku, Tokyo 113-8510, Japan
- Department of Oral, Plastic and Aesthetic Surgery, Hospital of Stomatology, Jilin University, Changchun, Jilin 130021, China
| | - Na Zhang
- Department of Radiotherapy, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Shosei Shimizu
- Department of Radiotherapy, Yizhou Tumor Hospital, Zhuozhou 072750, China
- Department of Radiotherapy, University of Tsukuba Hospital, Tsukuba 305-8576, Japan
| | - Wenjing Xiao
- Department of Radiotherapy, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Chuanlong Guo
- Department of Pharmacy, Qingdao University of Science and Technology, Qingdao 266041, China
| | - Xiguang Liu
- Department of Radiotherapy, The Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Hongzong Si
- School of Public Health, Qingdao University, Qingdao 266071, China
| |
Collapse
|
18
|
Giannoula A, Comas M, Castells X, Estupiñán-Romero F, Bernal-Delgado E, Sanz F, Sala M. Exploring long-term breast cancer survivors' care trajectories using dynamic time warping-based unsupervised clustering. J Am Med Inform Assoc 2024; 31:820-831. [PMID: 38193340 PMCID: PMC10990519 DOI: 10.1093/jamia/ocad251] [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: 09/08/2023] [Revised: 11/10/2023] [Accepted: 12/18/2023] [Indexed: 01/10/2024] Open
Abstract
OBJECTIVES Long-term breast cancer survivors (BCS) constitute a complex group of patients, whose number is estimated to continue rising, such that, a dedicated long-term clinical follow-up is necessary. MATERIALS AND METHODS A dynamic time warping-based unsupervised clustering methodology is presented in this article for the identification of temporal patterns in the care trajectories of 6214 female BCS of a large longitudinal retrospective cohort of Spain. The extracted care-transition patterns are graphically represented using directed network diagrams with aggregated patient and time information. A control group consisting of 12 412 females without breast cancer is also used for comparison. RESULTS The use of radiology and hospital admission are explored as patterns of special interest. In the generated networks, a more intense and complex use of certain healthcare services (eg, radiology, outpatient care, hospital admission) is shown and quantified for the BCS. Higher mortality rates and numbers of comorbidities are observed in various transitions and compared with non-breast cancer. It is also demonstrated how a wealth of patient and time information can be revealed from individual service transitions. DISCUSSION The presented methodology permits the identification and descriptive visualization of temporal patterns of the usage of healthcare services by the BCS, that otherwise would remain hidden in the trajectories. CONCLUSION The results could provide the basis for better understanding the BCS' circulation through the health system, with a view to more efficiently predicting their forthcoming needs and thus designing more effective personalized survivorship care plans.
Collapse
Affiliation(s)
- Alexia Giannoula
- Epidemiology and Evaluation Department, Hospital del Mar Research Institute (IMIM), Barcelona, 08003, Spain
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences (MELIS), Hospital del Mar Research Institute (IMIM), Universitat Pompeu Fabra, Barcelona, Spain
- RICAPPS Red de Investigación en Cronicidad, Atención Primaria Y Promoción de la Salud, Spain
| | - Mercè Comas
- Epidemiology and Evaluation Department, Hospital del Mar Research Institute (IMIM), Barcelona, 08003, Spain
- RICAPPS Red de Investigación en Cronicidad, Atención Primaria Y Promoción de la Salud, Spain
| | - Xavier Castells
- Epidemiology and Evaluation Department, Hospital del Mar Research Institute (IMIM), Barcelona, 08003, Spain
- RICAPPS Red de Investigación en Cronicidad, Atención Primaria Y Promoción de la Salud, Spain
| | - Francisco Estupiñán-Romero
- RICAPPS Red de Investigación en Cronicidad, Atención Primaria Y Promoción de la Salud, Spain
- Data Science for Health Services and Policy Research Group, Institute for Health Sciences (IACS), Zaragoza, Aragon, 50009, Spain
| | - Enrique Bernal-Delgado
- RICAPPS Red de Investigación en Cronicidad, Atención Primaria Y Promoción de la Salud, Spain
- Data Science for Health Services and Policy Research Group, Institute for Health Sciences (IACS), Zaragoza, Aragon, 50009, Spain
| | - Ferran Sanz
- Epidemiology and Evaluation Department, Hospital del Mar Research Institute (IMIM), Barcelona, 08003, Spain
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences (MELIS), Hospital del Mar Research Institute (IMIM), Universitat Pompeu Fabra, Barcelona, Spain
| | - Maria Sala
- Epidemiology and Evaluation Department, Hospital del Mar Research Institute (IMIM), Barcelona, 08003, Spain
- RICAPPS Red de Investigación en Cronicidad, Atención Primaria Y Promoción de la Salud, Spain
| |
Collapse
|
19
|
Li Y, Yang S, Qi L, Li Y, Wang X. Identification of a Group of Therapeutic Targets and Prognostic Biomarker for Triple Negative Breast Cancer. Adv Ther 2024; 41:1621-1636. [PMID: 38421558 DOI: 10.1007/s12325-024-02806-z] [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: 11/10/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024]
Abstract
INTRODUCTION Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Mining differentially expressed genes of TNBC is helpful to explore new therapeutic targets. This study aimed to investigate diagnostic biomarker genes in TNBC compared to normal tissue. Additionally, we explored the functions and prognostic value of these key genes as well as potential targeted drugs that could affect these genes. METHODS Differential gene expression analysis was conducted using the R software with data from the Gene Expression Omnibus (GEO) database. Then, the identified differentially expressed genes (DEGs) were used to construct a protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The mRNA expression levels of key genes were analyzed using the UALCAN database with data from The Cancer Genome Atlas (TCGA). Enrichment and survival analyses were performed using R software. In addition, potential compounds showing sensitivity to key genes were identified by gene set cancer analysis (GSCA). RESULTS Compared with normal tissues, a total of 203 DEGs were upregulated in TNBC. These DEGs participated in various biological processes including nuclear division, microtubule binding, cell cycle, and the p53 signaling pathway. Through the PPI network analysis, ten key genes were identified, among which four genes showed significant correlation with poor progression-free interval (PFI) in patients with TNBC. Moreover, the four survival-related genes were found to act as sensitive therapeutic targets. CONCLUSION The identified four key genes were considered new biomarkers for diagnosis and prognosis and also potential therapeutic targets for TNBC.
Collapse
Affiliation(s)
- Yan Li
- Phase I Clinical Trial Center, Beijing Shijitan Hospital, Capital Medical University, No. 10 Tieyi Road, Haidian District, Beijing, 100038, China
| | - Shengjie Yang
- Phase I Clinical Trial Center, Beijing Shijitan Hospital, Capital Medical University, No. 10 Tieyi Road, Haidian District, Beijing, 100038, China
| | - Lu Qi
- Phase I Clinical Trial Center, Beijing Shijitan Hospital, Capital Medical University, No. 10 Tieyi Road, Haidian District, Beijing, 100038, China
| | - Yinjuan Li
- Phase I Clinical Trial Center, Beijing Shijitan Hospital, Capital Medical University, No. 10 Tieyi Road, Haidian District, Beijing, 100038, China
| | - Xinghe Wang
- Phase I Clinical Trial Center, Beijing Shijitan Hospital, Capital Medical University, No. 10 Tieyi Road, Haidian District, Beijing, 100038, China.
| |
Collapse
|
20
|
de Munck L, Eijkelboom AH, Otten JDM, Broeders MJM, Siesling S. Method of primary breast cancer detection and the disease-free interval, adjusting for lead time. J Natl Cancer Inst 2024; 116:370-378. [PMID: 37935443 PMCID: PMC10919328 DOI: 10.1093/jnci/djad230] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/18/2023] [Accepted: 10/25/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND Little is known about the impact of screen-detected breast cancer compared with clinically detected breast cancer on the disease-free interval (ie, free from locoregional recurrences, distant metastasis, contralateral breast cancer). Moreover, it is thought that most studies overestimate the beneficial effect of screening, as they do not adjust for lead time. We investigated the association between method of breast cancer detection and disease-free interval, taking lead time into account. METHODS Women aged 50-76 years, diagnosed with breast cancer between 2005 and 2008 were selected from the Netherlands Cancer Registry. Women diagnosed in 2005 were divided into screen-detected and clinically detected cancer and had a follow-up of 10 years (2005 cohort). Women diagnosed in 2006-2008 were divided into screen-detected, interval, and nonscreen-related cancer and had a follow-up of 5 years (2006-2008 cohort). A previously published method was used to adjust for lead time. Analyses were repeated correcting for confounding variables instead of lead time. RESULTS The 2005 cohort included 6215 women. Women with screen-detected cancer had an improved disease-free interval compared with women with clinically detected cancer (hazard ratio [HR] = 0.77, 95% confidence interval [CI] = 0.68 to 0.87). The 2006-2008 cohort included 15 176 women. Women with screen-detected or interval cancer had an improved disease-free interval compared with women with nonscreen-related cancer (HR = 0.76, 95% CI = 0.66 to 0.88; HR = 0.88, 95% CI = 0.78 to 0.99, respectively). Correcting for confounders instead of lead time did not change associations. CONCLUSION Women with screen-detected cancer had an improved disease-free interval compared with women with a nonscreen-related or clinically detected cancer, after correction for lead time.
