Opportunities and Challenges for Selected Emerging Technologies in Cancer Epidemiology: Mitochondrial, Epigenomic, Metabolomic, and Telomerase Profiling

+Author Affiliations

Authors' Affiliations: ¹Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, Maryland; and ²Stanford Prevention Research Center, Department of Medicine, and Department of Health Research and Policy, Stanford University School of Medicine; and Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, California

Corresponding Author:
Mukesh Verma, Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, 6130 Executive Boulevard, Room 5100, Bethesda, MD 20892. Phone: 301-594-7344; Fax: 301-435-6609; E-mail: vermam@mail.nih.gov

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Abstract

Remarkable progress has been made in the last decade in new methods for biologic measurements using sophisticated technologies that go beyond the established genome, proteome, and gene expression platforms. These methods and technologies create opportunities to enhance cancer epidemiologic studies. In this article, we describe several emerging technologies and evaluate their potential in epidemiologic studies. We review the background, assays, methods, and challenges and offer examples of the use of mitochondrial DNA and copy number assessments, epigenomic profiling (including methylation, histone modification, miRNAs, and chromatin condensation), metabolite profiling (metabolomics), and telomere measurements. We map the volume of literature referring to each one of these measurement tools and the extent to which efforts have been made at knowledge integration (e.g., systematic reviews and meta-analyses). We also clarify strengths and weaknesses of the existing platforms and the range of type of samples that can be tested with each of them. These measurement tools can be used in identifying at-risk populations and providing novel markers of survival and treatment response. Rigorous analytic and validation standards, transparent availability of massive data, and integration in large-scale evidence are essential in fulfilling the potential of these technologies. Cancer Epidemiol Biomarkers Prev; 22(2); 189–200. ©2012 AACR.