Comprehensive Biomarker Discovery and Validation for Clinical Application

2020 ◽  
Vol 26 (42) ◽  
pp. 7655-7671 ◽  
Author(s):  
Jinfeng Zou ◽  
Edwin Wang

Background: Precision medicine puts forward customized healthcare for cancer patients. An important way to accomplish this task is to stratify patients into those who may respond to a treatment and those who may not. For this purpose, diagnostic and prognostic biomarkers have been pursued. Objective: This review focuses on novel approaches and concepts of exploring biomarker discovery under the circumstances that technologies are developed, and data are accumulated for precision medicine. Results: The traditional mechanism-driven functional biomarkers have the advantage of actionable insights, while data-driven computational biomarkers can fulfill more needs, especially with tremendous data on the molecules of different layers (e.g. genetic mutation, mRNA, protein etc.) which are accumulated based on a plenty of technologies. Besides, the technology-driven liquid biopsy biomarker is very promising to improve patients’ survival. The developments of biomarker discovery on these aspects are promoting the understanding of cancer, helping the stratification of patients and improving patients’ survival. Conclusion: Current developments on mechanisms-, data- and technology-driven biomarker discovery are achieving the aim of precision medicine and promoting the clinical application of biomarkers. Meanwhile, the complexity of cancer requires more effective biomarkers, which could be accomplished by a comprehensive integration of multiple types of biomarkers together with a deep understanding of cancer.


2018 ◽  
Vol 64 (11) ◽  
pp. 1657-1667 ◽  
Author(s):  
Lucy A Parker ◽  
Elisa Chilet-Rosell ◽  
Ildefonso Hernández-Aguado ◽  
María Pastor-Valero ◽  
Sonia Gea ◽  
...  

Abstract BACKGROUND Despite considerable research investment, moving from biomarker discovery to clinical application has presented unique challenges. We aimed to evaluate progress toward clinical application of a sample of molecular- and “omics”-based diagnostic tests over a 10-year period. METHODS We used Scopus to locate studies, published before the December 31, 2016, citing 107 original-research articles published in 2006 that assessed the diagnostic value of a molecular- or “omics”-based test. We identified diagnostic studies of the same test and disease and determined whether the article represented progress in the validation of the molecular test. We classified the types of progress: (a) clinical validation (measuring diagnostic accuracy in a series of patients similar to the population in which the test will be used in practice), (b) technical improvement, (c) extended diagnostic application (modification of the diagnostic question attended initially by the test), (d) economic evaluation, or (e) clinical use or implementation. RESULTS In the 10-year period analyzed, 4257 articles cited the 107 diagnostic studies; 118 (2.8%) were diagnostic studies of the same test, and of these papers, 25 (21.2%) did not constitute progress toward validation of the test for use in clinical practice (potential research waste). Of the 107 molecular- or “omics”-based tests described in 2006, only 28 (26.2%) appeared to have made progress toward clinical application. Only 4 (9.1%) of 44 proteomics-based tests had made progress toward clinical application. CONCLUSIONS Articles evaluating molecular- or “omics”-based diagnostic tests are numerous in biomedical journals. Few tests have made progress toward clinical application in the 10 years following their discovery.


2010 ◽  
Vol 5 (1-2) ◽  
pp. 9-23 ◽  
Author(s):  
Harald Mischak ◽  
Joost P. Schanstra

2015 ◽  
Vol 9 (3-4) ◽  
pp. 322-334 ◽  
Author(s):  
Claudia Pontillo ◽  
Szymon Filip ◽  
Daniel M. Borràs ◽  
William Mullen ◽  
Antonia Vlahou ◽  
...  

JAMA ◽  
1966 ◽  
Vol 195 (3) ◽  
pp. 161-166 ◽  
Author(s):  
B. L. Segal

2007 ◽  
Vol 177 (4S) ◽  
pp. 590-590
Author(s):  
Thomas J. Polascik ◽  
Vladimir Mouraviev ◽  
Janice M. Mayes ◽  
Leon Sun ◽  
John Madden ◽  
...  

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