Androgen receptor-mediated pharmacogenomic expression quantitative trait loci: implications for breast cancer response to AR-targeting therapy.

BACKGROUND: Endocrine therapy is the most important treatment modality of breast cancer patients whose tumors express the estrogen receptor α (ERα). The androgen receptor (AR) is also expressed in the vast majority (80-90%) of ERα-positive tumors. AR-targeting drugs are not used in clinical practice, but have been evaluated in multiple trials and preclinical studies. METHODS: We performed a genome-wide study to identify hormone/drug-induced single nucleotide polymorphism (SNP) genotype - dependent gene-expression, known as PGx-eQTL, mediated by either an AR agonist (dihydrotestosterone) or a partial antagonist (enzalutamide), utilizing a previously well characterized lymphoblastic cell line panel. The association of the identified SNPs-gene pairs with breast cancer phenotypes were then examined using three genome-wide association (GWAS) studies that we have published and other studies from the GWAS catalog. RESULTS: We identified 13 DHT-mediated PGx-eQTL loci and 23 Enz-mediated PGx-eQTL loci that were associated with breast cancer outcomes post ER antagonist or aromatase inhibitors (AI) treatment, or with pharmacodynamic (PD) effects of AIs. An additional 30 loci were found to be associated with cancer risk and sex-hormone binding globulin levels. The top loci involved the genes IDH2 and TMEM9, the expression of which were suppressed by DHT in a PGx-eQTL SNP genotype-dependent manner. Both of these genes were overexpressed in breast cancer and were associated with a poorer prognosis. Therefore, suppression of these genes by AR agonists may benefit patients with minor allele genotypes for these SNPs. CONCLUSIONS: We identified AR-related PGx-eQTL SNP-gene pairs that were associated with risks, outcomes and PD effects of endocrine therapy that may provide potential biomarkers for individualized treatment of breast cancer.

Oxalate Nephropathy After Kidney Transplantation: Risk Factors and Outcomes of Two Phenotypes.

Describing risk factors and outcomes in kidney transplant recipients with oxalate nephropathy (ON) may help elucidate the pathogenesis and guide treatment strategies. We used a large single-center database to identify patients with ON and categorized them into delayed graft function with ON (DGF-ON) and late ON. Incidence density sampling was used to select controls. A total of 37 ON cases were diagnosed between 1/2011 and 1/2021. DGF-ON (n = 13) was diagnosed in 1.05% of the DGF population. Pancreatic atrophy on imaging (36.4% vs. 2.9%, p = 0.002) and gastric bypass history (7.7% vs. 0%; p = 0.06) were more common in DGF-ON than with controls with DGF requiring biopsy but without evidence of ON. DGF-ON was not associated with worse graft survival (p = 0.98) or death-censored graft survival (p = 0.48). Late ON (n = 24) was diagnosed after a mean of 78.2 months. Late ON patients were older (mean age 55.1 vs. 48.4 years; p = 0.02), more likely to be women (61.7% vs. 37.5%; p = 0.03), have gastric bypass history (8.3% vs. 0.8%; p = 0.02) and pancreatic atrophy on imaging (38.9% vs. 13.3%; p = 0.02). Late ON was associated with an increased risk of graft failure (HR 2.0; p = 0.07) and death-censored graft loss (HR 2.5; p = 0.10). We describe two phenotypes of ON after kidney transplantation: DGF-ON and late ON. Our study is the first to our knowledge to evaluate DGF-ON with DGF controls without ON. Although limited by small sample size, DGF-ON was not associated with adverse outcomes when compared with controls. Late ON predicted worse allograft outcomes.

Functional dissection of complex and molecular trait variants at single nucleotide resolution.

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.