1
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Grätz C, Schuster M, Brandes F, Meidert AS, Kirchner B, Reithmair M, Schelling G, Pfaffl MW. A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics. Mol Aspects Med 2024; 97:101269. [PMID: 38552453 DOI: 10.1016/j.mam.2024.101269] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/11/2024] [Accepted: 03/17/2024] [Indexed: 06/12/2024]
Abstract
Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.
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Affiliation(s)
- Christian Grätz
- Department of Animal Physiology and Immunology, School of Life Sciences, Technical University of Munich, Freising, Germany.
| | - Martina Schuster
- Institute of Human Genetics, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Florian Brandes
- Department of Anesthesiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Agnes S Meidert
- Department of Anesthesiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Benedikt Kirchner
- Department of Animal Physiology and Immunology, School of Life Sciences, Technical University of Munich, Freising, Germany; Institute of Human Genetics, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Marlene Reithmair
- Institute of Human Genetics, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Gustav Schelling
- Department of Anesthesiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Michael W Pfaffl
- Department of Animal Physiology and Immunology, School of Life Sciences, Technical University of Munich, Freising, Germany.
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2
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Prime SS, Darski P, Hunter KD, Cirillo N, Parkinson EK. A Review of the Repair of DNA Double Strand Breaks in the Development of Oral Cancer. Int J Mol Sci 2024; 25:4092. [PMID: 38612901 PMCID: PMC11012950 DOI: 10.3390/ijms25074092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 03/29/2024] [Accepted: 04/01/2024] [Indexed: 04/14/2024] Open
Abstract
We explore the possibility that defects in genes associated with the response and repair of DNA double strand breaks predispose oral potentially malignant disorders (OPMD) to undergo malignant transformation to oral squamous cell carcinoma (OSCC). Defects in the homologous recombination/Fanconi anemia (HR/FA), but not in the non-homologous end joining, causes the DNA repair pathway to appear to be consistent with features of familial conditions that are predisposed to OSCC (FA, Bloom's syndrome, Ataxia Telangiectasia); this is true for OSCC that occurs in young patients, sometimes with little/no exposure to classical risk factors. Even in Dyskeratosis Congenita, a disorder of the telomerase complex that is also predisposed to OSCC, attempts at maintaining telomere length involve a pathway with shared HR genes. Defects in the HR/FA pathway therefore appear to be pivotal in conditions that are predisposed to OSCC. There is also some evidence that abnormalities in the HR/FA pathway are associated with malignant transformation of sporadic cases OPMD and OSCC. We provide data showing overexpression of HR/FA genes in a cell-cycle-dependent manner in a series of OPMD-derived immortal keratinocyte cell lines compared to their mortal counterparts. The observations in this study argue strongly for an important role of the HA/FA DNA repair pathway in the development of OSCC.
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Affiliation(s)
- Stephen S. Prime
- Centre for Immunology and Regenerative Medicine, Institute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UK;
| | - Piotr Darski
- Liverpool Head and Neck Centre, Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (P.D.); (K.D.H.)
| | - Keith D. Hunter
- Liverpool Head and Neck Centre, Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3BX, UK; (P.D.); (K.D.H.)
| | - Nicola Cirillo
- Melbourne Dental School, University of Melbourne, 720 Swanson Street, Carlton, Melbourne, VIC 3053, Australia;
- School of Dentistry, University of Jordan, Amman 11942, Jordan
| | - E. Kenneth Parkinson
- Centre for Immunology and Regenerative Medicine, Institute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UK;
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3
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Grossar L, Butaye E, Verhelst X. Biomarkers are strongly needed in liver transplantation, time to move forward. Hepatobiliary Surg Nutr 2024; 13:359-361. [PMID: 38617484 PMCID: PMC11007344 DOI: 10.21037/hbsn-24-31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 02/07/2024] [Indexed: 04/16/2024]
Affiliation(s)
- Lorenz Grossar
- Hepatology Research Unit, Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Liver Research Center Ghent, Ghent University, Ghent University Hospital, Ghent, Belgium
| | - Emma Butaye
- Hepatology Research Unit, Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Liver Research Center Ghent, Ghent University, Ghent University Hospital, Ghent, Belgium
| | - Xavier Verhelst
- Hepatology Research Unit, Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Department of Gastroenterology and Hepatology, Ghent University Hospital, Ghent, Belgium
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4
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Yi J, Luo X, Huang W, Yang W, Qi Y, He J, Xie H. PGK1 is a potential biomarker for early diagnosis and prognosis of hepatocellular carcinoma. Oncol Lett 2024; 27:109. [PMID: 38304170 PMCID: PMC10831403 DOI: 10.3892/ol.2024.14242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 12/05/2023] [Indexed: 02/03/2024] Open
Abstract
Hepatocellular carcinoma (HCC), a common type of liver cancer, is increasing in incidence worldwide. An early diagnosis of hepatocellular carcinoma (HCC) is still challenging: Currently, few biomarkers are available to diagnose the early stage of HCC, therefore, additional prognostic biomarkers are required to identify potential risk factors. The present study analyzed gene expression levels of HCC tissue samples and the protein expression levels obtained from the GSE46408 HCC dataset using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The metabolically associated differentially expressed genes (DEGs), including DEGs involved in the glucose metabolism pathway, were selected for further analysis. Phosphoglycerate kinase 1 (PGK1), a glycolytic enzyme, was determined as a potential prognostic biomarker through Kaplan-Meier curve and clinical association variable analyses. This was also verified based on the expression levels of PGK1 in tumor tissue and protein expression levels in several liver cancer cell lines. PGK1 mRNA demonstrated a high level of expression in HCC tissue and was significantly associated with a poor prognosis, showing a negative association with survival time. In addition, as an independent risk factor, PGK1 may potentially be a valuable prognostic biomarker for patients with HCC. Furthermore, expression of PGK1 was associated with the early stages (stage I and T1) of HCC. Moreover, PGK1 mRNA expression levels demonstrated a positive association with progression of liver cancer. The results suggested that PGK1 mRNA may be involved in the degree of HCC malignancy and may be a future potential prognostic biomarker for HCC progression.
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Affiliation(s)
- Jiaqi Yi
- College of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong 510632, P.R. China
| | - Xuehua Luo
- Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, P.R. China
| | - Weijian Huang
- Institute of Laboratory Animal Science, Jinan University, Guangzhou, Guangdong 510632, P.R. China
| | - Weijun Yang
- College of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong 510632, P.R. China
| | - Yan Qi
- Department of Market Research and Development, China Animal Husbandry Group, Beijing 100000, P.R. China
| | - Jun He
- Institute of Laboratory Animal Science, Jinan University, Guangzhou, Guangdong 510632, P.R. China
| | - Huijun Xie
- College of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong 510632, P.R. China
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5
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Mahmud I, Wei B, Veillon L, Tan L, Martinez S, Tran B, Raskind A, de Jong F, Akbani R, Weinstein JN, Beecher C, Lorenzi PL. An IROA Workflow for correction and normalization of ion suppression in mass spectrometry-based metabolomic profiling data. RESEARCH SQUARE 2024:rs.3.rs-3914827. [PMID: 38352620 PMCID: PMC10862963 DOI: 10.21203/rs.3.rs-3914827/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Ion suppression is a major problem in mass spectrometry (MS)-based metabolomics; it can dramatically decrease measurement accuracy, precision, and signal-to-noise sensitivity. Here we report a new method, the IROA TruQuant Workflow, that uses a stable isotope-labeled internal standard (IROA-IS) plus novel companion algorithms to 1) measure and correct for ion suppression, and 2) perform Dual MSTUS normalization of MS metabolomic data. We have evaluated the method across ion chromatography (IC), hydrophilic interaction liquid chromatography (HILIC), and reverse phase liquid chromatography (RPLC)-MS systems in both positive and negative ionization modes, with clean and unclean ion sources, and across different biological matrices. Across the broad range of conditions tested, all detected metabolites exhibited ion suppression ranging from 1% to 90+% and coefficient of variations ranging from 1% to 20%, but the Workflow and companion algorithms were highly effective at nulling out that suppression and error. Overall, the Workflow corrects ion suppression across diverse analytical conditions and produces robust normalization of non-targeted metabolomic data.
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6
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Samaržija I. The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery. Biomedicines 2023; 12:79. [PMID: 38255186 PMCID: PMC10813710 DOI: 10.3390/biomedicines12010079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 12/16/2023] [Accepted: 12/26/2023] [Indexed: 01/24/2024] Open
Abstract
Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.
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Affiliation(s)
- Ivana Samaržija
- Laboratory for Epigenomics, Division of Molecular Medicine, Ruđer Bošković Institute, 10000 Zagreb, Croatia
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7
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Liu Y, Zhou Y, Chen P. Lung cancer organoids: models for preclinical research and precision medicine. Front Oncol 2023; 13:1293441. [PMID: 37941550 PMCID: PMC10628480 DOI: 10.3389/fonc.2023.1293441] [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: 09/13/2023] [Accepted: 09/27/2023] [Indexed: 11/10/2023] Open
Abstract
Lung cancer is a malignancy with high incidence and mortality rates globally, and it has a 5-year survival rate of only 10%-20%. The significant heterogeneity in clinical presentation, histological features, multi-omics findings, and drug sensitivity among different lung cancer patients necessitate the development of personalized treatment strategies. The current precision medicine for lung cancer, primarily based on pathological and genomic multi-omics testing, fails to meet the needs of patients with clinically refractory lung cancer. Lung cancer organoids (LCOs) are derived from tumor cells within tumor tissues and are generated through three-dimensional tissue culture, enabling them to faithfully recapitulate in vivo tumor characteristics and heterogeneity. The establishment of a series of LCOs biobanks offers promising platforms for efficient screening and identification of novel targets for anti-tumor drug discovery. Moreover, LCOs provide supplementary decision-making factors to enhance the current precision medicine for lung cancer, thereby addressing the limitations associated with pathology-guided approaches in managing refractory lung cancer. This article presents a comprehensive review on the construction methods and potential applications of LCOs in both preclinical and clinical research. It highlights the significance of LCOs in biomarker exploration, drug resistance investigation, target identification, clinical precision drug screening, as well as microfluidic technology-based high-throughput drug screening strategies. Additionally, it discusses the current limitations and future prospects of this field.
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Affiliation(s)
- Yajing Liu
- School of Pharmacy, Qingdao University, Qingdao, China
- Research and Development Department, NanoPeptide (Qingdao) Biotechnology Ltd., Qingdao, China
| | - Yanbing Zhou
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Pu Chen
- Research and Development Department, NanoPeptide (Qingdao) Biotechnology Ltd., Qingdao, China
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, ON, Canada
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8
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Batool SM, Yekula A, Khanna P, Hsia T, Gamblin AS, Ekanayake E, Escobedo AK, You DG, Castro CM, Im H, Kilic T, Garlin MA, Skog J, Dinulescu DM, Dudley J, Agrawal N, Cheng J, Abtin F, Aberle DR, Chia D, Elashoff D, Grognan T, Krysan K, Oh SS, Strom C, Tu M, Wei F, Xian RR, Skates SJ, Zhang DY, Trinh T, Watson M, Aft R, Rawal S, Agarwal A, Kesmodel SB, Yang C, Shen C, Hochberg FH, Wong DTW, Patel AA, Papadopoulos N, Bettegowda C, Cote RJ, Srivastava S, Lee H, Carter BS, Balaj L. The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring. Cell Rep Med 2023; 4:101198. [PMID: 37716353 PMCID: PMC10591039 DOI: 10.1016/j.xcrm.2023.101198] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 12/01/2022] [Accepted: 08/22/2023] [Indexed: 09/18/2023]
Abstract
The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.
