Research Project 1
Project title: A Data-driven Pan-cancer Study of Biological Bases of Cancer Health Disparities
PI: Kun Zhang, Ph.D.
Overall goal/objectives:
The goal of this RCMI research project is therefore to address these significant limitations by performing an in-depth, data-driven, pan-cancer study to investigate the cancer-specific mutome, epigenome, and RNA-Seq transcriptome differences in different racial groups. The proposed study will focus on the eight TCGA cancer types, with pertinent cancer data from other sources (E.g. dbGaP, GEO, ICGC, etc.) being systematically utilized for methodology development and/or empirical validation throughout the entire project. For a specific cancer, in connection with clinical data, we will develop new bioinformatics algorithms and pipelines to analyze these multiple types of omics data individually and collectively. As such, we will establish a pan-cancer, race relevant assemblage of single- and multi- level coherent genes, modules and biological pathways, some of which will hold significance and promise for clinical use. This will provide large-scale direct molecular-level evidence for the biological mechanism underlying racial disparities in cancer, which is practically impossible using the approaches of in vitro, in vivo and/or population follow-up. Furthermore, we will biologically validate the identified signatures for prostate cancer using clinical samples. A database for all pinpointed signatures will be constructed so that cancer disparity researchers can interrogate how various levels of molecular variations may alter gene functions in different cancers and races. A set of efficient and powerful analytical tools for the proposed data-driven analyses of health disparities in cancer will also be made publicly available as open-source software.
Research discipline: Basic Biomedical