Collapse
Affiliation(s)
- Linda de Munck
- Department of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, the Netherlands
| | - Anouk H Eijkelboom
- Department of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, the Netherlands
- Department of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, the Netherlands
| | - Johannes D M Otten
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Mireille J M Broeders
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
- Dutch Expert Centre for Screening, Nijmegen, the Netherlands
| | - Sabine Siesling
- Department of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, the Netherlands
- Department of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, the Netherlands
| |
Collapse
|
21
|
Springer R, Erroba J, O'Malley JP, Huguet N. Differences in up-to-date colorectal and cervical cancer screening rates by ethnicity and preferred language: An analysis across patient-, clinic-, and area-level data sources. SSM Popul Health 2024; 25:101612. [PMID: 38322786 PMCID: PMC10844668 DOI: 10.1016/j.ssmph.2024.101612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 02/08/2024] Open
Abstract
Research objective There is interest in using clinic- and area-level data to inform cancer control, but it is unclear what value these sources may add in combination with patient-level data sources. This study aimed to investigate associations of up-to-date colorectal and cervical cancer screenings at community health centers (CHCs) with ethnicity and language variables at patient-, clinic-, and area-levels, while exploring whether patient-level associations differed based on clinic-level patient language and ethnicity distributions. Study design This was a cross-sectional study using data from multiple sources, including electronic health records, clinic patient panel data, and area-level demographic data. The study sample included English-preferring Hispanic, Spanish-preferring Hispanic, English-preferring non-Hispanic, and non-English-preferring non-Hispanic patients eligible for either colorectal cancer (N = 98,985) or cervical cancer (N = 129,611) screenings in 2019 from 130 CHCs in the OCHIN network in CA, OR, and WA. Population studied The study population consisted of adults aged 45+ eligible for colorectal cancer screening and adults with a cervix aged 25-65 eligible for cervical cancer screening. Principal findings Spanish-preferring Hispanic patients were significantly more likely to be up-to-date with colorectal and cervical cancer screenings than other groups. Patients seen at clinics with higher concentrations of Spanish-preferring Hispanics were significantly more likely to be up-to-date, as were individuals residing in areas with higher percentages of Spanish-speaking residents. Differential associations between patient ethnicity and language and up-to-date colorectal cancer screenings were greater among patients seen at clinics with higher concentrations of Spanish-preferring Hispanics. Conclusions The findings highlight that Spanish-speaking Hispanics seen in CHCs have higher rates of up-to-date cervical and colorectal cancer screenings than other groups and that this relationship is stronger at clinics with higher percentages of Spanish-preferring Hispanic patients. Our findings suggest area-level variables are not good substitutions for patient-level data, but variables at the clinic patient panel-level are more informative.
Collapse
Affiliation(s)
- Rachel Springer
- Department of Family Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Jeremy Erroba
- Department of Family Medicine, Oregon Health and Science University, Portland, OR, USA
| | | | - Nathalie Huguet
- Department of Family Medicine, Oregon Health and Science University, Portland, OR, USA
| |
Collapse
|
22
|
Rodriguez J, Grassmann F, Xiao Q, Eriksson M, Mao X, Bajalica-Lagercrantz S, Hall P, Czene K. Investigation of Genetic Alterations Associated With Interval Breast Cancer. JAMA Oncol 2024; 10:372-379. [PMID: 38270937 PMCID: PMC10811589 DOI: 10.1001/jamaoncol.2023.6287] [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: 07/19/2023] [Accepted: 10/16/2023] [Indexed: 01/26/2024]
Abstract
Importance Breast cancers (BCs) diagnosed between 2 screening examinations are called interval cancers (ICs), and they have worse clinicopathological characteristics and poorer prognosis than screen-detected cancers (SDCs). However, the association of rare germline genetic variants with IC have not been studied. Objective To evaluate whether rare germline deleterious protein-truncating variants (PTVs) can be applied to discriminate between IC and SDC while considering mammographic density. Design, Setting, and Participants This population-based genetic association study was based on women aged 40 to 76 years who were attending mammographic screening in Sweden. All women with a diagnosis of BC between January 2001 and January 2016 were included, together with age-matched controls. Patients with BC were followed up for survival until 2021. Statistical analysis was performed from September 2021 to December 2022. Exposure Germline PTVs in 34 BC susceptibility genes as analyzed by targeted sequencing. Main Outcomes and Measures Odds ratios (ORs) were used to compare IC with SDC using logistic regression. Hazard ratios were used to investigate BC-specific survival using Cox regression. Results All 4121 patients with BC (IC, n = 1229; SDC, n = 2892) were female, with a mean (SD) age of 55.5 (7.1) years. There were 5631 age-matched controls. The PTVs of the ATM, BRCA1, BRCA2, CHEK2, and PALB2 genes were more common in patients with IC compared with SDC (OR, 1.48; 95% CI, 1.06-2.05). This association was primarily influenced by BRCA1/2 and PALB2 variants. A family history of BC together with PTVs of any of these genes synergistically increased the probability of receiving a diagnosis of IC rather than SDC (OR, 3.95; 95% CI, 1.97-7.92). Furthermore, 10-year BC-specific survival revealed that if a patient received a diagnosis of an IC, carriers of PTVs in any of these 5 genes had significantly worse survival compared with patients not carrying any of them (hazard ratio, 2.04; 95% CI, 1.06-3.92). All of these associations were further pronounced in a subset of patients with IC who had a low mammographic density at prior screening examination. Conclusions and Relevance The results of this study may be helpful in future optimizations of screening programs that aim to lower mortality as well as the clinical treatment of patients with BC.
Collapse
Affiliation(s)
- Juan Rodriguez
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Health and Medical University, Potsdam, Germany
| | - Qingyang Xiao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Xinhe Mao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
23
|
Jiang Y, Liu J, Chen L, Qian Z, Zhang Y. A promising target for breast cancer: B7-H3. BMC Cancer 2024; 24:182. [PMID: 38326735 PMCID: PMC10848367 DOI: 10.1186/s12885-024-11933-3] [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: 11/22/2023] [Accepted: 01/29/2024] [Indexed: 02/09/2024] Open
Abstract
Breast cancer (BC) is the second-leading factor of mortality for women globally and is brought on by a variety of genetic and environmental causes. The conventional treatments for this disease have limitations, making it difficult to improve the lifespan of breast cancer patients. As a result, extensive research has been conducted over the past decade to find innovative solutions to these challenges. Targeting of the antitumor immune response through the immunomodulatory checkpoint protein B7 family has revolutionized cancer treatment and led to intermittent patient responses. B7-H3 has recently received attention because of its significant demodulation and its immunomodulatory effects in many cancers. Uncontrolled B7-H3 expression and a bad outlook are strongly associated, according to a substantial body of cancer research. Numerous studies have shown that BC has significant B7-H3 expression, and B7-H3 induces an immune evasion phenotype, consequently enhancing the survival, proliferation, metastasis, and drug resistance of BC cells. Thus, an innovative target for immunotherapy against BC may be the B7-H3 checkpoint.In this review, we discuss the structure and regulation of B7-H3 and its double costimulatory/coinhibitory function within the framework of cancer and normal physiology. Then we expound the malignant behavior of B7-H3 in BC and its role in the tumor microenvironment (TME) and finally focus on targeted drugs against B7-H3 that have opened new therapeutic opportunities in BC.
Collapse
Affiliation(s)
- Ying Jiang
- Department of Oncology, Wuxi Maternal and Child Health Care Hospital, Women's Hospital of Jiangnan University, Jiangnan University, Wuxi, 214002, China
| | - Jiayu Liu
- Department of Oncology, Wuxi Maternal and Child Health Care Hospital, Women's Hospital of Jiangnan University, Jiangnan University, Wuxi, 214002, China
| | - Lingyan Chen
- Wuxi Maternal and Child Health Hospital, Nanjing Medical University, Wuxi, 214000, China
| | - Zhiwen Qian
- Wuxi Maternal and Child Health Hospital, Nanjing Medical University, Wuxi, 214000, China
| | - Yan Zhang
- Department of Oncology, Wuxi Maternal and Child Health Care Hospital, Women's Hospital of Jiangnan University, Jiangnan University, Wuxi, 214002, China.
- Wuxi Maternal and Child Health Hospital, Nanjing Medical University, Wuxi, 214000, China.
| |
Collapse
|
24
|
Jayasekera J, Stein S, Wilson OWA, Wojcik KM, Kamil D, Røssell EL, Abraham LA, O'Meara ES, Schoenborn NL, Schechter CB, Mandelblatt JS, Schonberg MA, Stout NK. Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study. J Gen Intern Med 2024; 39:428-439. [PMID: 38010458 PMCID: PMC10897118 DOI: 10.1007/s11606-023-08518-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 10/27/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. OBJECTIVE To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. DESIGN, SETTING, AND PARTICIPANTS We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). MAIN OUTCOMES AND MEASURES Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. RESULTS Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29-31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. CONCLUSIONS Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.
Collapse
Affiliation(s)
- Jinani Jayasekera
- Health Equity and Decision Sciences Research Laboratory, National Institute on Minority Health and Health Disparities (NIMHD) Intramural Research Program (IRP), National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Sarah Stein
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Oliver W A Wilson
- Health Equity and Decision Sciences Research Laboratory, National Institute on Minority Health and Health Disparities (NIMHD) Intramural Research Program (IRP), National Institutes of Health, Bethesda, MD, 20892, USA
| | - Kaitlyn M Wojcik
- Health Equity and Decision Sciences Research Laboratory, National Institute on Minority Health and Health Disparities (NIMHD) Intramural Research Program (IRP), National Institutes of Health, Bethesda, MD, 20892, USA
| | - Dalya Kamil
- Health Equity and Decision Sciences Research Laboratory, National Institute on Minority Health and Health Disparities (NIMHD) Intramural Research Program (IRP), National Institutes of Health, Bethesda, MD, 20892, USA
| | | | - Linn A Abraham
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Ellen S O'Meara
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Nancy Li Schoenborn
- Division of Geriatric Medicine and Gerontology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Clyde B Schechter
- Departments of Family and Social Medicine and Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jeanne S Mandelblatt
- Georgetown Lombardi Institute for Cancer and Aging Research and the Cancer Prevention and Control Program at the Georgetown Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University Medical Center, Washington, DC, USA
| | - Mara A Schonberg
- Division of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Natasha K Stout
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| |
Collapse
|
25
|
Caswell-Jin JL, Sun LP, Munoz D, Lu Y, Li Y, Huang H, Hampton JM, Song J, Jayasekera J, Schechter C, Alagoz O, Stout NK, Trentham-Dietz A, Lee SJ, Huang X, Mandelblatt JS, Berry DA, Kurian AW, Plevritis SK. Analysis of Breast Cancer Mortality in the US-1975 to 2019. JAMA 2024; 331:233-241. [PMID: 38227031 PMCID: PMC10792466 DOI: 10.1001/jama.2023.25881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 11/27/2023] [Indexed: 01/17/2024]
Abstract
Importance Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. Objective To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. Design, Setting, and Participants Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. Exposures Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. Main Outcomes and Measures Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. Results The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). Conclusions and Relevance According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction.
