Genome-wide burden survival tests for patients with metastatic prostate cancer on androgen receptor-targeted therapies in the Million Veterans Program dataset.

251 Background: Literature suggests various genes influence metabolism and treatment response in prostate cancer. While the androgen receptor gene is the primary target for hormonal treatment, studies increasingly highlight the roles of genes in lipid metabolism and pharmacogenetics, including APOE, BGN, AHSG, CYP2D6, SLC2A4 , and HSD3B1 . Genes allowing androgens to enter cells more efficiently may increase therapy resistance, worsening outcomes in recurrent or metastatic disease. An understanding of biomarkers and resistance mechanisms is essential to address this issue. We conducted a genome-wide search for genes that exhibit an effect on survival in patients on androgen receptor-targeted therapies. Methods: We developed two models: Model 1 identified 5,107 patients with metastatic prostate cancer receiving androgen deprivation therapy; model 2 focused on a subgroup 2,240 patients on abiraterone. We performed 18,544 distinct gene-level tests across the human genome using all coding variants within each gene, analyzing rare (minor allele frequency <1%) loss-of-function variants, and rare loss-of-function and missense variants. All analyses used the Veterans Administration’s Million Veterans Program (MVP) whole genome Release2 genomic data (96K males). We conducted separate analyses for African and European ancestry subjects. Gene-level survival analysis was performed using the SeqMeta R package that performs burden, Skat, and Skat-O tests. A Bonferroni correction was applied for 82,567 tests, requiring p<6.06E-7 to establish significance and p<5.00E-6 for suggestive evidence. Individual survival analyses were conducted on all SNPs within each significant gene. Results: Gene-level tests identified OR1G1 (burden p=1.87E-7, OR=0.17), PCDHGB1 (burden p= 2.92E-07, OR=0.61) and CLPB (burden p=3.34E-07, OR=0.30) as significantly associated with prostate cancer survival, while SNX18 demonstrated a suggestive association (Skat-O p=3.40E-6) among European ancestry subjects in model 1. Among African ancestry subjects, the best performing gene was UBD (burden p= 2.61E-06, OR=0.76). Analyses of rare loss-of-function and loss-of-function or missense variants failed to achieve significant or suggestive evidence. Model 2 did not reveal any significant findings. Additional variant level survival analyses revealed 4 significant SNPs from UBD including chr6.29555893.C.A, chr6.29556082.G.C, chr6.29556095.A.G_A, chr6.29556226.A.G_A (1 copy HR 3.1, 2 copies HR 3.7, p <.05) and SNP chr5.54519665.A.C_A from gene SNX18 (1 copy HR 1.5 p <.05). Conclusions: Our results indicate variants within several genes may influence prostate cancer survival by causing resistance to androgen-receptor targeted therapies and warrant follow-up in external datasets for validation.