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Am Soc Clin Oncol Educ Book. 2012:e52-5. doi: 10.14694/EdBook_AM.2012.32.e52.

Why Hasn't Genomic Testing Changed the Landscape in Clinical Oncology?

Author information

1
From the University of Michigan Comprehensive Cancer Center, Ann Arbor, MI; Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD; Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA; Departments of Medicine and Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.

Abstract

The "omics" revolution produced great optimism that tumor biomarker tests based on high-order analysis of multiple (sometimes thousands) of factors would result in truly personalized oncologic care. Unfortunately, 10 years into the revolution, the promise of omics-based research has not yet been realized. The factors behind the slow progress in omics-based clinical care are many. First, over the last 15 years, there has been a gradual recognition of the importance of conducting tumor biomarker science with the kind of rigor that has traditionally been used for therapeutic research. However, this recognition has only recently been applied widely, and therefore most tumor biomarkers have insufficiently high levels of evidence to determine clinical utility. Second, omics-based research offers its own particular set of concerns, especially in regard to overfitting computational models and false discovery rates. Researchers and clinicians need to understand the importance of analytic validity, and the difference between clinical/biologic validity and clinical utility. The latter is required to introduce a tumor biomarker test of any kind (single analyte or omics-based), and are ideally generated by carefully planned and properly conducted "prospective retrospective" or truly prospective clinical trials. Only carefully planned studies, which take all three of these into account and in which the investigators are aware and recognize the enormous risk of unintended bias and overfitting inherent in omics-based test development, will ultimately result in translation of the exciting new technologies into better care for patients with cancer.

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