Collapse
Affiliation(s)
| | - Liyang P. Sun
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Diego Munoz
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Ying Lu
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Yisheng Li
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
| | | | - John M. Hampton
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin–Madison School of Medicine and Public Health, Madison
| | - Juhee Song
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
| | - Jinani Jayasekera
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland
| | - Clyde Schechter
- Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, New York
| | - Oguzhan Alagoz
- Department of Industrial and Systems Engineering, University of Wisconsin–Madison, Madison
| | - Natasha K. Stout
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts
| | - Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin–Madison School of Medicine and Public Health, Madison
| | - Sandra J. Lee
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Data Sciences, Harvard Medical School, Boston, Massachusetts
| | - Xuelin Huang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
| | - Jeanne S. Mandelblatt
- Department of Oncology, Georgetown University Medical Center, Georgetown Lombardi Comprehensive Cancer Center, Washington, DC
- Georgetown-Lombardi Institute for Cancer and Aging, Washington, DC
| | - Donald A. Berry
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
| | - Allison W. Kurian
- Department of Medicine, Stanford University School of Medicine, Stanford, California
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
| | - Sylvia K. Plevritis
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
- Department of Radiology, Stanford University School of Medicine, Stanford, California
| |
Collapse
|
26
|
Hadar M, Friger M, Ariad S, Koretz M, Delgado B, Tokar M, Bayme M, Agassi R, Rosenthal M, Dyomin V, Belochitski O, Amir N, Libson S, Meirovitz A, Lazarev I, Abu-Ghanem S, Geffen DB. Stage I Breast Cancer in the Modern Era: A Retrospective Cohort Study of 328 Patients Diagnosed from 2002 to 2006 with a 14-Year Median Follow-Up. Oncology 2024; 102:663-675. [PMID: 38185110 DOI: 10.1159/000536119] [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: 11/17/2023] [Accepted: 12/26/2023] [Indexed: 01/09/2024]
Abstract
INTRODUCTION This study aimed to evaluate the long-term outcomes of stage I breast cancer (BC) patients diagnosed during the current era of screening mammography, immunohistochemistry receptor testing, and systemic adjuvant therapy. METHODS A retrospective cohort study was conducted on 328 stage I BC patients treated consecutively in a single referral center with a follow-up period of at least 12 years. The primary endpoints were invasive disease-free survival (IDFS) and overall survival (OS). The influence of tumor size, grade, and subtype on the outcomes was analyzed. RESULTS Most patients were treated by lumpectomy, sentinel node biopsy, and adjuvant endocrine therapy, and most (82%) were of subtype luminal A. Adjuvant chemotherapy was administered to 25.6% of our cohort. Only 24 patients underwent gene expression testing, which was introduced toward the end of the study period. Mean IDFS was 14.64 years, with a 15-year IDFS of 75.6%. Mean OS was 15.28 years with a 15-year OS of 74.9%. In a Cox multivariate analysis, no clinical or pathologic variable impacted on OS and only tumor size (<1 cm vs. 1-2 cm) impacted significantly on IDFS. During follow-up, 20.1% of the cohort developed second primary cancers, including BC. The median time to diagnosis of a second BC was 6.49 years. CONCLUSION The study results emphasize the importance of long-term follow-up and screening for subsequent malignancies of patients with stage I BC and support the need for using prognostic and predictive indicators beyond the routine clinicopathological characteristics in luminal A patients.
Collapse
Affiliation(s)
- Maayan Hadar
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Michael Friger
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Epidemiology, Biostatistics and Community Health, Beer Sheva, Israel
| | - Samuel Ariad
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Michael Koretz
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Division of Surgery and the Eshkol Breast Center, Soroka University Medical Center, Beer Sheva, Israel
| | - Bertha Delgado
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Pathology, Soroka University Medical Center, Beer Sheva, Israel
| | - Margarita Tokar
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Michael Bayme
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Division of Surgery and the Eshkol Breast Center, Soroka University Medical Center, Beer Sheva, Israel
| | - Ravit Agassi
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Division of Surgery and the Eshkol Breast Center, Soroka University Medical Center, Beer Sheva, Israel
| | - Maia Rosenthal
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Imaging and the Eshkol Breast Center, Soroka University Medical Center, Beer Sheva, Israel
| | - Victor Dyomin
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Pathology, Soroka University Medical Center, Beer Sheva, Israel
| | - Olga Belochitski
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Noa Amir
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Shai Libson
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Division of Surgery and the Eshkol Breast Center, Soroka University Medical Center, Beer Sheva, Israel
| | - Amichay Meirovitz
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Irena Lazarev
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - Sara Abu-Ghanem
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| | - David B Geffen
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Department of Oncology, The Legacy Heritage Oncology Center and the Dr. Larry Norton Institute, Soroka University Medical Center, Beer Sheva, Israel
| |
Collapse
|
27
|
Uematsu T. Rethinking screening mammography in Japan: next-generation breast cancer screening through breast awareness and supplemental ultrasonography. Breast Cancer 2024; 31:24-30. [PMID: 37823977 PMCID: PMC10764506 DOI: 10.1007/s12282-023-01506-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: 08/03/2023] [Accepted: 09/16/2023] [Indexed: 10/13/2023]
Abstract
Breast cancer mortality has not been reduced in Japan despite more than 20 years of population-based screening mammography. Screening mammography might not be suitable for Japanese women who often have dense breasts, thus decreasing mammography sensitivity because of masking. The J-START study showed that breast ultrasonography increases the sensitivity and the detection rate for early invasive cancers and lowers the rate of interval cancers for Japanese women in their 40 s. Breast awareness and breast cancer survival are directly correlated; however, breast awareness is not widely known in Japan. Next-generation breast cancer screening in Japan should consist of breast awareness campaigns for improving breast cancer literacy and supplemental breast ultrasonography to address the problem of false-negative mammograms attributable to dense breasts.
Collapse
Affiliation(s)
- Takayoshi Uematsu
- Department of Breast Imaging and Breast Intervention Radiology, Shizuoka Cancer Center Hospital, 1007 Shimonagakubo, Nagaizumi, Shizuoka, 411-8777, Japan.
| |
Collapse
|
28
|
Trentham-Dietz A, Corley DA, Del Vecchio NJ, Greenlee RT, Haas JS, Hubbard RA, Hughes AE, Kim JJ, Kobrin S, Li CI, Meza R, Neslund-Dudas CM, Tiro JA. Data gaps and opportunities for modeling cancer health equity. J Natl Cancer Inst Monogr 2023; 2023:246-254. [PMID: 37947335 PMCID: PMC11009506 DOI: 10.1093/jncimonographs/lgad025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/12/2023] [Accepted: 08/15/2023] [Indexed: 11/12/2023] Open
Abstract
Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change.
Collapse
Affiliation(s)
- Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Natalie J Del Vecchio
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Jennifer S Haas
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Rebecca A Hubbard
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy E Hughes
- Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jane J Kim
- Department of Health Policy and Management, Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sarah Kobrin
- Healthcare Delivery Research Program, Division of Cancer Control & Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Christopher I Li
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Rafael Meza
- Department of Integrative Oncology, British Columbia (BC) Cancer Research Institute, Vancouver, BC, Canada
| | | | - Jasmin A Tiro
- Department of Public Health Sciences, University of Chicago Biological Sciences Division, and University of Chicago Medicine Comprehensive Cancer Center, Chicago, IL, USA
| |
Collapse
|
29
|
Mandelblatt J, Meza R, Trentham-Dietz A, Heckman-Stoddard B, Feuer E. Using simulation modeling to guide policy to reduce disparities and achieve equity in cancer outcomes: state of the science and a road map for the future. J Natl Cancer Inst Monogr 2023; 2023:159-166. [PMID: 37947330 PMCID: PMC11009490 DOI: 10.1093/jncimonographs/lgad033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 09/10/2023] [Indexed: 11/12/2023] Open
Affiliation(s)
- Jeanne Mandelblatt
- Department of Oncology, Georgetown University Medical Center, Washington, DC, USA
- Georgetown Lombardi Comprehensive Cancer Center, Cancer Prevention and Control Program, Washington, DC, USA
- Georgetown Lombardi Institute for Cancer and Aging Research, Georgetown University Medical Center, Washington, DC, USA
| | - Rafael Meza
- Department of Integrative Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada
| | - Amy Trentham-Dietz
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Carbone Cancer Center, University of Wisconsin–Madison, Madison, WI, USA
| | - Brandy Heckman-Stoddard
- Breast and Gynecologic Cancer Research Program, Division of Cancer Prevention, National Cancer Institute at the National Institutes of Health, Bethesda, MD, USA
| | - Eric Feuer
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute at the National Institutes of Health, Bethesda, MD, USA
| |
Collapse
|
30
|
Mandelblatt JS, Schechter CB, Stout NK, Huang H, Stein S, Hunter Chapman C, Trentham-Dietz A, Jayasekera J, Gangnon RE, Hampton JM, Abraham L, O’Meara ES, Sheppard VB, Lee SJ. Population simulation modeling of disparities in US breast cancer mortality. J Natl Cancer Inst Monogr 2023; 2023:178-187. [PMID: 37947337 PMCID: PMC10637022 DOI: 10.1093/jncimonographs/lgad023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/13/2023] [Accepted: 07/31/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence. METHODS Three Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy. RESULTS Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness. CONCLUSION Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities.
