Association of imputed prostate cancer transcriptome with disease risk reveals novel mechanisms

Nima C. Emami, Linda Kachuri, Travis J. Meyers, Rajdeep Das, Joshua D. Hoffman, Thomas J. Hoffmann, Donglei Hu, Jun Shan, Felix Y. Feng, Elad Ziv, Stephen K. Eeden and John S. Witte ()
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Nima C. Emami: University of California San Francisco
Linda Kachuri: University of California San Francisco
Travis J. Meyers: University of California San Francisco
Rajdeep Das: University of California San Francisco
Joshua D. Hoffman: University of California San Francisco
Thomas J. Hoffmann: University of California San Francisco
Donglei Hu: University of California San Francisco
Jun Shan: Kaiser Permanente, Northern California
Felix Y. Feng: University of California San Francisco
Elad Ziv: University of California San Francisco
Stephen K. Eeden: University of California San Francisco
John S. Witte: University of California San Francisco

Nature Communications, 2019, vol. 10, issue 1, 1-11

Abstract: Abstract Here we train cis-regulatory models of prostate tissue gene expression and impute expression transcriptome-wide for 233,955 European ancestry men (14,616 prostate cancer (PrCa) cases, 219,339 controls) from two large cohorts. Among 12,014 genes evaluated in the UK Biobank, we identify 38 associated with PrCa, many replicating in the Kaiser Permanente RPGEH. We report the association of elevated TMPRSS2 expression with increased PrCa risk (independent of a previously-reported risk variant) and with increased tumoral expression of the TMPRSS2:ERG fusion-oncogene in The Cancer Genome Atlas, suggesting a novel germline-somatic interaction mechanism. Three novel genes, HOXA4, KLK1, and TIMM23, additionally replicate in the RPGEH cohort. Furthermore, 4 genes, MSMB, NCOA4, PCAT1, and PPP1R14A, are associated with PrCa in a trans-ethnic meta-analysis (N = 9117). Many genes exhibit evidence for allele-specific transcriptional activation by PrCa master-regulators (including androgen receptor) in Position Weight Matrix, Chip-Seq, and Hi-C experimental data, suggesting common regulatory mechanisms for the associated genes.

Date: 2019
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DOI: 10.1038/s41467-019-10808-7

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