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Affiliation(s)
| | - Anudeep Yekula
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Prerna Khanna
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tiffaney Hsia
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Austin S Gamblin
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Emil Ekanayake
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ana K Escobedo
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Dong Gil You
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Cesar M Castro
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hyungsoon Im
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tugba Kilic
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Johan Skog
- Exosome Diagnostics Inc., Waltham, MA, USA
| | | | - Jonathan Dudley
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Jordan Cheng
- University of California Los Angeles, Los Angeles, CA, USA
| | | | | | - David Chia
- University of California Los Angeles, Los Angeles, CA, USA
| | - David Elashoff
- University of California Los Angeles, Los Angeles, CA, USA
| | | | | | - Scott S Oh
- University of California Los Angeles, Los Angeles, CA, USA
| | - Charles Strom
- University of California Los Angeles, Los Angeles, CA, USA
| | - Michael Tu
- Liquid Diagnostics LLC., Los Angeles, CA, USA
| | - Fang Wei
- University of California Los Angeles, Los Angeles, CA, USA
| | - Rena R Xian
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Steven J Skates
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Thi Trinh
- Yale University School of Medicine, New Haven, CT, USA
| | - Mark Watson
- Washington University School of Medicine, St. Louis, MO, USA
| | - Rebecca Aft
- Washington University School of Medicine, St. Louis, MO, USA
| | - Siddarth Rawal
- Washington University School of Medicine, St. Louis, MO, USA; Circulogix Inc., St. Louis, MO, USA
| | | | | | | | - Cheng Shen
- California Institute of Technology, Pasadena, CA, USA
| | | | - David T W Wong
- University of California Los Angeles, Los Angeles, CA, USA
| | | | | | | | - Richard J Cote
- Washington University School of Medicine, St. Louis, MO, USA; Circulogix Inc., St. Louis, MO, USA
| | - Sudhir Srivastava
- Cancer Biomarkers Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA
| | - Hakho Lee
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bob S Carter
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Leonora Balaj
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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9
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Zhao T, Cao L, Ji J, Chang DK, Wu J. ReProMSig: an integrative platform for development and application of reproducible multivariable models for cancer prognosis supporting guideline-based transparent reporting. Brief Bioinform 2023; 24:bbad267. [PMID: 37529934 DOI: 10.1093/bib/bbad267] [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] [Indexed: 08/03/2023] Open
Abstract
Adequate reporting is essential for evaluating the performance and clinical utility of a prognostic prediction model. Previous studies indicated a prevalence of incomplete or suboptimal reporting in translational and clinical studies involving development of multivariable prediction models for prognosis, which limited the potential applications of these models. While reporting templates introduced by the established guidelines provide an invaluable framework for reporting prognostic studies uniformly, there is a widespread lack of qualified adherence, which may be due to miscellaneous challenges in manual reporting of extensive model details, especially in the era of precision medicine. Here, we present ReProMSig (Reproducible Prognosis Molecular Signature), a web-based integrative platform providing the analysis framework for development, validation and application of a multivariable prediction model for cancer prognosis, using clinicopathological features and/or molecular profiles. ReProMSig platform supports transparent reporting by presenting both methodology details and analysis results in a strictly structured reporting file, following the guideline checklist with minimal manual input needed. The generated reporting file can be published together with a developed prediction model, to allow thorough interrogation and external validation, as well as online application for prospective cases. We demonstrated the utilities of ReProMSig by development of prognostic molecular signatures for stage II and III colorectal cancer respectively, in comparison with a published signature reproduced by ReProMSig. Together, ReProMSig provides an integrated framework for development, evaluation and application of prognostic/predictive biomarkers for cancer in a more transparent and reproducible way, which would be a useful resource for health care professionals and biomedical researchers.
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Affiliation(s)
- Tingting Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Center for Cancer Bioinformatics, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Lihua Cao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Center for Cancer Bioinformatics, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Jiafu Ji
- Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - David K Chang
- Wolfson Wohl Cancer Research Centre, Institute of Cancer Sciences, University of Glasgow, Scotland, United Kingdom
- West of Scotland Pancreatic Unit, Glasgow Royal Infirmary, Glasgow, United Kingdom
| | - Jianmin Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Center for Cancer Bioinformatics, Peking University Cancer Hospital & Institute, Beijing 100142, China
- Peking University International Cancer Institute, Peking University, Beijing 100191, China
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10
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Barker AD, Alba MM, Mallick P, Agus DB, Lee JSH. An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next. Mol Cell Proteomics 2023:100569. [PMID: 37196763 PMCID: PMC10388583 DOI: 10.1016/j.mcpro.2023.100569] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/26/2023] [Accepted: 05/08/2023] [Indexed: 05/19/2023] Open
Abstract
Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.
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Affiliation(s)
- Anna D Barker
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Complex Adaptive Systems Initiative and School of Life Sciences, Arizona State University, Tempe, Arizona
| | - Mario M Alba
- Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA
| | - Parag Mallick
- Canary Center at Stanford for Cancer Early Detection, Stanford University, Stanford, CA; Department of Radiology, Stanford University, Stanford, CA
| | - David B Agus
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA
| | - Jerry S H Lee
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA
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11
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Sahafnejad Z, Ramazi S, Allahverdi A. An Update of Epigenetic Drugs for the Treatment of Cancers and Brain Diseases: A Comprehensive Review. Genes (Basel) 2023; 14:genes14040873. [PMID: 37107631 PMCID: PMC10137918 DOI: 10.3390/genes14040873] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/28/2022] [Accepted: 04/03/2023] [Indexed: 04/08/2023] Open
Abstract
Epigenetics has long been recognized as a significant field in biology and is defined as the investigation of any alteration in gene expression patterns that is not attributed to changes in the DNA sequences. Epigenetic marks, including histone modifications, non-coding RNAs, and DNA methylation, play crucial roles in gene regulation. Numerous studies in humans have been carried out on single-nucleotide resolution of DNA methylation, the CpG island, new histone modifications, and genome-wide nucleosome positioning. These studies indicate that epigenetic mutations and aberrant placement of these epigenetic marks play a critical role in causing the disease. Consequently, significant development has occurred in biomedical research in identifying epigenetic mechanisms, their interactions, and changes in health and disease conditions. The purpose of this review article is to provide comprehensive information about the different types of diseases caused by alterations in epigenetic factors such as DNA methylation and histone acetylation or methylation. Recent studies reported that epigenetics could influence the evolution of human cancer via aberrant methylation of gene promoter regions, which is associated with reduced gene function. Furthermore, DNA methyltransferases (DNMTs) in the DNA methylation process as well as histone acetyltransferases (HATs)/histone deacetylases (HDACs) and histone methyltransferases (HMTs)/demethylases (HDMs) in histone modifications play important roles both in the catalysis and inhibition of target gene transcription and in many other DNA processes such as repair, replication, and recombination. Dysfunction in these enzymes leads to epigenetic disorders and, as a result, various diseases such as cancers and brain diseases. Consequently, the knowledge of how to modify aberrant DNA methylation as well as aberrant histone acetylation or methylation via inhibitors by using epigenetic drugs can be a suitable therapeutic approach for a number of diseases. Using the synergistic effects of DNA methylation and histone modification inhibitors, it is hoped that many epigenetic defects will be treated in the future. Numerous studies have demonstrated a link between epigenetic marks and their effects on brain and cancer diseases. Designing appropriate drugs could provide novel strategies for the management of these diseases in the near future.
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Affiliation(s)
- Zahra Sahafnejad
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Jalal Ale Ahmad Highway, Tehran P.O. Box 14115-111, Iran
| | - Shahin Ramazi
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Jalal Ale Ahmad Highway, Tehran P.O. Box 14115-111, Iran
| | - Abdollah Allahverdi
- Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Jalal Ale Ahmad Highway, Tehran P.O. Box 14115-111, Iran
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12
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Chang L, Wu X, Ran K, Tian Y, Ouyang X, Liu H, Gou S, Zhang Y, Ni J. One New Acid-Activated Hybrid Anticancer Peptide by Coupling with a Desirable pH-Sensitive Anionic Partner Peptide. ACS OMEGA 2023; 8:7536-7545. [PMID: 36873017 PMCID: PMC9979329 DOI: 10.1021/acsomega.2c06766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
Anticancer peptides (ACPs) are promising antitumor resources, and developing acid-activated ACPs as more effective and selective antitumor drugs would represent new progress in cancer therapy. In this study, we designed a new class of acid-activated hybrid peptides LK-LE by altering the charge shielding position of the anionic binding partner LE based on the cationic ACP LK and investigated their pH response, cytotoxic activity, and serum stability, in hoping to achieve a desirable acid-activatable ACP. As expected, the obtained hybrid peptides could be activated and exhibit a remarkable antitumor activity by rapid membrane disruption at acidic pH, whereas its killing activity could be alleviated at normal pH, showing a significant pH response compared with LK. Importantly, this study found that the peptide LK-LE3 with the charge shielding in the N-terminal of LK displayed notably low cytotoxicity and more stability, demonstrating that the position of charge masking is extremely important for the improvement of peptide toxicity and stability. In short, our work opens a new avenue to design promising acid-activated ACPs as potential targeting agents for cancer treatment.
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Affiliation(s)
- Linlin Chang
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Xiaoyan Wu
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Kaixin Ran
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Yali Tian
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Xu Ouyang
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Hui Liu
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Sanhu Gou
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Yun Zhang
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
| | - Jingman Ni
- Research
Unit of Peptide Science, Chinese Academy
of Medical Sciences, 2019RU066, Lanzhou University, Lanzhou 730000, P. R. China
- Institute
of Pharmaceutics, School of Pharmacy and Key Laboratory of Preclinical
Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China
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13
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Diagnosis of Fibrotic Hypersensitivity Pneumonitis: Is There a Role for Biomarkers? Life (Basel) 2023; 13:life13020565. [PMID: 36836922 PMCID: PMC9966605 DOI: 10.3390/life13020565] [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: 12/26/2022] [Revised: 01/31/2023] [Accepted: 02/03/2023] [Indexed: 02/19/2023] Open
Abstract
Hypersensitivity pneumonitis is a complex interstitial lung syndrome and is associated with significant morbimortality, particularly for fibrotic disease. This condition is characterized by sensitization to a specific antigen, whose early identification is associated with improved outcomes. Biomarkers measure objectively biologic processes and may support clinical decisions. These tools evolved to play a crucial role in the diagnosis and management of a wide range of human diseases. This is not the case, however, with hypersensitivity pneumonitis, where there is still great room for research in the path to find consensual diagnostic biomarkers. Gaps in the current evidence include lack of validation, validation against healthy controls alone, small sampling and heterogeneity in diagnostic and classification criteria. Furthermore, discriminatory accuracy is currently limited by overlapping mechanisms of inflammation, damage and fibrogenesis between ILDs. Still, biomarkers such as BAL lymphocyte counts and specific serum IgGs made their way into clinical guidelines, while others including KL-6, SP-D, YKL-40 and apolipoproteins have shown promising results in leading centers and have potential to translate into daily practice. As research proceeds, it is expected that the emergence of novel categories of biomarkers will offer new and thriving tools that could complement those currently available.
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14
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Mazer BL, Lee JW, Roberts NJ, Chu LC, Lennon AM, Klein AP, Eshleman JR, Fishman EK, Canto MI, Goggins MG, Hruban RH. Screening for pancreatic cancer has the potential to save lives, but is it practical? Expert Rev Gastroenterol Hepatol 2023; 17:555-574. [PMID: 37212770 PMCID: PMC10424088 DOI: 10.1080/17474124.2023.2217354] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/21/2023] [Accepted: 05/19/2023] [Indexed: 05/23/2023]
Abstract
INTRODUCTION Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers. AREAS COVERED This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms. EXPERT OPINION From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.
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Affiliation(s)
- Benjamin L. Mazer
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jae W. Lee
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nicholas J. Roberts
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Linda C. Chu
- Department of Radiology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anne Marie Lennon
- Department of Medicine, Division of Gastroenterology and Hepatology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alison P. Klein
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James R. Eshleman
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Elliot K. Fishman
- Department of Radiology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marcia Irene Canto
- Department of Medicine, Division of Gastroenterology and Hepatology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael G. Goggins
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ralph H. Hruban
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
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15
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Rowe A. Recommendations to improve use and reporting of statistics in animal experiments. Lab Anim 2022:236772221140669. [DOI: 10.1177/00236772221140669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Flaws in experimental statistics are a major contributor to the poor reproducibility of animal experiments. Informed decisions about whether conclusions are justified requires clear reporting of experimental data and the statistical methods used to analyse them. When data are misinterpreted, manipulated or concealed to generate publications, it creates an illusion that chance observations are robust data which confirm the hypotheses presented. Attempts to reproduce and advance such observations can propagate large areas of irreproducible science. This hinders scientific progress, erodes public support for research, damages reputations and wastes resources. This review analyses and explains recommendations to improve use and reporting of statistics in animal experiments.