Collapse
Affiliation(s)
- Jeanne S Mandelblatt
- Department of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program at Georgetown Lombardi Comprehensive Cancer Center, Washington, DC, USA
| | - Clyde B Schechter
- Departments of Family and Social Medicine and of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Natasha K Stout
- Department of Population Sciences, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Hui Huang
- Department of Data Science, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Sarah Stein
- Department of Population Sciences, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Christina Hunter Chapman
- Department of Radiation Oncology, Section of Health Services Research, Baylor College of Medicine and Health Policy, Quality and Informatics Program at the Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Jinani Jayasekera
- Health Equity and Decision Sciences Research Lab, National Institute on Minority Health and Health Disparities, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Ronald E Gangnon
- Departments of Population Health Sciences and of Biostatistics and Medical Informatics and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA
| | - John M Hampton
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Linn Abraham
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Ellen S O’Meara
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Vanessa B Sheppard
- Department of Health Behavior and Policy and Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Sandra J Lee
- Department of Data Science, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| |
Collapse
|
31
|
Ryser MD, Greenwald MA, Sorribes IC, King LM, Hall A, Geradts J, Weaver DL, Mallo D, Holloway S, Monyak D, Gumbert G, Vaez-Ghaemi S, Wu E, Murgas K, Grimm LJ, Maley CC, Marks JR, Shibata D, Hwang ES. Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.01.560370. [PMID: 37873488 PMCID: PMC10592867 DOI: 10.1101/2023.10.01.560370] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.
Collapse
Affiliation(s)
- Marc D. Ryser
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
- Department of Mathematics, Duke University, Durham, NC, USA
| | | | | | - Lorraine M. King
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Allison Hall
- Department of Pathology, Duke University School of Medicine, Durham, NC, USA
| | - Joseph Geradts
- Department of Pathology, East Carolina University School of Medicine, Greenville, NC, USA
| | - Donald L. Weaver
- Larner College of Medicine, University of Vermont and UVM Cancer Center, Burlington, VT, USA
| | - Diego Mallo
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Shannon Holloway
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Daniel Monyak
- Trinity College of Arts and Sciences, Duke University, Durham, NC
| | - Graham Gumbert
- Trinity College of Arts and Sciences, Duke University, Durham, NC
| | | | - Ethan Wu
- Trinity College of Arts and Sciences, Duke University, Durham, NC
| | - Kevin Murgas
- Department of Biomedical Informatics, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Lars J. Grimm
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Carlo C. Maley
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Jeffrey R. Marks
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Darryl Shibata
- Department of Pathology, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - E. Shelley Hwang
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| |
Collapse
|
32
|
Liu L, Kawashima M, Sugimoto M, Sonomura K, Pu F, Li W, Takeda M, Goto T, Kawaguchi K, Sato T, Toi M. Discovery of lipid profiles in plasma-derived extracellular vesicles as biomarkers for breast cancer diagnosis. Cancer Sci 2023; 114:4020-4031. [PMID: 37608343 PMCID: PMC10551607 DOI: 10.1111/cas.15935] [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: 02/24/2023] [Revised: 07/11/2023] [Accepted: 08/06/2023] [Indexed: 08/24/2023] Open
Abstract
Lipids are a major component of extracellular vesicles; however, their significance in tumorigenesis and progression has not been well elucidated. As we previously found that lipid profiles drastically changed in breast tumors upon progression, we hypothesized that lipid profiles of plasma-derived extracellular vesicles could be utilized as breast cancer biomarkers. Here, we adopted modified sucrose cushion ultracentrifugation to isolate plasma-derived extracellular vesicles from breast cancer (n = 105), benign (n = 11), and healthy individuals (n = 43) in two independent cohorts (n = 126 and n = 33) and conducted targeted lipidomic analysis. We established a breast cancer diagnostic model comprising three lipids that showed favorable performance with the area under the receiver operating characteristic curve of 0.759, 0.743, and 0.804 in the training, internal validation, and external test sets, respectively. Moreover, we identified several lipids that could effectively discriminate breast cancer progression and subtypes: phosphatidylethanolamines and phosphatidylserines were relatively higher in Stage III, whereas phosphatidylcholines and sphingomyelins were higher in Stage IV; phosphatidylcholines and ceramides were correspondingly concentrated in HER2-positive patients, while lysophosphatidylcholines and polyunsaturated triglycerides were concentrated in the triple-negative breast cancer subtype. Lipid profiling of plasma-derived extracellular vesicles is a non-invasive and promising approach for diagnosing, staging, and subtyping breast cancer.
Collapse
Affiliation(s)
- Lin Liu
- Department of Breast Surgery, Graduate School of MedicineKyoto UniversityKyotoJapan
| | - Masahiro Kawashima
- Department of Breast Surgery, Graduate School of MedicineKyoto UniversityKyotoJapan
| | | | - Kazuhiro Sonomura
- Center for Genomic Medicine, Graduate School of MedicineKyoto UniversityKyotoJapan
- Life Science Research Center, Technology Research LaboratoryShimadzu CorporationKyotoJapan
| | - Fengling Pu
- Department of Breast Surgery, Graduate School of MedicineKyoto UniversityKyotoJapan
| | - Wei Li
- Department of Breast Surgery, Graduate School of MedicineKyoto UniversityKyotoJapan
| | - Masashi Takeda
- Department of Urology, Graduate School of MedicineKyoto UniversityKyotoJapan
| | - Takayuki Goto
- Department of Urology, Graduate School of MedicineKyoto UniversityKyotoJapan
| | - Kosuke Kawaguchi
- Department of Breast Surgery, Graduate School of MedicineKyoto UniversityKyotoJapan
| | - Taka‐Aki Sato
- Life Science Research Center, Technology Research LaboratoryShimadzu CorporationKyotoJapan
| | - Masakazu Toi
- Department of Breast Surgery, Graduate School of MedicineKyoto UniversityKyotoJapan
| |
Collapse
|
33
|
Schopp JG, Polat DS, Arjmandi F, Hayes JC, Ahn RW, Sullivan K, Sahoo S, Porembka JH. Imaging Challenges in Diagnosing Triple-Negative Breast Cancer. Radiographics 2023; 43:e230027. [PMID: 37708071 DOI: 10.1148/rg.230027] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/16/2023]
Abstract
Triple-negative breast cancer (TNBC) refers to a heterogeneous group of carcinomas that have more aggressive biologic features, faster growth, and a propensity for early distant metastasis and recurrence compared with other breast cancer subtypes. Due to the aggressiveness and rapid growth of TNBCs, there are specific imaging challenges associated with their timely and accurate diagnosis. TNBCs commonly manifest initially as circumscribed masses and therefore lack the typical features of a primary breast malignancy, such as irregular shape, spiculated margins, and desmoplastic reaction. Given the potential for misinterpretation, review of the multimodality imaging appearances of TNBCs is important for guiding the radiologist in distinguishing TNBCs from benign conditions. Rather than manifesting as a screening-detected cancer, TNBC typically appears clinically as a palpable area of concern that most commonly corresponds to a discrete mass at mammography, US, and MRI. The combination of circumscribed margins and hypoechoic to anechoic echogenicity may lead to TNBC being misinterpreted as a benign fibroadenoma or cyst. Therefore, careful mammographic and sonographic evaluation with US image optimization can help avoid misinterpretation. Radiologists should recognize the characteristics of TNBCs that can mimic benign entities, as well as the subtle features of TNBCs that should raise concern for malignancy and aid in timely and accurate diagnosis. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
Collapse
Affiliation(s)
- Jennifer G Schopp
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Dogan S Polat
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Firouzeh Arjmandi
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Jody C Hayes
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Richard W Ahn
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Kirbi Sullivan
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Sunati Sahoo
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| | - Jessica H Porembka
- From the Departments of Radiology (J.G.S., D.S.P., F.A., J.C.H, R.W.A., K.S., J.H.P.) and Pathology (S.S.), University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, MC 8896, Dallas, TX 75390-8896
| |
Collapse
|
34
|
Uematsu T, Izumori A, Moon WK. Overcoming the limitations of screening mammography in Japan and Korea: a paradigm shift to personalized breast cancer screening based on ultrasonography. Ultrasonography 2023; 42:508-517. [PMID: 37697823 PMCID: PMC10555688 DOI: 10.14366/usg.23047] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 07/26/2023] [Accepted: 07/26/2023] [Indexed: 09/13/2023] Open
Abstract
Screening mammography programs have been implemented in numerous Western countries with the aim of reducing breast cancer mortality. However, despite over 20 years of population-based screening mammography, the mortality rates in Japan and Korea continue to rise. This may be due to the fact that screening mammography is not as effective for Japanese and Korean women, who often have dense breasts. This density decreases the sensitivity of mammography due to a masking effect. Therefore, the early detection of small invasive cancers requires more than just mammography, particularly for women in their 40s. This review discusses the limitations and challenges of screening mammography, as well as the keys to successful population-based breast cancer screening in Japan and Korea. This includes a focus on breast ultrasonography techniques, which are based on histopathologic anatomical knowledge, and personalized screening strategies that are based on risk assessments measured by glandular tissue components.
