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Large-scale genomic and transcriptomic initiatives offer unprecedented insight into complex traits, but clinical translation remains limited by variant-level associations without biological context and lack of analytic resources. Our resource, PhenomeXcan, synthesizes 8.87 million variants from genome-wide association study summary statistics on 4091 traits with transcriptomic data from 49 tissues in Genotype-Tissue Expression v8 into a gene-based, queryable platform including 22,515 genes. We developed a novel Bayesian colocalization method, fast enrichment estimation aided colocalization analysis (fastENLOC), to prioritize likely causal gene-trait associations. We successfully replicate associations from the phenome-wide association studies (PheWAS) catalog Online Mendelian Inheritance in Man, and an evidence-based curated gene list. Using PhenomeXcan results, we provide examples of novel and underreported genome-to-phenome associations, complex gene-trait clusters, shared causal genes between common and rare diseases via further integration of PhenomeXcan with ClinVar, and potential therapeutic targets. PhenomeXcan (phenomexcan.org) provides broad, user-friendly access to complex data for translational researchers.

ABSTR AC T Background Invasive lobular carcinoma (ILC) comprisesaround 10-15 % of invasive breast cancers. Few prior studies have demonstrated a unique pattern of metastases between ILC and the more common invasive ductal carcinoma (IDC).To our knowledge, such data is limited to first sites of distant recurrence. We aimed to perform a comparison of the metastatic pattern of ILC and IDC at first distant recurrence as well as over the entire course of metastatic disease.Methods We used a prospectively collated database of patients with metastatic breast cancer. Breast cancer recurrence or metastases were classified into various sites and a descriptive analysis was performed.Results Among 761 patients, 88 (11.6 %) were diagnosed with ILC and 673 (88.4 %) with IDC. Patients with ILC showed more frequent metastases to the bone (56.8 vs. 37.7 %, p = 0.001) and gastrointestinal (GI) tract (5.7 vs. 0.3 %, p < 0.001) as first site of distant recurrence, and less to organs such as lung (5.7 vs. 24.2 %, p < 0.001) and liver (4.6 vs. 11.4 %, p = 0.049). Over the entire course of metastatic disease, more patients with ILC had ovarian (5.7 vs. 2.1 %, p = 0.042) and GI tract metastases (8.0 vs. 0.6 %, p < 0.001), also demonstrating reduced tendency to metastasize to the liver (20.5 vs. 49.0 %, p < 0.001) and lung (23.9 vs. 51.9 %, p < 0.001). All associations but bone held after sensitivity analysis on hormonal status. Although patients presenting with ILC were noted to have more advanced stage at presentation, recurrence-free survival in these patients was increased (4.8 years vs. 3.2 years, p = 0.017). However, overall survival was not (2.5 vs. 2.0 years, p = 0.75).Conclusion After accounting for hormone receptor status, patients with IDC had greater lung/pleura and liver involvement, while patients with ILC had a greater propensity to develop ovarian and GI metastases both at first site and overall. Clinicians can use this information to provide more directed screening for metastases; it also adds to the argument that these two variants of breast cancer should be managed as unique diseases. ZUSAMMENFASSUNGEinleitung Invasiv-lobuläre Karzinome (ILC) machen rund

Familial, genome-wide association (GWAS), and sequencing studies and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWAS) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through novel application of a pleiotropy-guided conditional/conjunction false discovery rate approach for the first time in the setting of a TWAS. This identified 14 new candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 new candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were > 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. Overlaying candidate causal risk variants identified by GWAS fine mapping onto expression prediction models for genes at known loci suggested that the association for 55% of these genes was driven by the underlying GWAS signal. SignificanceThe 22 new genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

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