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16
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DeLouize AM, Eick G, Karam SD, Snodgrass JJ. Current and future applications of biomarkers in samples collected through minimally invasive methods for cancer medicine and population-based research. Am J Hum Biol 2022; 34:e23665. [PMID: 34374148 PMCID: PMC9894104 DOI: 10.1002/ajhb.23665] [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: 03/24/2021] [Revised: 07/27/2021] [Accepted: 07/28/2021] [Indexed: 02/04/2023] Open
Abstract
Despite advances in cancer medicine and research, invasive and potentially risky procedures such as biopsies, venous blood tests, imaging, colonoscopy, and pap smear tests are still primarily used for screening, staging, and assessing response to therapy. The development and interdisciplinary use of biomarkers from urine, feces, saliva, scent, and capillary blood collected with minimally invasive methods represents a potential opportunity for integration with biomarker analysis for cancers, both in clinical practice (e.g., in screening, treatment, and disease monitoring, and improved quality of life for patients) and population-based research (e.g., in epidemiology/public health, studies of social and environmental determinants, and evolutionary medicine). In this article, we review the scientific rationale, benefits, challenges, and potential opportunities for measuring cancer-related biomarkers in samples collected through minimally invasive methods.
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Affiliation(s)
| | - Geeta Eick
- Department of Anthropology, University of Oregon, Eugene, Oregon, USA
| | - Sana D. Karam
- Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - J. Josh Snodgrass
- Department of Anthropology, University of Oregon, Eugene, Oregon, USA
- Center for Global Health, University of Oregon, Eugene, Oregon, USA
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17
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Lee JC. Going deeper: molecular inflammatory scores in IBD. Gut 2022:gutjnl-2022-328539. [PMID: 36307179 DOI: 10.1136/gutjnl-2022-328539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 10/14/2022] [Indexed: 12/08/2022]
Affiliation(s)
- James C Lee
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London, UK .,Institute of Liver and Digestive Health, Royal Free Hospital, University College London, London, UK
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18
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van den Bosch T, Rueda OM, Caldas C, Vermeulen L, Miedema DM. Copy number heterogeneity identifies ER+ breast cancer patients that do not benefit from adjuvant endocrine therapy. Br J Cancer 2022; 127:1332-1339. [PMID: 35864159 PMCID: PMC9519566 DOI: 10.1038/s41416-022-01906-3] [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: 01/19/2022] [Revised: 06/22/2022] [Accepted: 06/28/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Endocrine therapy forms the backbone of adjuvant treatment for oestrogen-receptor-positive (ER+) breast cancer. However, it remains unclear whether adjuvant treatment improves survival rates in low-risk patients. Low intra-tumour heterogeneity (ITH) has been shown to confer low risk for recurrent disease. Here, it is studied if chromosomal copy-number ITH (CNH) can identify low-risk ER+, lymph-node-negative breast cancer patients who do not benefit from adjuvant endocrine therapy. METHODS Lymph-node-negative ER+ patients from the observational METABRIC dataset were retrospectively analysed (n = 708). CNH was determined from a single bulk copy-number measurement for each patient. Survival rates were compared between patients that did or did not receive adjuvant endocrine therapy for CNH-low, middle and high groups with Cox proportional-hazards models, using propensity-score weights to correct for confounders. RESULTS Adjuvant endocrine therapy improved the relapse-free survival (RFS) for CNH-high patients treatment (HR = 0.55), but not for CNH-low patients treatment (HR = 0.88). For CNH-low patients adjuvant endocrine therapy was associated with impaired OS (HR = 1.62). CONCLUSIONS This retrospective study of lymph-node-negative, ER+ breast cancer finds that patients identified as low risk using CNH do not benefit from adjuvant endocrine therapy.
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Affiliation(s)
- Tom van den Bosch
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism, Amsterdam University Medical Centers, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Oncode Institute, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Oscar M Rueda
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Carlos Caldas
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Department of Oncology, University of Cambridge, Cambridge, CB2 2QQ, 17, UK
- CRUK Cambridge Centre, Cambridge Experimental Cancer Medicine Centre (ECMC) and NIHR Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge, CB2 0RE, UK
| | - Louis Vermeulen
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism, Amsterdam University Medical Centers, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Oncode Institute, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Daniël M Miedema
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism, Amsterdam University Medical Centers, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
- Oncode Institute, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
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19
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Rodrigues-Ferreira S, Nahmias C. Predictive biomarkers for personalized medicine in breast cancer. Cancer Lett 2022; 545:215828. [PMID: 35853538 DOI: 10.1016/j.canlet.2022.215828] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 07/04/2022] [Accepted: 07/10/2022] [Indexed: 12/14/2022]
Abstract
Breast cancer is one of the most frequent malignancies among women worldwide. Based on clinical and molecular features of breast tumors, patients are treated with chemotherapy, hormonal therapy and/or radiotherapy and more recently with immunotherapy or targeted therapy. These different therapeutic options have markedly improved patient outcomes. However, further improvement is needed to fight against resistance to treatment. In the rapidly growing area of research for personalized medicine, predictive biomarkers - which predict patient response to therapy - are essential tools to select the patients who are most likely to benefit from the treatment, with the aim to give the right therapy to the right patient and avoid unnecessary overtreatment. The search for predictive biomarkers is an active field of research that includes genomic, proteomic and/or machine learning approaches. In this review, we describe current strategies and innovative tools to identify, evaluate and validate new biomarkers. We also summarize current predictive biomarkers in breast cancer and discuss companion biomarkers of targeted therapy in the context of precision medicine.
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Affiliation(s)
- Sylvie Rodrigues-Ferreira
- Gustave Roussy Institute, INSERM U981, Prédicteurs moléculaires et nouvelles cibles en oncologie, Villejuif, France; LabEx LERMIT, Université Paris-Saclay, 92296 Châtenay-Malabry, France; Inovarion, 75005, Paris, France
| | - Clara Nahmias
- Gustave Roussy Institute, INSERM U981, Prédicteurs moléculaires et nouvelles cibles en oncologie, Villejuif, France; LabEx LERMIT, Université Paris-Saclay, 92296 Châtenay-Malabry, France.
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20
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Shen N, Wang Q, Qiu Y, Wang Y, Li D, Li M. Clinicopathological and prognostic role of ROC1 in neoplasms: A PRISMA-compliant systematic review and meta-analysis. Medicine (Baltimore) 2022; 101:e29806. [PMID: 35777041 PMCID: PMC9239593 DOI: 10.1097/md.0000000000029806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Regulator of cullins 1 (ROC1) is frequently overexpressed in multiple tumors, and many pieces of research demonstrate that ROC1 is associated with the prognosis and development of a diversity of neoplasms and it is able to serve as a promising prognostic biomarker. Here we performed this meta-analysis to evaluate the prognostic and clinicopathological significance of ROC1 in patients suffering from cancer. METHODS We searched Pubmed, Embase, Web of Science, Chinese National Knowledge Infrastructure (CNKI), and WanFang database. The role of ROC1 in cancers was evaluated by pooled hazard ratios (HRs), odd ratios (ORs) and 95% confidence intervals (CIs). RESULTS In total, 9 studies including 1002 patients were enrolled in this analysis. The pooled results showed that patients with high expression of ROC1 had poor overall survival (OS) (HR: 2.04, 95% CI: 1.48-2.60, P < 0.001) and recurrence-free survival (RFS) (HR: 1.727, 95% CI: 0.965-2.488, P < 0.001). Additionally, elevated expression of ROC1 was significantly correlated with advanced clinical Tumor Node Metastasis stage (OR: 2.708, 95% CI: 1.856-3.951, P < 0.001), positive lymph node metastasis (OR: 1.968; 95% CI: 1.294-2.993, P = .002), large tumor size (OR: 1.522, 95% CI: 1.079-2.149, P = .017) and poor tumor differentiation (OR: 2.448, 95% CI: 1.793-3.344, P < 0.001). CONCLUSIONS Elevated ROC1 expression predicted worse prognosis and advanced pathological parameters in various cancers. ROC1 was a significant prognostic biomarker for poor survival in human cancers.
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Affiliation(s)
- Nirui Shen
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Qingting Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yuanjie Qiu
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yan Wang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Danyang Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Manxiang Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- *Correspondence: Manxiang Li, Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an, Shaanxi 710061, China (e-mail: )
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21
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Wong GYM, Diakos C, Hugh TJ, Molloy MP. Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases. Int J Mol Sci 2022; 23:ijms23116091. [PMID: 35682769 PMCID: PMC9181741 DOI: 10.3390/ijms23116091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 05/27/2022] [Accepted: 05/27/2022] [Indexed: 12/14/2022] Open
Abstract
Colorectal liver metastases (CRLM) are the leading cause of death among patients with metastatic colorectal cancer (CRC). As part of multimodal therapy, liver resection is the mainstay of curative-intent treatment for select patients with CRLM. However, effective treatment of CRLM remains challenging as recurrence occurs in most patients after liver resection. Proposed clinicopathologic factors for predicting recurrence are inconsistent and lose prognostic significance over time. The rapid development of next-generation sequencing technologies and decreasing DNA sequencing costs have accelerated the genomic profiling of various cancers. The characterisation of genomic alterations in CRC has significantly improved our understanding of its carcinogenesis. However, the functional context at the protein level has not been established for most of this genomic information. Furthermore, genomic alterations do not always result in predicted changes in the corresponding proteins and cancer phenotype, while post-transcriptional and post-translational regulation may alter synthesised protein levels, affecting phenotypes. More recent advancements in mass spectrometry-based technology enable accurate protein quantitation and comprehensive proteomic profiling of cancers. Several studies have explored proteomic biomarkers for predicting CRLM after oncologic resection of primary CRC and recurrence after curative-intent resection of CRLM. The current review aims to rationalise the proteomic complexity of CRC and explore the potential applications of proteomic biomarkers in CRLM.
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Affiliation(s)
- Geoffrey Yuet Mun Wong
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, NSW 2065, Australia;
- Northern Clinical School, The University of Sydney, Sydney, NSW 2065, Australia;
- Correspondence:
| | - Connie Diakos
- Northern Clinical School, The University of Sydney, Sydney, NSW 2065, Australia;
- Department of Medical Oncology, Royal North Shore Hospital, Sydney, NSW 2065, Australia
| | - Thomas J. Hugh
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, NSW 2065, Australia;
- Northern Clinical School, The University of Sydney, Sydney, NSW 2065, Australia;
| | - Mark P. Molloy
- Bowel Cancer and Biomarker Research Laboratory, Faculty of Medicine and Health, School of Medical Sciences, The University of Sydney, Sydney, NSW 2006, Australia;
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22
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Emons G, Auslander N, Jo P, Kitz J, Azizian A, Hu Y, Hess CF, Roedel C, Sax U, Salinas G, Stroebel P, Kramer F, Beissbarth T, Grade M, Ghadimi M, Ruppin E, Ried T, Gaedcke J. Gene-expression profiles of pretreatment biopsies predict complete response of rectal cancer patients to preoperative chemoradiotherapy. Br J Cancer 2022; 127:766-775. [PMID: 35597871 PMCID: PMC9381580 DOI: 10.1038/s41416-022-01842-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 03/19/2022] [Accepted: 05/04/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging. Experimental design We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial. Results A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76). Conclusion The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy. Translational relevance Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.
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Affiliation(s)
- Georg Emons
- Section of Cancer Genomics, Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.,Department of General, Visceral and Pediatric Surgery, University Medical Center, Göttingen, Germany
| | - Noam Auslander
- Section of Cancer Genomics, Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.,Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.,Program in Molecular and Cellular Oncogenesis, The Wistar Institute, Philadelphia, PA, USA
| | - Peter Jo
- Department of General, Visceral and Pediatric Surgery, University Medical Center, Göttingen, Germany
| | - Julia Kitz
- Department of Pathology, University Medical Center, Göttingen, Germany
| | - Azadeh Azizian
- Department of General, Visceral and Pediatric Surgery, University Medical Center, Göttingen, Germany
| | - Yue Hu
- Section of Cancer Genomics, Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Clemens F Hess
- Department of Radiotherapy and Radio-oncology, University Medical Center, Göttingen, Germany
| | - Claus Roedel
- Department of Radiation Oncology, University Hospital Johann Wolfgang Goethe University, Frankfurt, Germany
| | - Ulrich Sax
- Department of Medical Informatics, University Medical Center, Göttingen, Germany
| | - Gabriela Salinas
- Transcriptome and Genome Analysis Laboratory (TAL), Department of Developmental Biochemistry, University of Göttingen, Göttingen, Germany
| | - Philipp Stroebel
- Department of Pathology, University Medical Center, Göttingen, Germany
| | - Frank Kramer
- Department of Medical Statistics, University Medical Center, Göttingen, Germany
| | - Tim Beissbarth
- Department of Medical Statistics, University Medical Center, Göttingen, Germany
| | - Marian Grade
- Department of General, Visceral and Pediatric Surgery, University Medical Center, Göttingen, Germany
| | - Michael Ghadimi
- Department of General, Visceral and Pediatric Surgery, University Medical Center, Göttingen, Germany
| | - Eytan Ruppin
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Thomas Ried
- Section of Cancer Genomics, Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jochen Gaedcke
- Department of General, Visceral and Pediatric Surgery, University Medical Center, Göttingen, Germany.
