Mechanistic and Technical Challenges in Studying the Human Microbiome and Cancer Epidemiology
Author(s) -
Mukesh Verma
Publication year - 2016
Publication title -
technology in cancer research and treatment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.754
H-Index - 63
eISSN - 1533-0346
pISSN - 1533-0338
DOI - 10.1177/1533034616645219
Subject(s) - microbiome , computational biology , biology , metagenomics , epidemiology , human microbiome , bioinformatics , medicine , genetics , pathology , gene
This article reviews the significance of the microbiome in cancer epidemiology, mechanistic and technical challenges in the field, and characterization of the microbiome in different tumor types to identify biomarkers of risk, progression, and prognosis. Publications on the microbiome and cancer epidemiology were reviewed to analyze sample collection and processing, microbiome taxa characterization by 16S ribosomal RNA sequencing, and microbiome metabolite characterization (metabotyping) by nuclear magnetic resonance and mass spectrometry. The analysis identified methodology types, research design, sample types, and issues in integrating data from different platforms. Aerodigestive cancer epidemiology studies conducted by different groups demonstrated the significance of microbiome information in developing approaches to improve health. Challenges exist in sample preparation and processing (eg, standardization of methods for collection and analysis). These challenges relate to technology, data integration from “omics” studies, inherent bias in primer selection during 16S ribosomal RNA sequencing, the need for large consortia with well-characterized biospecimens, cause and effect issues, resilience of microbiota to exposure events (requires longitudinal studies), and expanding studies for fungal and viral diversity (most studies used bacterial 16S ribosomal RNA sequencing for microbiota characterization). Despite these challenges, microbiome and cancer epidemiology studies are significant and may facilitate cancer risk assessment, diagnosis, and prognosis. In the future, clinical trials likely will use microbiota modifications to improve the efficacy of existing treatments.
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