Our previous study of more than 10 thousand tumors across 33 cancer types identified over 800 germline
predisposition variants in both tumor suppressors and oncogenes. Although the impact of some of these
variants on cancer onset, incidence rate, and clonality have been documented, the effects of these variants
(especially when compared to somatic mutations) on molecular characteristics of cancer cells, contributions of
non-cancer cells having germline variants, and treatment responses, are far less studied. Our recent single
cell(sc) /single nucleus(sn) RNA-seq analyses of cancer samples provided comprehensive expression profiles
at a single cell resolution and revealed the expression of key cancer predisposition genes, such as BRCA 112,
VHL, BAP1, and c-MET in many non-cancer stromal and immune cells in the tumor microenvironment (TME).
Our pilot analyses also revealed significant differential gene expression in cancer and non-cancer cells based
on the nature of the driver event being germline or somatic. We hypothesize that tumors with certain germline
predisposition variants in tumor suppressors and oncogenes may show differences in tumor progression and
treatment responses from those tumors with somatic mutations in the same genes due to differential
influence on mutational, transcriptomic, and proteomic profiles of the cancer cells and potentially distinctive
contributions from non-cancer cells having those germline changes. To take advantage of the considerable
progress over the last few years, namely newly accumulated cancer sequencing data, advances in single cell
omics, patient-derived xenografts (PDX), and tumor genetic models, we propose to test these hypotheses by
performing the following: compare germline predisposition variants and somatic mutations to dissect their
differential biological impacts and interactions using computational analysis (Aim 1); perform single
nucleus RNA-seq/ATAC-seq, spatial transcriptomics, and multiplex imaging analysis of human cancer
samples to reveal the differential roles of germline predisposition variants and somatic mutations in tumor
cells and the TME (Aim 2); use PDX and genetic cancer models to investigate potential functional
differences between germline predisposition variants and somatic mutations in tumor cells, TME, and
treatment responses (Aim 3). Results from this study will advance our understanding of the unique
contributions of germline variants to cancer cells and TME alike, improve genetic counseling and prognosis,
and provide guidance for differential treatment of tumors carrying germline variants vs somatic mutations in key
cancer driver genes.