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23
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Sauerbrei W, Haeussler T, Balmford J, Huebner M. Structured reporting to improve transparency of analyses in prognostic marker studies. BMC Med 2022; 20:184. [PMID: 35546237 PMCID: PMC9095054 DOI: 10.1186/s12916-022-02304-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 02/17/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Factors contributing to the lack of understanding of research studies include poor reporting practices, such as selective reporting of statistically significant findings or insufficient methodological details. Systematic reviews have shown that prognostic factor studies continue to be poorly reported, even for important aspects, such as the effective sample size. The REMARK reporting guidelines support researchers in reporting key aspects of tumor marker prognostic studies. The REMARK profile was proposed to augment these guidelines to aid in structured reporting with an emphasis on including all aspects of analyses conducted. METHODS A systematic search of prognostic factor studies was conducted, and fifteen studies published in 2015 were selected, three from each of five oncology journals. A paper was eligible for selection if it included survival outcomes and multivariable models were used in the statistical analyses. For each study, we summarized the key information in a REMARK profile consisting of details about the patient population with available variables and follow-up data, and a list of all analyses conducted. RESULTS Structured profiles allow an easy assessment if reporting of a study only has weaknesses or if it is poor because many relevant details are missing. Studies had incomplete reporting of exclusion of patients, missing information about the number of events, or lacked details about statistical analyses, e.g., subgroup analyses in small populations without any information about the number of events. Profiles exhibit severe weaknesses in the reporting of more than 50% of the studies. The quality of analyses was not assessed, but some profiles exhibit several deficits at a glance. CONCLUSIONS A substantial part of prognostic factor studies is poorly reported and analyzed, with severe consequences for related systematic reviews and meta-analyses. We consider inadequate reporting of single studies as one of the most important reasons that the clinical relevance of most markers is still unclear after years of research and dozens of publications. We conclude that structured reporting is an important step to improve the quality of prognostic marker research and discuss its role in the context of selective reporting, meta-analysis, study registration, predefined statistical analysis plans, and improvement of marker research.
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Affiliation(s)
- Willi Sauerbrei
- Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
| | - Tim Haeussler
- Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - James Balmford
- Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Marianne Huebner
- Department of Statistics and Probability, Michigan State University, East Lansing, MI, USA
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24
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Patient-Derived Organoids of Colorectal Cancer: A Useful Tool for Personalized Medicine. J Pers Med 2022; 12:jpm12050695. [PMID: 35629118 PMCID: PMC9147270 DOI: 10.3390/jpm12050695] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 04/22/2022] [Accepted: 04/24/2022] [Indexed: 11/18/2022] Open
Abstract
Colorectal cancer is one of the most important malignancies worldwide, with high incidence and mortality rates. Several studies have been conducted using two-dimensional cultured cell lines; however, these cells do not represent a study model of patient tumors very well. In recent years, advancements in three-dimensional culture methods have facilitated the establishment of patient-derived organoids, which have become indispensable for molecular biology-related studies of colorectal cancer. Patient-derived organoids are useful in both basic science and clinical practice; they can help predict the sensitivity of patients with cancer to chemotherapy and radiotherapy and provide the right treatment to the right patient. Regarding precision medicine, combining gene panel testing and organoid-based screening can increase the effectiveness of medical care. In this study, we review the development of three-dimensional culture methods and present the most recent information on the clinical application of patient-derived organoids. Moreover, we discuss the problems and future prospects of organoid-based personalized medicine.
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25
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Verstockt B, Parkes M, Lee JC. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 2022; 162:1383-1395. [PMID: 34995535 DOI: 10.1053/j.gastro.2021.12.245] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 02/07/2023]
Abstract
Gastroenterologists will be all too familiar with the difficult decisions that managing inflammatory bowel disease often presents. How aggressively should I treat this patient? Do I expect them to have a mild or aggressive form of disease? Do they need a biologic? If so, which one? And when should I start it? The reality is that the answers that would be right for one patient might be disastrous for another. The growing therapeutic armamentarium will only make these decisions more difficult, and yet, we have seen how other specialties have begun to use the molecular heterogeneity in their diseases to provide some answers. Here, we review the progress that has been made in predicting the future for any given patient with inflammatory bowel disease-whether that is the course of disease that they will experience or whether or not they will respond to, or indeed tolerate, a particular therapy.
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Affiliation(s)
- Bram Verstockt
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, Katholieke Universiteit Leuven, Leuven, Belgium; Department of Chronic Diseases and Metabolism, Translational Research Center for Gastrointestinal Disorders-Inflammatory Bowel Disease (TARGID-IBD), Katholieke Universiteit Leuven, Leuven, Belgium
| | - Miles Parkes
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - James C Lee
- Genetic Mechanisms of Disease Laboratory, Francis Crick Institute, London, United Kingdom; Institute for Liver & Digestive Health, Royal Free London Hospital, University College London, London, United Kingdom.
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26
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Hendrikson J, Liu Y, Ng WH, Lee JY, Lim AH, Loh JW, Ng CCY, Ong WS, Tan JWS, Tan QX, Ng G, Shannon NB, Lim WK, Lim TKH, Chua C, Wong JSM, Tan GHC, So JBY, Yeoh KG, Teh BT, Chia CS, Soo KC, Kon OL, Tan IB, Chan JY, Teo MCC, Ong CAJ. Ligand-mediated PAI-1 inhibition in a mouse model of peritoneal carcinomatosis. Cell Rep Med 2022; 3:100526. [PMID: 35243423 PMCID: PMC8861959 DOI: 10.1016/j.xcrm.2022.100526] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 11/22/2021] [Accepted: 01/19/2022] [Indexed: 12/28/2022]
Abstract
Peritoneal carcinomatosis (PC) present a ubiquitous clinical conundrum in all intra-abdominal malignancies. Via functional and transcriptomic experiments of ascites-treated PC cells, we identify STAT3 as a key signaling pathway. Integrative analysis of publicly available databases and correlation with clinical cohorts (n = 7,359) reveal putative clinically significant activating ligands of STAT3 signaling. We further validate a 3-biomarker prognostic panel in ascites independent of clinical covariates in a prospective study (n = 149). Via single-cell sequencing experiments, we uncover that PAI-1, a key component of the prognostic biomarker panel, is largely secreted by fibroblasts and mesothelial cells. Molecular stratification of ascites using PAI-1 levels and STAT3 activation in ascites-treated cells highlight a therapeutic opportunity based on a phenomenon of paracrine addiction. These results are recapitulated in patient-derived ascites-dependent xenografts. Here, we demonstrate therapeutic proof of concept of direct ligand inhibition of a prognostic target within an enclosed biological space.
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Affiliation(s)
- Josephine Hendrikson
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Ying Liu
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Wai Har Ng
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Jing Yi Lee
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Abner Herbert Lim
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Jui Wan Loh
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Cedric C Y Ng
- Laboratory of Cancer Epigenome, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Whee Sze Ong
- Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Joey Wee-Shan Tan
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Qiu Xuan Tan
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Gillian Ng
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Nicholas B Shannon
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore 169609, Singapore.,Cancer and Stem Biology Signature Research Program, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Tony K H Lim
- Department of Anatomical Pathology, Singapore General Hospital, Singapore 169856, Singapore.,Pathology Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore 168753, Singapore
| | - Clarinda Chua
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Jolene Si Min Wong
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,SingHealth Duke-NUS Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore.,SingHealth Duke-NUS Surgery Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Grace Hwei Ching Tan
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore
| | - Jimmy Bok Yan So
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore.,Division of Surgical Oncology, National University Cancer Institute, National University Health System, Singapore 119074, Singapore
| | - Khay Guan Yeoh
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore.,Department of Gastroenterology and Hepatology, National University Hospital, Singapore 119074, Singapore
| | - Bin Tean Teh
- Laboratory of Cancer Epigenome, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore.,Institute of Molecular and Cell Biology, A∗STAR Research Entities, Singapore 138673, Singapore
| | - Claramae Shulyn Chia
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,SingHealth Duke-NUS Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore.,SingHealth Duke-NUS Surgery Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Khee Chee Soo
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore
| | - Oi Lian Kon
- Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Iain Beehuat Tan
- Cancer and Stem Biology Signature Research Program, Duke-NUS Medical School, Singapore 169857, Singapore.,Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore.,Laboratory of Applied Cancer Genomics, Genome Institute of Singapore, A∗STAR Research Entities, Singapore 138672, Singapore
| | - Jason Yongsheng Chan
- Cancer Discovery Hub, National Cancer Centre Singapore, Singapore 169610, Singapore.,Division of Medical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Melissa Ching Ching Teo
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore
| | - Chin-Ann J Ong
- Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, 11 Hospital Cresent, Singapore 169610, Singapore.,Department of Sarcoma, Peritoneal and Rare Tumours (SPRinT), Division of Surgery and Surgical Oncology, Singapore General Hospital, Singapore 169608, Singapore.,Laboratory of Applied Human Genetics, Division of Medical Sciences, National Cancer Centre Singapore, Singapore 169610, Singapore.,SingHealth Duke-NUS Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore.,SingHealth Duke-NUS Surgery Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore.,Institute of Molecular and Cell Biology, A∗STAR Research Entities, Singapore 138673, Singapore
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27
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A framework to predict the applicability of Oncotype DX, MammaPrint, and E2F4 gene signatures for improving breast cancer prognostic prediction. Sci Rep 2022; 12:2211. [PMID: 35140308 PMCID: PMC8828770 DOI: 10.1038/s41598-022-06230-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Accepted: 01/18/2022] [Indexed: 11/08/2022] Open
Abstract
To improve cancer precision medicine, prognostic and predictive biomarkers are critically needed to aid physicians in deciding treatment strategies in a personalized fashion. Due to the heterogeneous nature of cancer, most biomarkers are expected to be valid only in a subset of patients. Furthermore, there is no current approach to determine the applicability of biomarkers. In this study, we propose a framework to improve the clinical application of biomarkers. As part of this framework, we develop a clinical outcome prediction model (CPM) and a predictability prediction model (PPM) for each biomarker and use these models to calculate a prognostic score (P-score) and a confidence score (C-score) for each patient. Each biomarker’s P-score indicates its association with patient clinical outcomes, while each C-score reflects the biomarker applicability of the biomarker’s CPM to a patient and therefore the confidence of the clinical prediction. We assessed the effectiveness of this framework by applying it to three biomarkers, Oncotype DX, MammaPrint, and an E2F4 signature, which have been used for predicting patient response, pathologic complete response versus residual disease to neoadjuvant chemotherapy (a classification problem), and recurrence-free survival (a Cox regression problem) in breast cancer, respectively. In both applications, our analyses indicated patients with higher C scores were more likely to be correctly predicted by the biomarkers, indicating the effectiveness of our framework. This framework provides a useful approach to develop and apply biomarkers in the context of cancer precision medicine.
