Abstract
Abstract Future success in molecular epidemiology depends on how quickly epidemiology adopts, optimizes and validates emerging technologies for molecular-scale analysis. In order to advance molecular epidemiology in cancer, the National Cancer Institute (NCI) supports the development of novel, next-generation, and cutting-edge molecular and cellular analysis technologies. Here we present past and present technology development efforts and their impact on cancer epidemiology. Some of the technologies, whose early-stage development was supported by the NCI, such as resequencing arrays, gene expression assay system, technologies which enable next generation sequencing, RNA preservative, rolling circle amplification of DNA, digital PCR system, functionalization of quantum dots, chromatin immunoprecipitation with next gen Sequencing, and multidimensional protein identification technology are now mainstay in basic and clinical research laboratories for genomic, epigenomic, transcriptomic and proteomic analysis. Additionally, these technologies have significantly contributed in identifying molecular determinants of cancer, and in assessing risk, disease progression and prognosis in large scale cancer epidemiology. Current awards support developing technologies for single cell analysis which can capture heterogeneity, simultaneous detection of multiple oncogenes, sensitive sequencing of geneomic/somatic mutations, targeted sequencing, rare variant detection, sequencing of ultralow-frequency mutations, epigenetic changes, kinome, multiplexed detection of microRNA, proteins, cytokines and metabolites, circulating tumor cells, and highthroughput protein-DNA interactions assessment. In addition, several novel biospecimen collection, preservation and processing technologies are also being supported with the potential to define the future of molecular epidemiology. Collectively, these technology development efforts supported by NCI provide a tremendous opportunity for molecular epidemiologists wishing to study archived samples collected in large-scale epidemiology efforts, and optimize and validate them for new molecular analyses. Citation Format: Rao L. Divi, Mukesh Verma, Anthony Dickherber. Technologies for molecular epidemiology in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5571. doi:10.1158/1538-7445.AM2015-5571
Published Version
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