Collapse
Affiliation(s)
- Takayoshi Uematsu
- Department of Breast Imaging and Breast Intervention Radiology and Department of Clinical Physiology, Shizuoka Cancer Center Hospital, Japan
| | - Ayumi Izumori
- Department of Breast Surgery, Takamatsu Heiwa Hospital, Takamatsu, Japan
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| |
Collapse
|
35
|
Wei L, Zhang Q, Zhong C, He L, Zhang Y, Armaly AM, Aubé J, Welch DR, Xu L, Wu X. Functional inhibition of the RNA-binding protein HuR sensitizes triple-negative breast cancer to chemotherapy. Mol Oncol 2023; 17:1962-1980. [PMID: 37357618 PMCID: PMC10552894 DOI: 10.1002/1878-0261.13478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/18/2023] [Accepted: 06/23/2023] [Indexed: 06/27/2023] Open
Abstract
Chemotherapy remains the standard treatment for triple-negative breast cancer (TNBC); however, chemoresistance compromises its efficacy. The RNA-binding protein Hu antigen R (HuR) could be a potential therapeutic target to enhance the chemotherapy efficacy. HuR is known to mainly stabilize its target mRNAs, and/or promote the translation of encoded proteins, which are implicated in multiple cancer hallmarks, including chemoresistance. In this study, a docetaxel-resistant cell subline (231-TR) was established from the human TNBC cell line MDA-MB-231. Both the parental and resistant cell lines exhibited similar sensitivity to the small molecule functional inhibitor of HuR, KH-3. Docetaxel and KH-3 combination therapy synergistically inhibited cell proliferation in TNBC cells and tumor growth in three animal models. KH-3 downregulated the expression levels of HuR targets (e.g., β-Catenin and BCL2) in a time- and dose-dependent manner. Moreover, KH-3 restored docetaxel's effects on activating Caspase-3 and cleaving PARP in 231-TR cells, induced apoptotic cell death, and caused S-phase cell cycle arrest. Together, our findings suggest that HuR is a critical mediator of docetaxel resistance and provide a rationale for combining HuR inhibitors and chemotherapeutic agents to enhance chemotherapy efficacy.
Collapse
Affiliation(s)
- Lanjing Wei
- Bioengineering ProgramThe University of KansasLawrenceKSUSA
| | - Qi Zhang
- Department of Molecular BiosciencesThe University of KansasLawrenceKSUSA
| | - Cuncong Zhong
- Department of Electrical Engineering and Computer ScienceThe University of KansasLawrenceKSUSA
| | - Lily He
- Department of Pharmacology, Toxicology & TherapeuticsThe University of Kansas Medical CenterKansas CityKSUSA
| | - Yuxia Zhang
- Department of Pharmacology, Toxicology & TherapeuticsThe University of Kansas Medical CenterKansas CityKSUSA
| | - Ahlam M. Armaly
- Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of PharmacyThe University of North CarolinaChapel HillNCUSA
| | - Jeffrey Aubé
- Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of PharmacyThe University of North CarolinaChapel HillNCUSA
| | - Danny R. Welch
- Department of Cancer BiologyThe University of Kansas Medical CenterKansas CityKSUSA
- The University of Kansas Cancer CenterThe University of Kansas Medical CenterKansas CityKSUSA
| | - Liang Xu
- Department of Molecular BiosciencesThe University of KansasLawrenceKSUSA
- The University of Kansas Cancer CenterThe University of Kansas Medical CenterKansas CityKSUSA
- Department of Radiation OncologyThe University of Kansas Medical CenterKansas CityKSUSA
| | - Xiaoqing Wu
- The University of Kansas Cancer CenterThe University of Kansas Medical CenterKansas CityKSUSA
- Higuchi Biosciences CenterThe University of KansasLawrenceKSUSA
| |
Collapse
|
36
|
Bhimani F, Zhang J, Shah L, McEvoy M, Gupta A, Pastoriza J, Shihabi A, Feldman S. Can the Clinical Utility of iBreastExam, a Novel Device, Aid in Optimizing Breast Cancer Diagnosis? A Systematic Review. JCO Glob Oncol 2023; 9:e2300149. [PMID: 38085036 PMCID: PMC10846782 DOI: 10.1200/go.23.00149] [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: 05/04/2023] [Revised: 08/05/2023] [Accepted: 09/02/2023] [Indexed: 12/18/2023] Open
Abstract
PURPOSE A portable, cost-effective, easy-to-use, hand-held Intelligent Breast Exam (iBE), which is a wireless, radiation-free device, may be a valuable screening tool in resource-limited settings. While multiple studies evaluating the use of iBE have been conducted worldwide, there are no cumulative studies evaluating the iBE's performance. Therefore this review aims to determine the clinical utility and applicability of iBE compared with clinical breast examinations, ultrasound, and mammography and discuss its strengths and weaknesses when performing breast-cancer screening. METHODS A systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Four electronic databases were searched: PubMed, Cochrane Library, Web of Science, and Google Scholar. RESULTS The review included 11 studies with a total sample size of 16,052 breasts. The mean age ranged from 42 to 58 years. The sensitivity and specificity of the iBE ranged from 34.3% to 86% and 59% to 94%, respectively. For malignant lesions, iBE demonstrated a moderate to higher diagnostic capacity ranging from 57% to 93% and could identify tumor sizes spanning from 0.5 cm to 9 cm. CONCLUSION Our findings underscore the potential clinical utility and applicability of iBE as a prescreening and triaging tool, which may aid in reducing the burden of patients undergoing diagnostic imaging in lower- and middle-income countries. Furthermore, iBE has shown to diagnose cancers as small as 0.5 cm, which can be a boon in early detection and reduce mortality rates. However, the encouraging results of this systematic review should be interpreted with caution because of the device's low sensitivity and high false-positive rates.
Collapse
Affiliation(s)
- Fardeen Bhimani
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| | - Janice Zhang
- Albert Einstein College of Medicine, New York, NY
| | - Lamisha Shah
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| | - Maureen McEvoy
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| | - Anjuli Gupta
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| | - Jessica Pastoriza
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| | - Areej Shihabi
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| | - Sheldon Feldman
- Breast Surgery Division, Department of Surgery, Montefiore Medical Center, Montefiore Einstein Center for Cancer Care, New York, NY
| |
Collapse
|
37
|
Feigin K. Quality assurance in Mammography: An overview. Eur J Radiol 2023; 165:110935. [PMID: 37354771 PMCID: PMC10528604 DOI: 10.1016/j.ejrad.2023.110935] [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: 06/15/2023] [Indexed: 06/26/2023]
Abstract
Since 1989, hundreds of thousands of lives have been saved worldwide by the widespread use of screening mammography alongside new developments in breast cancer treatment [1]. The ability of screening mammography to detect cancer early, when treatment is most effective, is optimized when it is performed in the highest quality manner and accessed by all eligible candidates. Currently, worldwide, there are over 14 guidance documents for mammographic quality [2]. Some countries, such as the United Kingdom (UK), monitor quality through a national screening program. In the United States (US), where 39 million mammograms are performed annually [3], there is not a national screening program, but the federal government mandates minimum quality standards for the performance of mammography. Among a consortium of European countries, the European Reference Organisation for Quality Assured Breast Screening and Diagnostic Services (EUREF) promotes voluntary adherence to European mammography quality standards. Setting quality standards at national or international levels ensures the uniformity of practice and identifies substandard practices in need of improvement, ultimately maximizing the benefit of screening mammography.
Collapse
Affiliation(s)
- Kimberly Feigin
- Memorial Sloan Kettering Cancer Center, MSK Evelyn H. Lauder Breast and Imaging Center, 300 East 66(th) Street, New York, NY 10065, United States.
| |
Collapse
|
38
|
Kim G, Karadal-Ferrena B, Qin J, Sharma VP, Oktay IS, Lin Y, Ye X, Asiry S, Pastoriza JM, Cheng E, Ladak N, Condeelis JS, Adler E, Ginter PS, D'Alfonso T, Entenberg D, Xue X, Sparano JA, Oktay MH. Racial disparity in tumor microenvironment and distant recurrence in residual breast cancer after neoadjuvant chemotherapy. NPJ Breast Cancer 2023; 9:52. [PMID: 37311792 PMCID: PMC10264351 DOI: 10.1038/s41523-023-00547-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 04/28/2023] [Indexed: 06/15/2023] Open
Abstract
Black, compared to white, women with residual estrogen receptor-positive (ER+) breast cancer after neoadjuvant chemotherapy (NAC) have worse distant recurrence-free survival (DRFS). Such racial disparity may be due to difference in density of portals for systemic cancer cell dissemination, called TMEM doorways, and pro-metastatic tumor microenvironment (TME). Here, we evaluate residual cancer specimens after NAC from 96 Black and 87 white women. TMEM doorways are visualized by triple immunohistochemistry, and cancer stem cells by immunofluorescence for SOX9. The correlation between TMEM doorway score and pro-metastatic TME parameters with DRFS is examined using log-rank and multivariate Cox regression. Black, compared to white, patients are more likely to develop distant recurrence (49% vs 34.5%, p = 0.07), receive mastectomy (69.8% vs 54%, p = 0.04), and have higher grade tumors (p = 0.002). Tumors from Black patients have higher TMEM doorway and macrophages density overall (p = 0.002; p = 0.002, respectively) and in the ER+/HER2- (p = 0.02; p = 0.02, respectively), but not in the triple negative disease. Furthermore, high TMEM doorway score is associated with worse DRFS. TMEM doorway score is an independent prognostic factor in the entire study population (HR, 2.02; 95%CI, 1.18-3.46; p = 0.01), with a strong trend in ER+/HER2- disease (HR, 2.38; 95%CI, 0.96-5.95; p = 0.06). SOX9 expression is not associated with racial disparity in TME or outcome. In conclusion, higher TMEM doorway density in residual breast cancer after NAC is associated with higher distant recurrence risk, and Black patients are associated with higher TMEM doorway density, suggesting that TMEM doorway density may contribute to racial disparities in breast cancer.