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28
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Li Y, Yang X, Sun J, Zhao Y, Zhou Q, Hua B. ADAMTS8 Expression is a Potential Prognostic Biomarker for Postoperative Metastasis in Lymph Node-Negative Early-Stage Invasive Breast Carcinoma Patients. Pharmgenomics Pers Med 2022; 14:1701-1713. [PMID: 35002288 PMCID: PMC8722701 DOI: 10.2147/pgpm.s339919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 12/15/2021] [Indexed: 11/23/2022] Open
Abstract
Purpose Invasive breast carcinoma (BC) is the most common malignant breast tumor. Most lymph node-negative (LN-) early-stage BC patients usually have a good prognosis, but 7% of patients still develop metastasis after surgery. It is not yet clear how to screen candidates with poorer prognosis in LN- early-stage patients, so that they can receive intensive therapy. Hence, we expect to identify a prognostic biomarker to assess postoperative metastasis in LN- early-stage BC patients. Patients and Methods Screening and verifying of candidate genes by gene expression profiling of LN- early-stage BC samples (n = 640) from 3 independent public datasets. Univariable and multivariable Cox regression analyses showed the relation between the candidate genes and postoperative metastasis. Distant metastasis-free survival (DMFS) analysis was performed to examine the prognostic significance. Quantitative real-time polymerase chain reaction (qRT-PCR) assays were performed to examine ADAMTS8 expression and prognostic association in our clinical samples (n = 25). Results In the discovery cohort (TCGA and GSE20685 datasets), we found that ADAMTS8 tend to be low expression in LN- early-stage BC, and low ADAMTS8 expression was associated with postoperative metastasis and shortened DMFS. Moreover, the above finding was confirmed in the validation cohort (GSE6538 dataset). Lower ADAMTS8 expression was related to poorer prognostic clinical stage and PAM50 subtypes and shorter DMFS. Gene enrichment analysis indicated that ADAMTS8 may be correlated with BC metastasis. qRT-PCR assays of our clinical tumor sample showed that patients with low ADAMTS8 expression seem to be prone to developing metastasis and have a shorter DMFS time. Conclusion Our research shows that low ADAMTS8 expression is associated with postoperative metastasis and shortened DMFS in LN- early-stage BC patients, which suggests that ADAMTS8 may be a potential prognostic marker for postoperative metastasis in LN- early-stage BC patients.
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Affiliation(s)
- Yao Li
- Breast Center, Department of Thyroid-Breast-Hernia Surgery, Department of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
| | - Xin Yang
- Breast Center, Department of Thyroid-Breast-Hernia Surgery, Department of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
| | - Jie Sun
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
| | - Yangyang Zhao
- The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
| | - Qi Zhou
- The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
| | - Bin Hua
- Breast Center, Department of Thyroid-Breast-Hernia Surgery, Department of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China
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29
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The Diagnostic Value of the CA19-9 and Bilirubin Ratio in Patients with Pancreatic Cancer, Distal Bile Duct Cancer and Benign Periampullary Diseases, a Novel Approach. Cancers (Basel) 2022; 14:cancers14020344. [PMID: 35053506 PMCID: PMC8774022 DOI: 10.3390/cancers14020344] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 01/06/2022] [Accepted: 01/07/2022] [Indexed: 12/13/2022] Open
Abstract
Distinction of pancreatic ductal adenocarcinoma (PDAC) in the head of the pancreas, distal cholangiocarcinoma (dCCA), and benign periampullary conditions, is complex as they often share similar clinical symptoms. However, these diseases require specific management strategies, urging improvement of non-invasive tools for accurate diagnosis. Recent evidence has shown that the ratio between CA19-9 and bilirubin levels supports diagnostic distinction of benign or malignant hepatopancreaticobiliary diseases. Here, we investigate the diagnostic value of this ratio in PDAC, dCCA and benign diseases of the periampullary region in a novel fashion. To address this aim, we enrolled 265 patients with hepatopancreaticobiliary diseases and constructed four logistic regression models on a subset of patients (n = 232) based on CA19-9, bilirubin and the ratio of both values: CA19-9/(bilirubin-1). Non-linearity was investigated using restricted cubic splines and a final model, the 'Model Ratio', based on these three variables was fitted using multivariable fractional polynomials. The performance of this model was consistently superior in terms of discrimination and calibration compared to models based on CA19-9 combined with bilirubin and CA19-9 or bilirubin alone. The 'Model Ratio' accurately distinguished between malignant and benign disease (AUC [95% CI], 0.91 [0.86-0.95]), PDAC and benign disease (AUC 0.91 [0.87-0.96]) and PDAC and dCCA (AUC 0.83 [0.74-0.92]) which was confirmed by internal validation using 1000 bootstrap replicates. These findings provide a foundation to improve minimally-invasive diagnostic procedures, ultimately ameliorating effective therapy for PDAC and dCCA.
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30
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Bruun J, Eide PW, Bergsland CH, Bruck O, Svindland A, Arjama M, Välimäki K, Bjørnslett M, Guren MG, Kallioniemi O, Nesbakken A, Lothe RA, Pellinen T. E-cadherin is a robust prognostic biomarker in colorectal cancer and low expression is associated with sensitivity to inhibitors of topoisomerase, aurora, and HSP90 in preclinical models. Mol Oncol 2021; 16:2312-2329. [PMID: 34890102 PMCID: PMC9208074 DOI: 10.1002/1878-0261.13159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/10/2021] [Accepted: 12/09/2021] [Indexed: 12/24/2022] Open
Abstract
Cell–cell and cell–matrix adhesion proteins that have been implicated in colorectal epithelial integrity and epithelial‐to‐mesenchymal transition could be robust prognostic and potential predictive biomarkers for standard and novel therapies. We analyzed in situ protein expression of E‐cadherin (ECAD), integrin β4 (ITGB4), zonula occludens 1 (ZO‐1), and cytokeratins in a single‐hospital series of Norwegian patients with colorectal cancer (CRC) stages I–IV (n = 922) using multiplex fluorescence‐based immunohistochemistry (mfIHC) on tissue microarrays. Pharmacoproteomic associations were explored in 35 CRC cell lines annotated with drug sensitivity data on > 400 approved and investigational drugs. ECAD, ITGB4, and ZO‐1 were positively associated with survival, while cytokeratins were negatively associated with survival. Only ECAD showed independent prognostic value in multivariable Cox models. Clinical and molecular associations for ECAD were technically validated on a different mfIHC platform, and the prognostic value was validated in another Norwegian series (n = 798). In preclinical models, low and high ECAD expression differentially associated with sensitivity to topoisomerase, aurora, and HSP90 inhibitors, and EGFR inhibitors. E‐cadherin protein expression is a robust prognostic biomarker with potential clinical utility in CRC.
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Affiliation(s)
- Jarle Bruun
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, Norway.,K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway
| | - Peter W Eide
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, Norway.,K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway
| | - Christian Holst Bergsland
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, Norway.,K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway
| | - Oscar Bruck
- Hematology Research Unit Helsinki, University of Helsinki and Comprehensive Cancer Center, Helsinki University Hospital, Finland
| | - Aud Svindland
- K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway.,Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Norway.,Department of Pathology, Oslo University Hospital, Norway
| | - Mariliina Arjama
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Finland
| | - Katja Välimäki
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Finland
| | - Merete Bjørnslett
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, Norway.,K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway
| | - Marianne G Guren
- K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway.,Department of Oncology, Oslo University Hospital, Norway
| | - Olli Kallioniemi
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Finland.,Science for Life Laboratory, Department of Oncology & Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Arild Nesbakken
- K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway.,Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Norway.,Department of Gastrointestinal Surgery, Oslo University Hospital, Norway
| | - Ragnhild A Lothe
- Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, Norway.,K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway.,Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Norway
| | - Teijo Pellinen
- K.G. Jebsen Colorectal Cancer Research Centre, Division for Cancer Medicine, Oslo University Hospital, Norway.,Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Finland
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31
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Seo MK, Strong M. A Practical Guide to Modeling and Conducting a Cost-Effectiveness Analysis of Companion Biomarker Tests for Targeted Therapies Using R: Tutorial Paper. PHARMACOECONOMICS 2021; 39:1373-1381. [PMID: 34414545 PMCID: PMC8599329 DOI: 10.1007/s40273-021-01069-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/13/2021] [Indexed: 06/13/2023]
Abstract
Despite the increasing number of potential biomarkers identified in laboratories and reported in much literature, the adoption of biomarkers routinely available in clinical practice to inform treatment decisions is very limited. Reimbursement decisions for new health technologies are often informed by economic evaluations; however, economic evaluations of diagnostics/testing technologies, such as companion biomarker tests, are far less frequently reported than drugs. Furthermore, few countries provide the health economic evaluation methods guide specific to co-dependent technologies such as companion diagnostics or precision medicines. Therefore, this paper aims to guide the process of the development of cost-effectiveness models of cancer biomarkers for targeted therapies, focusing on companion diagnostics. This tutorial paper provides practical guidance on how to conduct economic evaluations of cancer biomarkers and how to model the characteristics of the biomarker tests as part of the value for money of corresponding targeted therapies. This paper presents a brief introduction to the methods and data requirements, a step-by-step guide to constructing a health economic model of companion cancer biomarkers, and a discussion of issues that arise in their application to healthcare decision making. This practical guidance is provided in R, and worked examples are provided in this paper with R codes in the accompanying electronic supplementary material.
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Affiliation(s)
- Mikyung Kelly Seo
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.
- Centre for Cancer Biomarkers (CCBIO), University of Bergen, Bergen, Norway.
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
| | - Mark Strong
- School of Health and Related Research, University of Sheffield, Sheffield, UK
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Zhou C, Wang S, Shen Z, Shen Y, Li Q, Shen Y, Huang J, Deng H, Ye D, Zhan G, Li J. Construction of an m6A-related lncRNA pair prognostic signature and prediction of the immune landscape in head and neck squamous cell carcinoma. J Clin Lab Anal 2021; 36:e24113. [PMID: 34783061 PMCID: PMC8761472 DOI: 10.1002/jcla.24113] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 10/19/2021] [Accepted: 10/29/2021] [Indexed: 01/01/2023] Open
Abstract
Background Mounting evidence indicates that aberrantly expressed N6‐methylandenosine (m6A) modification regulators and long noncoding RNA (lncRNA) influence the development of head and neck squamous cell carcinoma (HNSCC). However, the prognosis of m6A‐related lncRNA (mrlncRNA) in HNSCC has not yet been evaluated. Methods We retrieved transcriptome, somatic mutation, and clinical information from The Cancer Genome Atlas database and established a differently expressed mrlncRNA (DEmrlncRNA) pair signature based on least absolute shrinkage and selection operator Cox regression and multivariate Cox analyses. Each sample's risk score was computed premised on the signature, which accurately classified patients into low‐ and high‐risk group by the cut‐off point. The signature was evaluated from the perspective of survival, clinicopathological characteristics, tumor mutation burden (TMB), immune cell infiltration, efficacy of chemotherapeutics, tumor immune microenvironment, and immune checkpoint inhibitor (ICI)‐related genes. Results 11 DEmrlncRNA pairs were identified and were used to construct the prediction signature. Kaplan–Meier plotter revealed a worse prognosis in high‐risk patients over low‐risk patients (log rank p < 0.001). According to multivariate Cox regression analysis, the hazard ratio of the risk score and 95% confidence interval of 1.722 and (1.488–1.992) (p < 0.001) were obtained. Furthermore, an increased risk score was associated with aggressive clinicopathological features, specific tumor immune infiltration status, increased expression of ICI‐related genes, higher TMB, and higher chemotherapeutics sensitivity (all p < 0.05). Conclusion This research demonstrated that the signature premised on DEmrlncRNA pairs was an efficient independent prognostic indicator and may provide a rationale for research on immunotherapeutic and chemotherapeutics strategies for HNSCC patients.
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Affiliation(s)
- Chongchang Zhou
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Shumin Wang
- Department of StomatologyHuashan HospitalFudan UniversityShanghaiChina
| | - Zhisen Shen
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Yiming Shen
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Qun Li
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Yi Shen
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Juntao Huang
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Hongxia Deng
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Dong Ye
- Department of Otorhinolaryngology Head and Neck SurgeryNingbo Medical Center Lihuili HospitalNingboChina
- Department of Otorhinolaryngology Head and Neck SurgeryLihuili Hospital affiliated to Ningbo UniversityNingboChina
| | - Guowen Zhan
- Department of Otolaryngology Head and Neck SurgeryNingbo Yinzhou Second HospitalNingboChina
| | - Jinyun Li
- Department of Oncology and HematologyThe Affiliated Hospital of Medical School of Ningbo UniversityNingboChina
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Van Den Bosch T, van Dijk E, Vermeulen L, Miedema DM. Predicting survival of cancer patients by chromosomal copy number heterogeneity. Mol Cell Oncol 2021; 8:1949956. [PMID: 34616875 PMCID: PMC8489936 DOI: 10.1080/23723556.2021.1949956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
We recently introduced a method to derive intra-tumor heterogeneity (ITH) from a single copy number measurement. This method stratifies patients for survival and could potentially help to identify low and high-risk patients with clinical relevance.
