bioRxivCancer BiologyPreprint
Germline determinants of the prostate tumor genome
K. E. Houlahan, J. Yuan, T. Schwarz, J. Livingstone, N. S. Fox, W. Jaratlerdsiri, J. van Riet, K. Taraszka, N. Kurganovs, H. Zhu, J. Sietsma Penington, C.-H. Jung, T. N. Yamaguchi, J. Jiang, L. E. Heisler, R. Jovelin, S. G. Ramanand, C. Bell, E. O'Connor, S. B. A. Mutambirwa, J.-H. Seo, A. J. Costello, M. M. Pomerantz, B. J. Pope, N. Zaitlen, , P. C. Boutros
Abstract
A persons germline genome strongly influences their risk of developing cancer. Yet the molecular mechanisms linking the host genome to the specific somatic molecular phenotypes of individual cancers are largely unknown. We quantified the relationships between germline polymorphisms and somatic mutational features in prostate cancer. Across 1,991 prostate tumors, we identified 23 co-occurring germline and somatic events in close 2D or 3D spatial genomic proximity, affecting 10 cancer driver genes. These driver quantitative trait loci (dQTLs) overlap active regulatory regions, and shape the tumor epigenome, transcriptome and proteome. Some dQTLs are active in multiple cancer types, and information content analyses imply hundreds of undiscovered dQTLs. Specific dQTLs explain at least 16.7% ancestry-biases in rates of TMPRSS2-ERG gene fusions and 67.3% of ancestry-biases in rates of FOXA1 point mutations. These data reveal extensive influences of common germline variation on somatic mutational landscapes.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- assay: proteomics
- assay: bulk RNA-seq
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: variant effect prediction
- approach: statistical model
- approach: genetic perturbation / CRISPR
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