PROJECT SUMMARY
Cancer sequencing projects have demonstrated that tumors are tremendously heterogeneous,
reflecting the large diversity of perturbations in the cellular machinery that promote tumor growth
and metastasis. Tumors from different patients with the same type of cancer have a diverse
collection of genomic, epigenomic, and transcriptomic aberrations. Moreover, a tumor from a
single patient is a mixture of cell types including normal cells, stroma, and multiple subpopulations
of cancerous cells. We propose a Genome Data Analysis Center (GDAC) that will develop and
apply novel computational approaches to address the challenges of inter-tumor and intra-tumor
heterogeneity. This GDAC will integrate data from multiple genome characterization platforms,
multiple sequencing technologies -- including bulk, single-cell, and spatial sequencing
technologies – and leverage prior knowledge of pathways and interaction networks to explain
clinical phenotypes and inform treatment strategies. The GDAC will perform pathway and network
integration of genome characterization data, spatial analysis of tumor microenvironment, and
temporal analysis of intra-tumor heterogeneity, tumor evolution, and network rewiring. These
analyses will enable more precise translation of cancer genome characterization efforts into
clinical utility for a larger fraction of cancer patients. The GDAC will continue the ongoing
contributions of the PIs to the current Genome Data Analysis Network (GDAN) and previous
efforts in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium
(ICGC) projects.