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Affiliation(s)
- Tom Van Den Bosch
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Oncode Institute, Amsterdam, The Netherlands
| | - Erik van Dijk
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Louis Vermeulen
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Oncode Institute, Amsterdam, The Netherlands
| | - Daniël M Miedema
- LEXOR, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Oncode Institute, Amsterdam, The Netherlands
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Zhu J, Zhao L, Hu Y, Cui G, Luo A, Bao C, Han Y, Zhou T, Lu W, Wang J, Black SM, Tang H. Hypoxia-Inducible Factor 2-Alpha Mediated Gene Sets Differentiate Pulmonary Arterial Hypertension. Front Cell Dev Biol 2021; 9:701247. [PMID: 34422822 PMCID: PMC8375387 DOI: 10.3389/fcell.2021.701247] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/16/2021] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVES HIF2α is of vital importance in the regulation of endothelial dysfunction, cell proliferation, migration, and pulmonary vascular remodeling in pulmonary hypertension. Our previous studies demonstrated that conditional and inducible deletion of HIF2α in mouse lung endothelial cells, dramatically protected the mice against vascular remodeling and the development of pulmonary arterial hypertension (PAH). Here, we provide a novel transcriptome insight into the impact of HIF2α in PAH pathogenesis and the potential to use HIF2α-mediated gene sets to differentiate PAH human subjects. METHODS Using transcriptome data, we first tapped the value of the difference in gene expression profile between wild type (WT) and Hif2a knockdown (KD) cell lines. We considered the deregulated genes between WT and Hif2a-KD cells as HIF2α influenced genes. By examining the lung tissue transcriptome data set with nine controls and eight PAH patients, we evaluated the HIF2α regulatory network in PAH pathogenesis to further determine the identification ability of HIF2α-mediated gene sets in human PAH subjects. On the other hand, using peripheral blood mononuclear cells (PBMCs) transcriptome data from PAH patients and healthy controls, we further validated the potential of the HIF2α-mediated PBMC gene sets as a possible diagnostic tool for PAH. To verify the ability of HIF2α-mediated gene sets for the identification of PAH, endothelial cell-specific Phd2 knockout mice with spontaneous pulmonary hypertension were used for reverse validation experiments. RESULTS 19 identified GO biological process terms were significantly correlated with the genes down-regulated in Hif2a-KD cells, all of which are strongly related to the PAH pathogenesis. We further assessed the discriminative power of these HIF2α-mediated gene sets in PAH human subjects. We found that the expression profile of the HIF2α-mediated gene sets in lung tissues and PBMCs were differentiated both between controls and PAH patients. Further, a significant positive correlation was observed between hypoxia and Phd2 deficiency mediated gene set expression profiles. As expected, 7 of the 19 significantly down-regulated GO terms in Hif2a-KD cells were found to overlap with the up-regulated GO gene sets in Phd2 EC-/- mice compared to WT controls, suggesting opposing effects of HIF2α and PHD2 on PAH pathogenesis. CONCLUSION HIF2α-mediated gene sets may be used to differentiate pulmonary arterial hypertension.
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Affiliation(s)
- Jinsheng Zhu
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
| | - Li Zhao
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
| | - Yadan Hu
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
| | - Guoqi Cui
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
| | - Ang Luo
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
| | - Changlei Bao
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
| | - Ying Han
- Department of Physiology, Nanjing Medical University, Nanjing, China
| | - Tong Zhou
- Department of Physiology and Cell Biology, University of Nevada School of Medicine, Reno, NV, United States
| | - Wenju Lu
- State Key Laboratory of Respiratory Disease, Guangdong Key Laboratory of Vascular Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jian Wang
- State Key Laboratory of Respiratory Disease, Guangdong Key Laboratory of Vascular Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Stephen M. Black
- Department of Cellular Biology and Pharmacology, Herbert Wertheim College of Medicine, Miami, FL, United States
- Department of Environmental Health Sciences, Robert Stempel College of Public Health and Social Work, Miami, FL, United States
- Center for Translational Science, Florida International University, Port St. Lucie, FL, United States
| | - Haiyang Tang
- College of Veterinary Medicine, Northwest A&F University, Xianyang, China
- State Key Laboratory of Respiratory Disease, Guangdong Key Laboratory of Vascular Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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Primary metabolic tumor volume from 18F-FDG PET/CT associated with epidermal growth factor receptor mutation in lung adenocarcinoma patients. Nucl Med Commun 2021; 41:1210-1217. [PMID: 32815896 DOI: 10.1097/mnm.0000000000001274] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
PURPOSE To explore the potential parameters from F-FDG PET/CT that might be associated with the epidermal growth factor receptor (EGFR) gene mutation status in lung adenocarcinoma (ADC) patients. METHODS Data of the test cohort of 191 patients and the validation cohort of 55 patients with newly diagnosed ADC were retrospectively reviewed. All patients underwent F-FDG PET/CT scans and EGFR mutation tests prior to treatment. The metabolic parameters obtained from F-FDG PET/CT combining with clinical characteristics were analyzed by using univariate and multivariate logistic regression analyses. Then two cohorts were enrolled to validate the predictive model by area under the receiver-operating characteristic curve (AUC), respectively. RESULTS EGFR mutation-positive was seen of 33.0% (63/191) and 32.7% (18/55) in two cohorts, respectively. In univariate analysis, female, nonsmokers, metabolic parameters of primary tumor [mean standardized uptake value, metabolic tumor volume (pMTV), and total lesion glycolysis], non-necrosis of primary tumor, and serum tumor markers [carbohydrate antigen 19-9, squamous cell carcinoma antigen, and precursor of gastrin releasing peptide (proGRP)] were significantly relevant with EGFR mutation. In multivariate analysis with adjustment of age and TNM stage, pMTV (<8.13 cm), proGRP (≥38.44 pg/ml) and women were independent significant predictors for EGFR mutation. The AUC for the predictive value of these factors was 0.739 [95% confidence interval (CI) 0.665-0.813] in the cohort of 191 patients and 0.716 (95% CI 0.567-0.865) in the cohort of 55 patients, respectively. CONCLUSION Low pMTV (<8.13 cm) was an independent predictor and could be integrated with women and high proGRP (≥38.44 pg/ml) to enhance the discriminability on the EGFR mutation status in ADC patients.
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Creemers JHA, Lesterhuis WJ, Mehra N, Gerritsen WR, Figdor CG, de Vries IJM, Textor J. A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery. J Immunother Cancer 2021; 9:jitc-2020-002032. [PMID: 34059522 PMCID: PMC8169479 DOI: 10.1136/jitc-2020-002032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/06/2021] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Predicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice. METHODS A computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs. RESULTS Our model shows that a tipping point-a sharp state transition between immune control and immune evasion-induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments. CONCLUSION These findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patient's distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for patients with cancer.
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Affiliation(s)
- Jeroen H A Creemers
- Department of Tumor Immunology, Radboudumc, Nijmegen, The Netherlands.,Oncode Institute, Nijmegen, The Netherlands
| | - W Joost Lesterhuis
- School of Biomedical Sciences and Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
| | - Niven Mehra
- Department of Medical Oncology, Radboudumc, Nijmegen, The Netherlands
| | | | - Carl G Figdor
- Department of Tumor Immunology, Radboudumc, Nijmegen, The Netherlands.,Oncode Institute, Nijmegen, The Netherlands
| | | | - Johannes Textor
- Department of Tumor Immunology, Radboudumc, Nijmegen, The Netherlands .,Data Science Department, Radboud University Institute for Computing and Information Sciences, Nijmegen, The Netherlands
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Liu J, Sun G, Pan S, Qin M, Ouyang R, Li Z, Huang J. The Cancer Genome Atlas (TCGA) based m 6A methylation-related genes predict prognosis in hepatocellular carcinoma. Bioengineered 2021; 11:759-768. [PMID: 32631107 PMCID: PMC8291839 DOI: 10.1080/21655979.2020.1787764] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The current study aims to investigate the significance of N6-methyladenosine (m6A) methylation-related genes in the clinical prognosis of hepatocellular carcinoma (HCC) using bioinformatics analyses based on The Cancer Genome Atlas (TCGA) database. Transcriptome data and corresponding clinical data on m6A methylation-related genes (including 15 genes) were obtained from TCGA database. Differential expression of 15 genes was identified. Survival curves of subgroups based on m6A methylation-related gene expression levels were plotted. We selected potential predictive genes and analyzed their prognostic values using bioinformatics methods. Eleven genes (METTL3, YTHDF1, YTHDF2, YTHDF3, YTHDC1, YTHDC2, FTO, KIAA1429, HNRNPC, HNRNPA2B1, and RBM15) were found to be overexpressed in HCC. Of these, five genes had worse survival (P < 0.05). There was a significant difference in the survival rate between subgroups with different expression levels of m6A. We selected five potential predictors (METTL3, KIAA1429, ZC3H13, YTHDF1, and YTHDF2) that met the independent predictive value. ZC3H13 was upregulated in patients with high cancer risk, whereas METTL3, KIAA1429, YTHDF1, and YTHDF2 were downregulated. In summary, we found that the expression levels of m6A methylation-related genes were different in patients with HCC and correlated with survival and prognosis. This implies that m6A methylation-related genes may be promising prognostic indicators or therapeutic targets for HCC.
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Affiliation(s)
- Jun Liu
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University , Nanning, China.,Department of Gastroenterology, The Fourth Affiliated Hospital of Guangxi Medical University/Liu Zhou Worker's Hospital , Liuzhou, China
| | - Guili Sun
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University , Nanning, China
| | - Shangling Pan
- Departments of Pathophysiology, Guangxi Medical University , Nanning, P.R. China
| | - Mengbin Qin
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University , Nanning, China
| | - Rong Ouyang
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University , Nanning, China.,Department of Gastroenterology, The Fourth Affiliated Hospital of Guangxi Medical University/Liu Zhou Worker's Hospital , Liuzhou, China
| | - Zhongzhuan Li
- Department of Gastroenterology, The Fourth Affiliated Hospital of Guangxi Medical University/Liu Zhou Worker's Hospital , Liuzhou, China
| | - Jiean Huang
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University , Nanning, China
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Joosten SC, Odeh SNO, Koch A, Buekers N, Aarts MJB, Baldewijns MMLL, Van Neste L, van Kuijk S, Schouten LJ, van den Brandt PA, Tjan-Heijnen VC, van Engeland M, Smits KM. Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers. Clin Epigenetics 2021; 13:103. [PMID: 33947447 PMCID: PMC8094610 DOI: 10.1186/s13148-021-01084-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 04/19/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC). PATIENTS AND METHODS Promoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used. RESULTS Methylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model. CONCLUSION In this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors.
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Affiliation(s)
- S C Joosten
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
- Department of Medical Oncology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - S N O Odeh
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - A Koch
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - N Buekers
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - M J B Aarts
- Department of Medical Oncology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | | | - L Van Neste
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - S van Kuijk
- Department of Clinical Epidemiology and Medical Technology Assessment, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - L J Schouten
- Department of Epidemiology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - P A van den Brandt
- Department of Epidemiology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - V C Tjan-Heijnen
- Department of Medical Oncology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - M van Engeland
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - K M Smits
- Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands.
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Trifonova OP, Maslov DL, Balashova EE, Lokhov PG. Mass spectrometry-based metabolomics diagnostics - myth or reality? Expert Rev Proteomics 2021; 18:7-12. [PMID: 33653222 DOI: 10.1080/14789450.2021.1893695] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
ABSTACTIntroduction: Metabolomics, one of the most high-promising technologies, is the most recently developed post-genomics discipline for developing new diagnostic tests for future implementation in medicine. More than 2,000 scientific papers, using mass spectrometry-based (MS-based) metabolomics analysis for human disease diagnostics, have been published during the past two decades, and almost every metabolomics study shows high diagnostic accuracy. However, despite the great results and promising perspectives, there are currently no diagnostic tests based on metabolomics that have been approved and introduced into clinics.Areas covered: In this report, the advantages and challenges of MS-based metabolomics are discussed with a focus on its developing role in diagnostics, and the current trends in implementing metabolomics diagnostics in the clinic.Expert opinion: In the development of new clinical diagnostics tests, MS-based metabolomics has potential as both a preliminary discovery base for routine testing and a multi-test prototype, which is hoped to be introduced into clinical practice in the near future. A laboratory-developed test (LDT) is one possible way that multi-testing could be developed.
