Rare germline deleterious variants increase susceptibility for lung cancer.

Although multiple common susceptibility loci for lung cancer (LC) have been identified by genome-wide association studies, they can explain only a small portion of heritability. The etiological contribution of rare deleterious variants (RDVs) to LC risk is not fully characterized and may account for part of the missing heritability. Here, we sequenced the whole exomes of 2777 participants from the Environment and Genetics in Lung cancer Etiology study, a homogenous population including 1461 LC cases and 1316 controls. In single-variant analyses, we identified a new RDV, rs77187983 [EHBP1, odds ratio (OR) = 3.13, 95% confidence interval (CI) = 1.34-7.30, P = 0.008] and replicated two previously reported RDVs, rs11571833 (BRCA2, OR = 2.18; 95% CI = 1.25-3.81, P = 0.006) and rs752672077 (MPZL2, OR = 3.70, 95% CI = 1.04-13.15, P = 0.044). In gene-based analyses, we confirmed BRCA2 (P = 0.007) and ATM (P = 0.014) associations with LC risk and identified TRIB3 (P = 0.009), involved in maintaining genome stability and DNA repair, as a new candidate susceptibility gene. Furthermore, cases were enriched with RDVs in homologous recombination repair [carrier frequency (CF) = 22.9% versus 19.5%, P = 0.017] and Fanconi anemia (CF = 12.5% versus 10.2%, P = 0.036) pathways. Our results were not significant after multiple testing corrections but were enriched in cases versus controls from large scale public biobank resources, including The Cancer Genome Atlas, FinnGen and UK Biobank. Our study identifies novel candidate genes and highlights the importance of RDVs in DNA repair-related genes for LC susceptibility. These findings improve our understanding of LC heritability and may contribute to the development of risk stratification and prevention strategies.

Assessment of Oncology Practice Billing Claims for Supplementing Chemotherapy: A Pilot Study in the Georgia SEER Cancer Registry.

BACKGROUND: Chemotherapy information in the population-based cancer registries is underascertained and lacks detail. We conducted a pilot study in the Georgia SEER Cancer Registry (GCR) to investigate the feasibility of supplementing chemotherapy information using billing claims from six private oncology practices (OP). METHODS: To assess cancer patients' representativeness from OP, we compared individuals with invasive first primary cancers diagnosed during 2013-2015 in the GCR (cohort 1) with those who had at least one OP claim in the 12 months after diagnosis (cohort 2). To assess completeness of OP claims to capture chemotherapy (yes or no), we further restricted cohort 2 to patients ages 65 years and older enrolled in fee-for-service Medicare Part A and B from the diagnosis date through 12 months follow-up or to the date of death. With Medicare data serving as the gold standard, sensitivity, specificity, and kappa statistics for the receipt of chemotherapy per OP claims were calculated by demographic and clinical characteristics. RESULTS: Cancer patients seeking care in the OP included in our analysis were not representative of the underlying patient population in the GCR. The practices underrepresented minorities and uninsured while overrepresenting females, persons with high socioeconomic status, patients residing outside the metropolitan Atlanta area, and persons with advance staged disease. The ability of practice claims to identify chemotherapy receipt was moderate (76.1% sensitivity) but varied by demographic and clinical characteristics (76.1-83.0%). CONCLUSIONS: Given the limited ability of OP claims to identify chemotherapy receipt, we suggest analyzing these data for hypothesis generation, but inference should be limited to this patient cohort.

Transcriptomes of human prostate cells.

BACKGROUND: The gene expression profiles of most human tissues have been studied by determining the transcriptome of whole tissue homogenates. Due to the solid composition of tissues it is difficult to study the transcriptomes of individual cell types that compose a tissue. To overcome the problem of heterogeneity we have developed a method to isolate individual cell types from whole tissue that are a source of RNA suitable for transcriptome profiling. RESULTS: Using monoclonal antibodies specific for basal (integrin beta4), luminal secretory (dipeptidyl peptidase IV), stromal fibromuscular (integrin alpha 1), and endothelial (PECAM-1) cells, respectively, we separated the cell types of the prostate with magnetic cell sorting (MACS). Gene expression of MACS-sorted cell populations was assessed with Affymetrix GeneChips. Analysis of the data provided insight into gene expression patterns at the level of individual cell populations in the prostate. CONCLUSION: In this study, we have determined the transcriptome profile of a solid tissue at the level of individual cell types. Our data will be useful for studying prostate development and cancer progression in the context of single cell populations within the organ.