Collapse
Affiliation(s)
- Gina Kim
- Department of Surgery, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Burcu Karadal-Ferrena
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Department of Basic Oncology, Hacettepe University, Ankara, Turkey
| | - Jiyue Qin
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Ved P Sharma
- Bio-Imaging Resource Center, The Rockefeller University, New York, NY, USA
| | - Isabelle S Oktay
- College of Art and Sciences, New York University, New York, NY, USA
| | - Yu Lin
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Xianjun Ye
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Integrated Imaging Program, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Saeed Asiry
- Department of Pathology, Batterjee Medical College, Jeddah, Saudi Arabia
| | - Jessica M Pastoriza
- Department of Surgery, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | | | - Nurfiza Ladak
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
| | - John S Condeelis
- Department of Surgery, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Integrated Imaging Program, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Department of Cell Biology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Esther Adler
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
| | - Paula S Ginter
- Department of Pathology, NYU Long Island School of Medicine, Mineola, NY, USA
| | - Timothy D'Alfonso
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - David Entenberg
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
- Integrated Imaging Program, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Xiaonan Xue
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA
| | - Joseph A Sparano
- Division of Hematology/Oncology, Icahn School of Medicine at Mount Sinai, Tisch Cancer Institute, New York, NY, USA
| | - Maja H Oktay
- Department of Surgery, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA.
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA.
- Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA.
- Integrated Imaging Program, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY, USA.
| |
Collapse
|
39
|
Zhang M, Mesurolle B, Theriault M, Meterissian S, Morris EA. Imaging of breast cancer-beyond the basics. Curr Probl Cancer 2023:100967. [PMID: 37316336 DOI: 10.1016/j.currproblcancer.2023.100967] [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: 01/12/2023] [Revised: 04/12/2023] [Accepted: 05/20/2023] [Indexed: 06/16/2023]
Abstract
Imaging of breast cancer is the backbone of breast cancer screening, diagnosis, preoperative/treatment assessment and follow-up. The main modalities are mammography, ultrasound and magnetic resonance imaging, each with its own advantages and disadvantages. New emerging technologies have also enabled each modality to improve on their weaknesses. Imaging-guided biopsies have allowed for accurate diagnosis of breast cancer, with low complication rates. The purpose of this article is to review the common modalities for breast cancer imaging in current practice with emphasis on the strengths and potential weaknesses, discuss the selection of the best imaging modality for the specific clinical question or patient population, and explore new technologies / future directions of breast cancer imaging.
Collapse
Affiliation(s)
- Michelle Zhang
- Department of Radiology, McGill University Health Center, Montreal, Quebec, Canada.
| | - Benoit Mesurolle
- Department of Radiology, Elsan, Pôle Santé République, Clermont-Ferrand, France
| | - Melanie Theriault
- Department of Radiology, McGill University Health Center, Montreal, Quebec, Canada
| | - Sarkis Meterissian
- Department of Surgery, McGill University Health Centre, Montreal, Quebec, Canada
| | | |
Collapse
|
40
|
Li J, Zhou X, Li L, Ji L, Li J, Qu Y, Wang Z, Zhao Y, Zhang J, Liang F, Liu J, Gu W, Yang R, Ma F, Dai L. The association between CTSZ methylation in peripheral blood and breast cancer in Chinese women. Front Oncol 2023; 13:1148635. [PMID: 37274256 PMCID: PMC10233099 DOI: 10.3389/fonc.2023.1148635] [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: 01/20/2023] [Accepted: 05/02/2023] [Indexed: 06/06/2023] Open
Abstract
Purpose Previous studies have shown that DNA methylation in peripheral blood may be associated with breast cancer (BC). To explore the association between the methylation level of the Cathepsin Z (CTSZ) gene in peripheral blood and BC, we conducted a case-control study in the Chinese population. Methods Peripheral blood samples were collected from 567 BC cases, 635 healthy controls, and 303 benign breast disease (BBD) cases. DNA extraction and bisulfite-specific PCR amplification were performed for all samples. The methylation levels of seven sites of the CTSZ gene were quantitatively determined by Mass spectrometry. The odds ratios (ORs) of CpG sites were evaluated for BC risk using per 10% reduction and quartiles analyses by logistic regression. Results Our analysis showed that five out of the seven CpG sites exhibited significant associations with hypomethylation of CTSZ and BC, compared to healthy controls. The highest OR was for Q2 of CTSZ_CpG_1 (OR: 1.62, P=0.006), particularly for early-stage breast cancer in the case of per 10% reduction of CTSZ_CpG_1 (OR: 1.20, P=0.003). We also found that per 10% reduction of CTSZ_CpG_5 (OR: 1.39, P=0.004) and CTSZ_CpG_7,8 (OR: 1.35, P=0.005) were associated with increased BC risk. Our study also revealed that four out of seven CpG sites were linked to increased BC risk in women under 50 years of age, compared to healthy controls. The highest OR was for per 10% reduction of CTSZ_CpG_1 (OR: 1.47, P<0.001). Additionally, we found that BC exhibited lower methylation levels than BBD at CTSZ_CpG_4 (OR for Q1: 2.18, P<0.001) and CTSZ_CpG_7,8 (OR for Q1: 2.01, P=0.001). Furthermore, we observed a correlation between methylation levels and tumor stage, ER, and HER2 status in BC patients. Conclusion Overall, our findings suggest that altered CTSZ methylation levels in peripheral blood may be associated with breast cancer, particularly in young women, and may serve as a potential biomarker for early-stage BC.
Collapse
Affiliation(s)
- Jinyu Li
- School of Basic Medical Sciences & The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan, China
| | - Xiajie Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Lixi Li
- Department of Medical Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Longtao Ji
- BGI College, Zhengzhou University, Zhengzhou, Henan, China
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| | - Jiaqi Li
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| | - Yunhui Qu
- Department of Clinical Laboratory in the First Affiliated Hospital & Key Clinical Laboratory of Henan Province, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhi Wang
- BGI College, Zhengzhou University, Zhengzhou, Henan, China
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| | - Yutong Zhao
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| | - Jie Zhang
- Department of Clinical Laboratory, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, China
| | - Feifei Liang
- BGI College, Zhengzhou University, Zhengzhou, Henan, China
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| | - Jingjing Liu
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| | - Wanjian Gu
- Department of Clinical Laboratory, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, China
| | - Rongxi Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Fei Ma
- Department of Medical Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Liping Dai
- School of Basic Medical Sciences & The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan, China
- Henan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, Henan, China
| |
Collapse
|
41
|
Zhu Y, Liu Z, Gui L, Yun W, Mao C, Deng R, Yao Y, Yu Q, Feng J, Ma H, Bao W. Inhibition of CXorf56 promotes PARP inhibitor-induced cytotoxicity in triple-negative breast cancer. NPJ Breast Cancer 2023; 9:34. [PMID: 37156759 PMCID: PMC10167262 DOI: 10.1038/s41523-023-00540-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 04/11/2023] [Indexed: 05/10/2023] Open
Abstract
Poly(ADP-ribose) polymerase inhibitors (PARPis) induce DNA lesions that preferentially kill homologous recombination (HR)-deficient breast cancers induced by BRCA mutations, which exhibit a low incidence in breast cancer, thereby limiting the benefits of PARPis. Additionally, breast cancer cells, particularly triple-negative breast cancer (TNBC) cells, exhibit HR and PARPi resistance. Therefore, targets must be identified for inducing HR deficiency and sensitizing cancer cells to PARPis. Here, we reveal that CXorf56 protein increased HR repair in TNBC cells by interacting with the Ku70 DNA-binding domain, reducing Ku70 recruitment and promoting RPA32, BRCA2, and RAD51 recruitment to sites of DNA damage. Knockdown of CXorf56 protein suppressed HR in TNBC cells, specifically during the S and G2 phases, and increased cell sensitivity to olaparib in vitro and in vivo. Clinically, CXorf56 protein was upregulated in TNBC tissues and associated with aggressive clinicopathological characteristics and poor survival. All these findings indicate that treatment designed to inhibit CXorf56 protein in TNBC combined with PARPis may overcome drug resistance and expand the application of PARPis to patients with non-BRCA mutantion.
Collapse
Affiliation(s)
- Ying Zhu
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Zhixian Liu
- Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Liang Gui
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Wen Yun
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Changfei Mao
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Rong Deng
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Yufeng Yao
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Qiao Yu
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jifeng Feng
- Department of General Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.
| | - Wei Bao
- Department of Pathology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
| |
Collapse
|
42
|
Acheampong T, Rodríguez CB, O'Neill SC, Agovino M, Argov EJL, Tehranifar P. Scientific uncertainty and perceived mammography benefits in women screened for breast cancer. Cancer Causes Control 2023; 34:611-619. [PMID: 37085746 DOI: 10.1007/s10552-023-01697-9] [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: 06/09/2022] [Accepted: 04/03/2023] [Indexed: 04/23/2023]
Abstract
PURPOSE Personal aversion to scientific uncertainty may influence how women perceive the benefits of mammography, a breast cancer screening practice with conflicting scientific opinions and guidelines. Such associations may even exist among women who participate in screening. METHODS We evaluated the distribution of aversion to ambiguous medical information (AA-Med), using a 6-item scale capturing the level of agreement with statements about obtaining a cancer screening test with conflicting medical recommendations in 665 women (aged 40-60 years; 79.5% Hispanic) recruited during screening mammography appointments in New York City. We assessed the association of AA-Med with perceptions of benefits of mammography (breast cancer mortality reduction, worry reduction, early detection, treatment improvement) using multivariable logistic regression. RESULTS Over a quarter of participants expressed negative reactions to medical ambiguity about a cancer screening test (e.g., fear, lower trust in experts), but a majority endorsed intention to undergo screening. AA-Med was higher in women who were U.S.-born, non-Hispanic black, and had marginal to adequate health literacy, but there were no differences by clinical factors or screening experiences (e.g., family history, prior breast biopsy). Women with higher AA-Med were more likely to perceive treatment benefits from mammography (OR = 1.37, 95% CI = 0.99-1.90), but AA-Med was not associated with other perceived mammography benefits. CONCLUSIONS Aversion to uncertainty regarding cancer screening varies by sociodemographic characteristics but has limited associations with perceived mammography benefits in women who already participate in screening.