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Affiliation(s)
- Oxana P Trifonova
- Analytical Branch, Laboratory of Mass Spectrometry-based Metabolomic Diagnostic, Institute of Biomedical Chemistry, Moscow, Russia
| | - Dmitri L Maslov
- Analytical Branch, Laboratory of Mass Spectrometry-based Metabolomic Diagnostic, Institute of Biomedical Chemistry, Moscow, Russia
| | - Elena E Balashova
- Analytical Branch, Laboratory of Mass Spectrometry-based Metabolomic Diagnostic, Institute of Biomedical Chemistry, Moscow, Russia
| | - Petr G Lokhov
- Analytical Branch, Laboratory of Mass Spectrometry-based Metabolomic Diagnostic, Institute of Biomedical Chemistry, Moscow, Russia
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Veigas F, Mahmoud YD, Merlo J, Rinflerch A, Rabinovich GA, Girotti MR. Immune Checkpoints Pathways in Head and Neck Squamous Cell Carcinoma. Cancers (Basel) 2021; 13:cancers13051018. [PMID: 33804419 PMCID: PMC7957692 DOI: 10.3390/cancers13051018] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/16/2021] [Accepted: 02/25/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary During the last decades, scientific advances in immuno-oncology and a better understanding of tumors’ immune profile led to the development of novel immunotherapeutic strategies, especially immune checkpoint inhibitors. The blockade of PD-1 by monoclonal antibodies (mAbs) is the only immunotherapy based on immune checkpoint pathways approved for head and neck squamous cell carcinoma. As only a small fraction of patients perceives clinical benefit, understanding the molecular mechanisms and signaling pathways activated by the immune checkpoints and other tumor intrinsic features that modulate the immune infiltrate is crucial to better select patients for immunotherapy treatment and to develop novel therapeutic strategies. We here review the immune escape mechanisms of head and neck tumors, with a particular focus on the immune checkpoints, their role as therapeutic targets, and the predictive biomarkers of response to anti-PD-1/PD-L1 therapy. We also summarize the ongoing clinical trials testing several combinations of immune checkpoint inhibitors with other therapeutic approaches to improve patient outcomes. Abstract Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous group of tumors usually diagnosed at an advanced stage and characterized by a poor prognosis. The main risk factors associated with its development include tobacco and alcohol consumption and Human Papillomavirus (HPV) infections. The immune system has a significant role in the oncogenesis and evolution of this cancer type. Notably, the immunosuppressive tumor microenvironment triggers immune escape through several mechanisms. The improved understanding of the antitumor immune response in solid tumors and the role of the immune checkpoint molecules and other immune regulators have led to the development of novel therapeutic strategies that revolutionized the clinical management of HNSCC. However, the limited overall response rate to immunotherapy urges identifying predictive biomarkers of response and resistance to treatment. Here, we review the role of the immune system and immune checkpoint pathways in HNSCC, the most relevant clinical findings linked to immunotherapeutic strategies and predictive biomarkers of response and future treatment perspectives.
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Affiliation(s)
- Florencia Veigas
- Laboratorio de Inmuno Oncología Traslacional, Instituto of Biología y Medicina Experimental, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428ADN, Argentina; (F.V.); (Y.D.M.); (J.M.)
| | - Yamil D. Mahmoud
- Laboratorio de Inmuno Oncología Traslacional, Instituto of Biología y Medicina Experimental, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428ADN, Argentina; (F.V.); (Y.D.M.); (J.M.)
| | - Joaquin Merlo
- Laboratorio de Inmuno Oncología Traslacional, Instituto of Biología y Medicina Experimental, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428ADN, Argentina; (F.V.); (Y.D.M.); (J.M.)
| | - Adriana Rinflerch
- Laboratorio GIGA, Facultad de Ciencias Exactas, Químicas y Naturales, Instituto de Biología Subtropical, Universidad Nacional de Misiones, CONICET, Posadas N3300NFK, Misiones, Argentina;
| | - Gabriel Adrian Rabinovich
- Laboratorio de Inmunopatología, Instituto of Biología y Medicina Experimental, CONICET, Buenos Aires C1428ADN, Argentina;
- Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires C1428EGA, Argentina
| | - María Romina Girotti
- Laboratorio de Inmuno Oncología Traslacional, Instituto of Biología y Medicina Experimental, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires C1428ADN, Argentina; (F.V.); (Y.D.M.); (J.M.)
- Correspondence:
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Ikeda C, Haga H, Makino N, Inuzuka T, Kurimoto A, Ueda T, Matsuda A, Kakizaki Y, Ishizawa T, Kobayashi T, Sugahara S, Tsunoda M, Suda K, Ueno Y. Utility of Claudin-3 in extracellular vesicles from human bile as biomarkers of cholangiocarcinoma. Sci Rep 2021; 11:1195. [PMID: 33441949 PMCID: PMC7807063 DOI: 10.1038/s41598-021-81023-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 12/30/2020] [Indexed: 12/11/2022] Open
Abstract
Extracellular vesicles (EVs) are released from all cells. Bile directly contacts bile duct tumor; bile-derived EVs may contain high concentrations of cancer biomarkers. We performed a proteomic analysis of human bile-derived EVs and identified a novel biomarker of cholangiocarcinoma (CCA). EVs were isolated using ultracentrifugation, and chelating agents, ethylenediaminetetraacetic acid and ethylene glycol tetraacetic acid (EDEG) and phosphate buffered saline (PBS) were used as dissolution solutions. Bile was collected from 10 CCA and 10 choledocholithiasis (stones) cases. Proteomic analysis was performed; subsequently, ELISA was performed using the candidate biomarkers in a verification cohort. The vesicles isolated from bile had a typical size and morphology. The expression of exosome markers was observed. RNA was more abundant in the EDEG group. The proportion of microRNA was higher in the EDEG group. EDEG use resulted in the removal of more contaminants. Proteomic analysis identified 166 proteins as CCA-specific. ELISA for Claudin-3 revealed statistically significant difference. The diagnostic accuracy was AUC 0.945 and sensitivity and specificity were 87.5%. We report the first use of EDEG in the isolation of EVs from human bile and the proteomic analysis of human bile-derived EV-proteins in CCA. Claudin-3 in bile-derived EVs is a useful biomarker for CCA.
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Affiliation(s)
- Chisaki Ikeda
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Hiroaki Haga
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan.
| | - Naohiko Makino
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Tatsutoshi Inuzuka
- H.U. Group Research Institute G.K., 51 Komiyamachi, Hachioji, Tokyo, 192-0031, Japan
| | - Ayako Kurimoto
- H.U. Group Research Institute G.K., 51 Komiyamachi, Hachioji, Tokyo, 192-0031, Japan
| | - Toshiki Ueda
- H.U. Group Research Institute G.K., 51 Komiyamachi, Hachioji, Tokyo, 192-0031, Japan
| | - Akiko Matsuda
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Yasuharu Kakizaki
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Tetsuya Ishizawa
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Toshikazu Kobayashi
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Shinpei Sugahara
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Michihiko Tsunoda
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Kensei Suda
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
| | - Yoshiyuki Ueno
- Department of Gastroenterology, Faculty of Medicine, Yamagata University, 2-2-2 Iidanishi, Yamagata, Yamagata, 990-8595, Japan
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Poulsen TBG, Karamehmedovic A, Aboo C, Jørgensen MM, Yu X, Fang X, Blackburn JM, Nielsen CH, Kragstrup TW, Stensballe A. Protein array-based companion diagnostics in precision medicine. Expert Rev Mol Diagn 2020; 20:1183-1198. [PMID: 33315478 DOI: 10.1080/14737159.2020.1857734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities. AREA COVERED This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests. EXPERT OPINION Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.
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Affiliation(s)
- Thomas B G Poulsen
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark.,Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China
| | - Azra Karamehmedovic
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark.,Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China
| | - Christopher Aboo
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark.,Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China
| | - Malene Møller Jørgensen
- Department of Clinical Immunology, Aalborg University Hospital , Aalborg, Denmark.,Department of Clinical Medicine, Aalborg University , Aalborg, Denmark
| | - Xiaobo Yu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics , Beijing, China
| | - Xiangdong Fang
- Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences , China
| | - Jonathan M Blackburn
- Department of Integrative Biomedical Sciences & Institute of Infectious Disease and Molecular Medicine, University of Cape Town , Cape Town, South Africa.,Sengenics Corporation Pte Ltd , Singapore
| | - Claus H Nielsen
- Institute for Inflammation Research, Center for Rheumatology and Spine Diseases, Copenhagen University Hospital Rigshospitalet , Copenhagen, Denmark
| | - Tue W Kragstrup
- Department of Biomedicine, Aarhus University , Aarhus, Denmark.,Department of Rheumatology, Aarhus University Hospital , Aarhus, Denmark
| | - Allan Stensballe
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark
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Bime C, Camp SM, Casanova N, Oita RC, Ndukum J, Lynn H, Garcia JGN. The acute respiratory distress syndrome biomarker pipeline: crippling gaps between discovery and clinical utility. Transl Res 2020; 226:105-115. [PMID: 32599095 PMCID: PMC7319618 DOI: 10.1016/j.trsl.2020.06.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 06/17/2020] [Accepted: 06/23/2020] [Indexed: 12/14/2022]
Abstract
Recent innovations in translational research have ushered an exponential increase in the discovery of novel biomarkers, thereby elevating the hope for deeper insights into "personalized" medicine approaches to disease phenotyping and care. However, a critical gap exists between the fast pace of biomarker discovery and the successful translation to clinical use. This gap underscores the fundamental biomarker conundrum across various acute and chronic disorders: how does a biomarker address a specific unmet need? Additionally, the gap highlights the need to shift the paradigm from a focus on biomarker discovery to greater translational impact and the need for a more streamlined drug approval process. The unmet need for biomarkers in acute respiratory distress syndrome (ARDS) is for reliable and validated biomarkers that minimize heterogeneity and allow for stratification of subject selection for enrollment in clinical trials of tailored therapies. This unmet need is particularly highlighted by the ongoing SARS-CoV-2/COVID-19 pandemic. The unprecedented numbers of COVID-19-induced ARDS cases has strained health care systems across the world and exposed the need for biomarkers that would accelerate drug development and the successful phenotyping of COVID-19-infected patients at risk for development of ARDS and ARDS mortality. Accordingly, this review discusses the current state of ARDS biomarkers in the context of the drug development pipeline and highlight gaps between biomarker discovery and clinical implementation while proposing potential paths forward. We discuss potential ARDS biomarkers by category and by context of use, highlighting progress in the development continuum. We conclude by discussing challenges to successful translation of biomarker candidates to clinical impact and proposing possible novel strategies.
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Affiliation(s)
- Christian Bime
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona.
| | - Sara M Camp
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona
| | - Nancy Casanova
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona
| | - Radu C Oita
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona
| | - Juliet Ndukum
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona
| | - Heather Lynn
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona
| | - Joe G N Garcia
- College of Medicine, University of Arizona Health Sciences, Tucson, Arizona
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Iafolla MAJ, Picardo S, Aung K, Hansen AR. Systematic Review and STARD Scoring of Renal Cell Carcinoma Circulating Diagnostic Biomarker Manuscripts. JNCI Cancer Spectr 2020; 4:pkaa050. [PMID: 33134830 PMCID: PMC7583155 DOI: 10.1093/jncics/pkaa050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 05/14/2020] [Accepted: 06/01/2020] [Indexed: 01/23/2023] Open
Abstract
Background No validated molecular biomarkers exist to help guide diagnosis of renal cell carcinoma (RCC) patients. We seek to evaluate the quality of published RCC circulating diagnostic biomarker manuscripts using the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines. Methods The phrase “(renal cell carcinoma OR renal cancer OR kidney cancer OR kidney carcinoma) AND circulating AND (biomarkers OR cell free DNA OR tumor DNA OR methylated cell free DNA OR methylated tumor DNA)” was searched in Embase, MEDLINE, and PubMed in March 2018. Relevant manuscripts were scored using 41 STARD subcriteria for a maximal score of 26 points. All tests of statistical significance were 2 sided. Results The search identified 535 publications: 27 manuscripts of primary research were analyzed. The median STARD score was 11.5 (range = 7-16.75). All manuscripts had appropriate abstracts, introductions, and distribution of alternative diagnoses. None of the manuscripts stated how indeterminant data were handled or if adverse events occurred from performing the index test or reference standard. Statistically significantly higher STARD scores were present in manuscripts reporting receiver operator characteristic curves (P < .001), larger sample sizes (P = .007), and after release of the original STARD statement (P = .005). Conclusions Most RCC circulating diagnostic biomarker manuscripts poorly adhere to the STARD guidelines. Future studies adhering to STARD guidelines may address this unmet need.
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Affiliation(s)
- Marco A J Iafolla
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada.,Division of Oncology, William Osler Health System, Brampton, Ontario, Canada
| | - Sarah Picardo
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
| | - Kyaw Aung
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada.,Livestrong Cancer Institute and Dell Medical School, University of Texas at Austin, Austin, TX, USA
| | - Aaron R Hansen
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
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Nam SH, Jang J, Cheon DH, Chong SE, Ahn JH, Hyun S, Yu J, Lee Y. pH-Activatable cell penetrating peptide dimers for potent delivery of anticancer drug to triple-negative breast cancer. J Control Release 2020; 330:898-906. [PMID: 33152392 DOI: 10.1016/j.jconrel.2020.10.063] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 10/29/2020] [Accepted: 10/30/2020] [Indexed: 02/06/2023]
Abstract
We developed a pH-activatable cell-penetrating peptide dimer LH2 with histidine residues, which can penetrate cells, specifically in weak acidic conditions, even at few tens of nanomolar concentrations. LH2 effectively delivered paclitaxel into triple-negative breast cancer cells, MDA-MB-231, via formation of non-covalent complexes (PTX-LH2(M)) or covalent conjugates (PTX-LH2(C)). Moreover, LH2 showed prolonged circulation in the body and enhanced accumulation in tumors. Both PTX-LH2(M) and PTX-LH2(C) showed strong antitumor effects in a triple-negative breast cancer grafted mouse model at an extremely low dosage.
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Affiliation(s)
- So Hee Nam
- Department of Chemistry, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea.
| | - Joomyung Jang
- Department of Chemistry, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Dae Hee Cheon
- Department of Chemistry, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Seung-Eun Chong
- Department of Chemistry, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Joon Hyung Ahn
- Department of Chemistry, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Soonsil Hyun
- Department of Chemistry and Education, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jaehoon Yu
- Department of Chemistry and Education, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea.
| | - Yan Lee
- Department of Chemistry, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea.
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Multicompartment modeling of protein shedding kinetics during vascularized tumor growth. Sci Rep 2020; 10:16709. [PMID: 33028917 PMCID: PMC7542472 DOI: 10.1038/s41598-020-73866-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 09/10/2020] [Indexed: 02/07/2023] Open
Abstract
Identification of protein biomarkers for cancer diagnosis and prognosis remains a critical unmet clinical need. A major reason is that the dynamic relationship between proliferating and necrotic cell populations during vascularized tumor growth, and the associated extra- and intra-cellular protein outflux from these populations into blood circulation remains poorly understood. Complementary to experimental efforts, mathematical approaches have been employed to effectively simulate the kinetics of detectable surface proteins (e.g., CA-125) shed into the bloodstream. However, existing models can be difficult to tune and may be unable to capture the dynamics of non-extracellular proteins, such as those shed from necrotic and apoptosing cells. The models may also fail to account for intra-tumoral spatial and microenvironmental heterogeneity. We present a new multi-compartment model to simulate heterogeneously vascularized growing tumors and the corresponding protein outflux. Model parameters can be tuned from histology data, including relative vascular volume, mean vessel diameter, and distance from vasculature to necrotic tissue. The model enables evaluating the difference in shedding rates between extra- and non-extracellular proteins from viable and necrosing cells as a function of heterogeneous vascularization. Simulation results indicate that under certain conditions it is possible for non-extracellular proteins to have superior outflux relative to extracellular proteins. This work contributes towards the goal of cancer biomarker identification by enabling simulation of protein shedding kinetics based on tumor tissue-specific characteristics. Ultimately, we anticipate that models like the one introduced herein will enable examining origins and circulating dynamics of candidate biomarkers, thus facilitating marker selection for validation studies.
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Whole transcriptome signature for prognostic prediction (WTSPP): application of whole transcriptome signature for prognostic prediction in cancer. J Transl Med 2020; 100:1356-1366. [PMID: 32144347 PMCID: PMC7483260 DOI: 10.1038/s41374-020-0413-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 02/20/2020] [Accepted: 02/21/2020] [Indexed: 11/08/2022] Open
Abstract
Developing prognostic biomarkers for specific cancer types that accurately predict patient survival is increasingly important in clinical research and practice. Despite the enormous potential of prognostic signatures, proposed models have found limited implementations in routine clinical practice. Herein, we propose a generic, RNA sequencing platform independent, statistical framework named whole transcriptome signature for prognostic prediction to generate prognostic gene signatures. Using ovarian cancer and lung adenocarcinoma as examples, we provide evidence that our prognostic signatures overperform previous reported signatures, capture prognostic features not explained by clinical variables, and expose biologically relevant prognostic pathways, including those involved in the immune system and cell cycle. Our approach demonstrates a robust method for developing prognostic gene expression signatures. In conclusion, our statistical framework can be generally applied to all cancer types for prognostic prediction and might be extended to other human diseases. The proposed method is implemented as an R package (PanCancerSig) and is freely available on GitHub ( https://github.com/Cheng-Lab-GitHub/PanCancer_Signature ).
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Quezada-Marín JI, Lam AK, Ochiai A, Odze RD, Washington KM, Fukayama M, Rugge M, Klimstra DS, Nagtegaal ID, Tan PH, Arends MJ, Goldblum JR, Cree IA, Salto-Tellez M. Gastrointestinal tissue-based molecular biomarkers: a practical categorisation based on the 2019 World Health Organization classification of epithelial digestive tumours. Histopathology 2020; 77:340-350. [PMID: 32320495 DOI: 10.1111/his.14120] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 03/25/2020] [Accepted: 04/15/2020] [Indexed: 12/15/2022]
Abstract
Molecular biomarkers have come to constitute one of the cornerstones of oncological pathology. The method of classification not only directly affects the manner in which patients are diagnosed and treated, but also guides the development of drugs and of artificial intelligence tools. The aim of this article is to organise and update gastrointestinal molecular biomarkers in order to produce an easy-to-use guide for routine diagnostics. For this purpose, we have extracted and reorganised the molecular information on epithelial neoplasms included in the 2019 World Health Organization classification of tumours. Digestive system tumours, 5th edn.
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Affiliation(s)
- Javier I Quezada-Marín
- Precision Medicine Centre of Excellence, Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK
- Molecular Pathology Laboratory, Anatomical Pathology Service, Puerto Montt Hospital, Puerto Montt, Chile
| | - Alfred K Lam
- Cancer Molecular Pathology, School of Medicine, Griffith University, Gold Coast, Queensland, Australia
| | - Atsushi Ochiai
- Exploratory Oncology Research and Clinical Trial Centre, National Cancer Centre, Kashiwa, Japan
| | | | - Kay M Washington
- Department of Pathology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Masashi Fukayama
- Department of Pathology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Massimo Rugge
- Surgical Pathology and Cytopathology Unit, Department of Medicine (DIMED), University of Padova, Padova, Italy
| | - David S Klimstra
- Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Iris D Nagtegaal
- Department of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Puay-Hoon Tan
- Division of Pathology, Singapore General Hospital, Singapore, Singapore
| | - Mark J Arends
- Division of Pathology, Cancer Research UK Edinburgh Centre, Western General Hospital, Edinburgh, UK
| | - John R Goldblum
- Department of Anatomic Pathology, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Ian A Cree
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Manuel Salto-Tellez
- Precision Medicine Centre of Excellence, Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK
- Cellular Pathology, Belfast Health and Social Care Trust, Belfast, UK
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Sun Q, Liu P, Long B, Zhu Y, Liu T. Screening of significant biomarkers with poor prognosis in hepatocellular carcinoma via bioinformatics analysis. Medicine (Baltimore) 2020; 99:e21702. [PMID: 32769939 PMCID: PMC7593045 DOI: 10.1097/md.0000000000021702] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a malignant tumor with unsatisfactory prognosis. The abnormal genes expression is significantly associated with initiation and poor prognosis of HCC. The aim of the present study was to identify molecular biomarkers related to the initiation and development of HCC via bioinformatics analysis, so as to provide a certain molecular mechanism for individualized treatment of hepatocellular carcinoma.Three datasets (GSE101685, GSE112790, and GSE121248) from the GEO database were used for the bioinformatics analysis. Differentially expressed genes (DEGs) of HCC and normal liver samples were obtained using GEO2R online tools. Gene ontology term and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were conducted via the Database for Annotation, Visualization, and Integrated Discovery online bioinformatics tool. The protein-protein interaction (PPI) network was constructed by the Search Tool for the Retrieval of Interacting Genes database and hub genes were visualized by Cytoscape. Survival analysis and RNA sequencing expression were conducted by UALCAN and Gene Expression Profiling Interactive Analysis.A total of 115 shared DEGs were identified, including 30 upregulated genes and 85 downregulated genes in HCC samples. P53 signaling pathway and cell cycle were the major enriched pathways for the upregulated DEGs whereas metabolism-related pathways were the major enriched pathways for the downregulated DEGs. The PPI network was established with 105 nodes and 249 edges and 3 significant modules were identified via molecular complex detection. Additionally, 17 candidate genes from these 3 modules were significantly correlated with HCC patient survival and 15 of 17 genes exhibited high expression level in HCC samples. Moreover, 4 hub genes (CCNB1, CDK1, RRM2, BUB1B) were identified for further reanalysis of KEGG pathway, and enriched in 2 pathways, the P53 signaling pathway and cell cycle pathway.Overexpression of CCNB1, CDK1, RRM2, and BUB1B in HCC samples was correlated with poor survival in HCC patients, which could be potential therapeutic targets for HCC.
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Affiliation(s)
- Quanquan Sun
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences
- Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences, Beijing
- Department of Radiation Oncology
- Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital
| | - Peng Liu
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences
- Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences, Beijing
- Department of Radiation Oncology
- Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital
| | - Bin Long
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences
- Department of Nuclear Medicine, Zhejiang Cancer Hospital, Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang, Hangzhou, Zhejiang Province, People's Republic of China
| | - Yuan Zhu
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences
- Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences, Beijing
- Department of Radiation Oncology
- Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital
| | - Tongxin Liu
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences
- Department of Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences, Beijing
- Department of Radiation Oncology
- Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital
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Abstract
PURPOSE OF REVIEW Sinonasal cancers are a heterogenous group of rare cancers for which histopathological diagnosis can be very challenging and treatment options are limited for advanced disease in particular. Here, we review the candidacy of novel diagnostic and prognostic biomarkers, and therapeutic targets for sinonasal cancers. RECENT FINDINGS Molecular multidimensional analyses of sinonasal cancers have been lagging behind other major cancers, but there are numerous publications describing the discovery of novel candidate biomarkers, e.g. the methylation classifier, originally developed for brain cancers, and gene expression panels for the prediction of response to induction chemotherapy in sinonasal undifferentiated carcinoma. The most promising biomarkers are summarized and discussed further with regard to their clinical applicability and future potential. Many of the described novel biomarkers for sinonasal cancers will eventually overcome the pitfalls associated with the frequently non-specific immunohistological tests. With comprehensive, multidimensional molecular testing of these tumours in collaborative consortia projects, our better understanding of the molecular mechanisms of sinonasal cancers and their carcinogenesis will determine the most useful diagnostic and prognostic biomarkers, allow stringent multi-institutional validation and guide trials on targeted therapies.
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Affiliation(s)
- Matt Lechner
- UCL Cancer Institute, University College London, 72 Huntley Street, London, UK
- Royal London Hospital, Barts Health NHS Trust, London, UK
- Royal National Throat, Nose and Ear Hospital/Head and Neck Centre, University College London Hospitals NHS Foundation Trust, London, UK
| | - Jacklyn Liu
- UCL Cancer Institute, University College London, 72 Huntley Street, London, UK
- Royal National Throat, Nose and Ear Hospital/Head and Neck Centre, University College London Hospitals NHS Foundation Trust, London, UK
| | - Valerie J Lund
- Royal National Throat, Nose and Ear Hospital/Head and Neck Centre, University College London Hospitals NHS Foundation Trust, London, UK.
- UCL Ear Institute, University College London, London, UK.
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