Collapse
Affiliation(s)
- Teofilia Acheampong
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Carmen B Rodríguez
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Suzanne C O'Neill
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Mariangela Agovino
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Erica J Lee Argov
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Parisa Tehranifar
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA.
| |
Collapse
|
43
|
Kim DD, DeSnyder SM, Dougherty PM, Cata JP. Effect of neoadjuvant chemotherapy on intraoperative core temperature in patients with breast cancer: a retrospective cohort study. BJA OPEN 2023; 5:100119. [PMID: 37587989 PMCID: PMC10430839 DOI: 10.1016/j.bjao.2022.100119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 12/06/2022] [Accepted: 12/12/2022] [Indexed: 08/18/2023]
Abstract
Background Clinical evidence suggests that chemotherapeutic agents are associated with neuropathy and peripheral autonomic dysfunction. However, the possible effects of neoadjuvant chemotherapy on intraoperative temperature remain poorly characterised. Methods We evaluated patients who underwent a mastectomy for breast cancer between April 2016 and July 2020. Propensity scores were used to match patients who received neoadjuvant chemotherapy with those who did not, and intraoperative core temperature patterns were analysed in the matched cohort. The independent associations between vasopressor use and heart rate during general anaesthesia in the matched cohort were also analysed. Results Data from 1764 patients were analysed (882 patients in each group). Both groups presented a similar pattern of heat redistribution and subsequent rewarming; however, the neoadjuvant chemotherapy group did not reach the same intraoperative plateau temperature as the group that did not receive prior chemotherapy, with differences of up to 0.4°C (95% confidence interval: 0.11-0.63°C; P=0.005). In a subgroup analysis, neuropathy in patients who received neoadjuvant chemotherapy was associated with increased use of vasopressors and higher heart rate. Conclusions In patients with breast cancer, neoadjuvant chemotherapy is associated with lower plateau core temperatures, increased vasopressor use, and higher heart rates during general anaesthesia, which is more severe in the presence of neuropathy.
Collapse
Affiliation(s)
- Daniel D. Kim
- Department of Anesthesiology and Perioperative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Anesthesiology and Surgical Oncology Research Group, Houston, TX, USA
| | - Sarah M. DeSnyder
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Patrick M. Dougherty
- Department of Pain Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Juan P. Cata
- Department of Anesthesiology and Perioperative Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Anesthesiology and Surgical Oncology Research Group, Houston, TX, USA
| |
Collapse
|
44
|
Cariolou M, Abar L, Aune D, Balducci K, Becerra‐Tomás N, Greenwood DC, Markozannes G, Nanu N, Vieira R, Giovannucci EL, Gunter MJ, Jackson AA, Kampman E, Lund V, Allen K, Brockton NT, Croker H, Katsikioti D, McGinley‐Gieser D, Mitrou P, Wiseman M, Cross AJ, Riboli E, Clinton SK, McTiernan A, Norat T, Tsilidis KK, Chan DSM. Postdiagnosis recreational physical activity and breast cancer prognosis: Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis. Int J Cancer 2023; 152:600-615. [PMID: 36279903 PMCID: PMC10091720 DOI: 10.1002/ijc.34324] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 09/20/2022] [Accepted: 09/23/2022] [Indexed: 02/01/2023]
Abstract
It is important to clarify the associations between modifiable lifestyle factors such as physical activity and breast cancer prognosis to enable the development of evidence-based survivorship recommendations. We performed a systematic review and meta-analyses to summarise the evidence on the relationship between postbreast cancer diagnosis physical activity and mortality, recurrence and second primary cancers. We searched PubMed and Embase through 31st October 2021 and included 20 observational studies and three follow-up observational analyses of patients enrolled in clinical trials. In linear dose-response meta-analysis of the observational studies, each 10-unit increase in metabolic equivalent of task (MET)-h/week higher recreational physical activity was associated with 15% and 14% lower risk of all-cause (95% confidence interval [CI]: 8%-22%, studies = 12, deaths = 3670) and breast cancer-specific mortality (95% CI: 4%-23%, studies = 11, deaths = 1632), respectively. Recreational physical activity was not associated with breast cancer recurrence (HR = 0.97, 95% CI: 0.91-1.05, studies = 6, deaths = 1705). Nonlinear dose-response meta-analyses indicated 48% lower all-cause and 38% lower breast cancer-specific mortality with increasing recreational physical activity up to 20 MET-h/week, but little further reduction in risk at higher levels. Predefined subgroup analyses across strata of body mass index, hormone receptors, adjustment for confounders, number of deaths, menopause and physical activity intensities were consistent in direction and magnitude to the main analyses. Considering the methodological limitations of the included studies, the independent Expert Panel concluded 'limited-suggestive' likelihood of causality for an association between recreational physical activity and lower risk of all-cause and breast cancer-specific mortality.
Collapse
Affiliation(s)
- Margarita Cariolou
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Leila Abar
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Dagfinn Aune
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
- Department of NutritionBjørknes University CollegeOsloNorway
- Department of EndocrinologyMorbid Obesity and Preventive Medicine, Oslo University HospitalOsloNorway
- Unit of Cardiovascular and Nutritional EpidemiologyInstitute of Environmental Medicine, Karolinska InstitutetStockholmSweden
| | - Katia Balducci
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Nerea Becerra‐Tomás
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Darren C. Greenwood
- Leeds Institute for Data Analytics, Faculty of Medicine and HealthUniversity of LeedsLeedsUK
| | - Georgios Markozannes
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
- Department of Hygiene and EpidemiologyUniversity of Ioannina Medical SchoolIoanninaGreece
| | - Neesha Nanu
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Rita Vieira
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Edward L. Giovannucci
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Department of NutritionHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Marc J. Gunter
- Nutrition and Metabolism SectionInternational Agency for Research on CancerLyonFrance
| | - Alan A. Jackson
- Faculty of Medicine, School of Human Development and HealthUniversity of SouthamptonSouthamptonUK
- National Institute of Health Research Cancer and Nutrition CollaborationSouthamptonUK
| | - Ellen Kampman
- Division of Human Nutrition and HealthWageningen University & ResearchWageningenThe Netherlands
| | - Vivien Lund
- World Cancer Research Fund InternationalLondonUK
| | - Kate Allen
- World Cancer Research Fund InternationalLondonUK
| | | | - Helen Croker
- World Cancer Research Fund InternationalLondonUK
| | | | | | | | | | - Amanda J. Cross
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Elio Riboli
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| | - Steven K. Clinton
- Division of Medical Oncology, The Department of Internal MedicineCollege of Medicine and Ohio State University Comprehensive Cancer Center, Ohio State UniversityColumbusOhioUSA
| | - Anne McTiernan
- Division of Public Health SciencesFred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Teresa Norat
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
- World Cancer Research Fund InternationalLondonUK
| | - Konstantinos K. Tsilidis
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
- Department of Hygiene and EpidemiologyUniversity of Ioannina Medical SchoolIoanninaGreece
| | - Doris S. M. Chan
- Department of Epidemiology and BiostatisticsSchool of Public Health, Faculty of Medicine, Imperial College LondonLondonUK
| |
Collapse
|
45
|
Liu A, Li X, Wu H, Guo B, Jonnagaddala J, Zhang H, Xu S. Prognostic Significance of Tumor-Infiltrating Lymphocytes Determined Using LinkNet on Colorectal Cancer Pathology Images. JCO Precis Oncol 2023; 7:e2200522. [PMID: 36848612 DOI: 10.1200/po.22.00522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023] Open
Abstract
PURPOSE Tumor-infiltrating lymphocytes (TILs) have a significant prognostic value in cancers. However, very few automated, deep learning-based TIL scoring algorithms have been developed for colorectal cancer (CRC). MATERIALS AND METHODS We developed an automated, multiscale LinkNet workflow for quantifying TILs at the cellular level in CRC tumors using H&E-stained images from the Lizard data set with annotations of lymphocytes. The predictive performance of the automatic TIL scores (TILsLink) for disease progression and overall survival (OS) was evaluated using two international data sets, including 554 patients with CRC from The Cancer Genome Atlas (TCGA) and 1,130 patients with CRC from Molecular and Cellular Oncology (MCO). RESULTS The LinkNet model provided outstanding precision (0.9508), recall (0.9185), and overall F1 score (0.9347). Clear continuous TIL-hazard relationships were observed between TILsLink and the risk of disease progression or death in both TCGA and MCO cohorts. Both univariate and multivariate Cox regression analyses for the TCGA data demonstrated that patients with high TIL abundance had a significant (approximately 75%) reduction in risk for disease progression. In both the MCO and TCGA cohorts, the TIL-high group was significantly associated with improved OS in univariate analysis (30% and 54% reduction in risk, respectively). The favorable effects of high TIL levels were consistently observed in different subgroups (classified according to known risk factors). CONCLUSION The proposed deep-learning workflow for automatic TIL quantification on the basis of LinkNet can be a useful tool for CRC. TILsLink is likely an independent risk factor for disease progression and carries predictive information of disease progression beyond the current clinical risk factors and biomarkers. The prognostic significance of TILsLink for OS is also evident.
Collapse
Affiliation(s)
- Anran Liu
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China
| | - Xingyu Li
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China
| | - Hongyi Wu
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China
| | - Bangwei Guo
- School of Data Science, University of Science and Technology of China, Hefei, Anhui, China
| | | | - Hong Zhang
- Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China
| | - Steven Xu
- Clinical Pharmacology and Quantitative Science, Genmab Inc, Princeton, NJ
| |
Collapse
|
46
|
Brawley OW, Lansey DG. Disparities in Breast Cancer Outcomes and How to Resolve Them. Hematol Oncol Clin North Am 2023; 37:1-15. [PMID: 36435603 DOI: 10.1016/j.hoc.2022.08.002] [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] [Indexed: 11/24/2022]
Abstract
There has been a 40% decline in breast cancer age-adjusted death rate since 1990. Black American women have not experienced as great a decline; indeed, the Black-White disparity in mortality in the United States is greater today than it has ever been. Certain states (areas of residence), however, do not see such dramatic differences in outcome by race. This latter finding suggests much more can be done to reduce disparities and prevent deaths. Interventions to get high-quality care (screening, diagnostics, and treatment) involve understanding the needs and concerns of the patient and addressing those needs and concerns. Patient navigators are 1 way to improve outcomes.
Collapse
Affiliation(s)
- Otis W Brawley
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Dina George Lansey
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| |
Collapse
|
47
|
Strandberg R, Abrahamsson L, Isheden G, Humphreys K. Tumour Growth Models of Breast Cancer for Evaluating Early Detection-A Summary and a Simulation Study. Cancers (Basel) 2023; 15:cancers15030912. [PMID: 36765870 PMCID: PMC9913080 DOI: 10.3390/cancers15030912] [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: 12/15/2022] [Revised: 01/26/2023] [Accepted: 01/29/2023] [Indexed: 02/04/2023] Open
Abstract
With the advent of nationwide mammography screening programmes, a number of natural history models of breast cancers have been developed and used to assess the effects of screening. The first half of this article provides an overview of a class of these models and describes how they can be used to study latent processes of tumour progression from observational data. The second half of the article describes a simulation study which applies a continuous growth model to illustrate how effects of extending the maximum age of the current Swedish screening programme from 74 to 80 can be evaluated. Compared to no screening, the current and extended programmes reduced breast cancer mortality by 18.5% and 21.7%, respectively. The proportion of screen-detected invasive cancers which were overdiagnosed was estimated to be 1.9% in the current programme and 2.9% in the extended programme. With the help of these breast cancer natural history models, we can better understand the latent processes, and better study the effects of breast cancer screening.
Collapse
Affiliation(s)
- Rickard Strandberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
- Correspondence: (R.S.); (K.H.)
| | - Linda Abrahamsson
- Center for Primary Health Care Research, Lund University, 205 02 Malmö, Sweden
| | | | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
- Correspondence: (R.S.); (K.H.)
| |
Collapse
|
48
|
Ainembabazi P, Abila DB, Manyangwa G, Anguzu G, Musaazi J, Mutyaba I, Osingada CP, Mwaka AD. Perceived risk and risk reduction behaviours of female first-degree relatives of breast cancer patients attending care at Uganda cancer institute. Psychooncology 2023; 32:34-41. [PMID: 35584282 DOI: 10.1002/pon.5963] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 05/04/2022] [Accepted: 05/08/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVE The objective of this study was to assess the perceived risk of breast cancer (BC) and adoption of risk reduction behaviours among female first-degree relatives (FDRs) of BC patients attending care at the Uganda Cancer Institute (UCI). METHODS A cross-sectional study was performed using a questionnaire to collect data between March to October 2019. Adult female FDRs of patients attending care at UCI were recruited consecutively. Breast cancer perceived risk was assessed using a verbal measure; 'My chances of getting BC are great' on a Likert scale with 5 response alternatives. Chi square tests and modified Poisson regression using generalised estimating equations model were used to determine associations and examine factors associated with perceived risk of BC. RESULTS We enrolled 296 FDRs from 186 female BC patients. Few participants 118/296 (40%) had high perceived risk of BC. Majority 165/296 (56%), had ever practiced breast self-examination. At the multivariable modified Poisson GEE model, women aged 36-45 years were more likely to perceive themselves to be at high risk of developing BC compared to women aged 18-25 years (adjusted prevalence ratio: 1.174; 95% confidence interval [95%CI] = 1.05-2.88; p value = 0.030) after adjusting for age, religion, educational level and residence. CONCLUSION Few FDRs of BC patients perceived themselves to be at high risk of developing BC and do not seek risk reduction measures including screening and early diagnosis approaches. Breast cancer health education especially targeting younger women should emphasize the increased risk of BC in FDRs.
Collapse
Affiliation(s)
- Provia Ainembabazi
- Department of Nursing, School of Health Sciences, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Derrick Bary Abila
- Department of Pathology, School of Biomedical Sciences, College of Health Sciences, Makerere University, Kampala, Uganda
| | | | - Godwin Anguzu
- Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda.,Duke University, Durham, North Caroline, USA
| | - Joseph Musaazi
- Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | | | - Charles Peter Osingada
- Department of Nursing, School of Health Sciences, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Amos Deogratius Mwaka
- Department of Medicine, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda.,Department of Medicine, Faculty of Medicine, Gulu University, Kampala, Uganda
| |
Collapse
|
49
|
Mavragani A, Bradley H, Jin Y, Zhou L, Sun S, Xu X, Li S, Yang H, Zhang Q, Wang Y. An Assessment of the Predictive Performance of Current Machine Learning-Based Breast Cancer Risk Prediction Models: Systematic Review. JMIR Public Health Surveill 2022; 8:e35750. [PMID: 36426919 PMCID: PMC9837707 DOI: 10.2196/35750] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 06/17/2022] [Accepted: 11/25/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Several studies have explored the predictive performance of machine learning-based breast cancer risk prediction models and have shown controversial conclusions. Thus, the performance of the current machine learning-based breast cancer risk prediction models and their benefits and weakness need to be evaluated for the future development of feasible and efficient risk prediction models. OBJECTIVE The aim of this review was to assess the performance and the clinical feasibility of the currently available machine learning-based breast cancer risk prediction models. METHODS We searched for papers published until June 9, 2021, on machine learning-based breast cancer risk prediction models in PubMed, Embase, and Web of Science. Studies describing the development or validation models for predicting future breast cancer risk were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias and the clinical applicability of the included studies. The pooled area under the curve (AUC) was calculated using the DerSimonian and Laird random-effects model. RESULTS A total of 8 studies with 10 data sets were included. Neural network was the most common machine learning method for the development of breast cancer risk prediction models. The pooled AUC of the machine learning-based optimal risk prediction model reported in each study was 0.73 (95% CI 0.66-0.80; approximate 95% prediction interval 0.56-0.96), with a high level of heterogeneity between studies (Q=576.07, I2=98.44%; P<.001). The results of head-to-head comparison of the performance difference between the 2 types of models trained by the same data set showed that machine learning models had a slightly higher advantage than traditional risk factor-based models in predicting future breast cancer risk. The pooled AUC of the neural network-based risk prediction model was higher than that of the nonneural network-based optimal risk prediction model (0.71 vs 0.68, respectively). Subgroup analysis showed that the incorporation of imaging features in risk models resulted in a higher pooled AUC than the nonincorporation of imaging features in risk models (0.73 vs 0.61; Pheterogeneity=.001, respectively). The PROBAST analysis indicated that many machine learning models had high risk of bias and poorly reported calibration analysis. CONCLUSIONS Our review shows that the current machine learning-based breast cancer risk prediction models have some technical pitfalls and that their clinical feasibility and reliability are unsatisfactory.
Collapse
Affiliation(s)
| | | | - Yujing Jin
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Lengxiao Zhou
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Shaomei Sun
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaoqian Xu
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Shuqian Li
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Qing Zhang
- Health Management Center, Tianjin Medical University General Hospital, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China
| |
Collapse
|
50
|
Le XT, Lee J, Nguyen NT, Lee WT, Lee ES, Oh KT, Choi HG, Shin BS, Youn YS. Combined phototherapy with metabolic reprogramming-targeted albumin nanoparticles for treating breast cancer. Biomater Sci 2022; 10:7117-7132. [PMID: 36350285 DOI: 10.1039/d2bm01281b] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Triple-negative breast cancer (TNBC) is characterized by rapid tumor growth and resistance to cancer therapy, and has a poor prognosis. Accumulating data have revealed that cancer metabolism relies on both the Warburg effect and oxidative phosphorylation (OXPHOS), which are strongly related to the high proliferation and chemoresistance of cancer cells. Phototherapy is considered as a non-invasive method to precisely control drug activity with reduced side effects. Herein, our group introduced an Abraxane-like nanoplatform, named LCIR NPs, which significantly eradicates cancer cells via synergism between metabolic reprogramming and phototherapy effects. Endowed with mitochondria-targeting residues, the nanoparticles efficiently inhibited mitochondrial complexes I and IV as well as hexokinase II, leading to the depletion of intracellular ATP. Consequently, the photodynamic and photothermal effect triggered by NIR irradiation was enhanced due to the alleviation of hypoxia and the thermoresistance mechanism that rely on mitochondrial metabolism. In vivo experiments showed that the tumor size of mice that received the combination treatment was only 50.7 mm3, which was 21 times smaller than that of the untreated group and was much lower than those of other single treatments after 21 days. Additionally, almost no systemic undesired toxicity was detected during the observation period. We believe that the concept of LCIR as presented here offers a potential platform to overcome the resistance to conventional therapies by the incorporation with the energy metabolism inhibition approach.
Collapse
Affiliation(s)
- Xuan Thien Le
- School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
| | - Junyeong Lee
- School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
| | - Nguyen Thi Nguyen
- School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
| | - Woo Tak Lee
- School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
| | - Eun Seong Lee
- Department of Biotechnology, The Catholic University of Korea, 43 Jibong-ro, Bucheon-si, Gyeonggi-do 14662, Republic of Korea
| | - Kyung Taek Oh
- College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Han-Gon Choi
- College of Pharmacy, Hanyang University, 55, Hanyangdaehak-ro, Sangnok-gu, Ansan 15588, Republic of Korea
| | - Beom Soo Shin
- School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
| | - Yu Seok Youn
- School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
| |
Collapse
|