Abstract Background: Over 20 susceptibility single-nucleotide polymorphisms (SNP) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett esophagus (BE), explaining a small portion of heritability. Methods: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene-expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTL), and set-based SKAT association using selected eQTLs that predict the gene expression. Results: Although the standard approach did not identify significant signals, the eQTL set–based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641, and HSP90AA1). Conclusions: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set–based genetic association approach. Impact: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set–based genetic association approach as an alternative method for TWAS analysis.
Genetic variants associated with circulating C‐reactive protein levels and colorectal cancer survival: Sex‐specific and lifestyle factors specific associations
AbstractElevated blood levels of C‐reactive protein (CRP) have been linked to colorectal cancer (CRC) survival. We evaluated genetic variants associated with CRP levels and their interactions with sex and lifestyle factors in association with CRC‐specific mortality. Our study included 16 142 CRC cases from the International Survival Analysis in Colorectal Cancer Consortium. We identified 618 common single nucleotide polymorphisms (SNPs) associated with CRP levels from the NHGRI‐EBI GWAS Catalog. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between SNPs and CRC‐specific mortality adjusting for age, sex, genotyping platform/study and principal components. We investigated their interactions with sex and lifestyle factors using likelihood ratio tests. Of 5472 (33.9%) deaths accrued over up to 10 years of follow‐up, 3547 (64.8%) were due to CRC. No variants were associated with CRC‐specific mortality after multiple comparison correction. We observed strong evidence of interaction between variant rs1933736 at FRK gene and sex in relation to CRC‐specific mortality (corrected Pinteraction = .0004); women had higher CRC‐specific mortality associated with the minor allele (HR = 1.11, 95% CI = 1.04‐1.19) whereas an inverse association was observed for men (HR = 0.88, 95% CI = 0.82‐0.94). There was no evidence of interactions between CRP‐associated SNPs and alcohol, obesity or smoking. Our study observed a significant interaction between sex and a CRP‐associated variant in relation to CRC‐specific mortality. Future replication of this association and functional annotation of the variant are needed.
A four‐gene transcript score to predict metastatic‐lethal progression in men treated for localized prostate cancer: Development and validation studies
AbstractBackgroundMolecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed.MethodsBased on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing datasets. Using the validated messenger RNAs and Gleason score (GS), we performed model selection in the training set to define a final locked model to classify patients who developed metastatic‐lethal events from those who remained recurrence‐free. In an independent testing dataset, we compared our locked model to established clinical prognostic factors and utilized Kaplan‐Meier curves and receiver operating characteristic analyses to evaluate the model's performance.ResultsThirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus GS were used to develop a four‐gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic‐lethal events compared to those without recurrence in the testing dataset (P = 5.7 × 10−11). The 4GT score provided higher prediction accuracy (area under the ROC curve [AUC] = 0.76; 95% confidence interval [CI] = 0.69‐0.83; partial area under the ROC curve [pAUC] = 0.008) than GS alone (AUC = 0.63; 95% CI = 0.56‐0.70; pAUC = 0.002), and it improved risk stratification in subgroups defined by a combination of clinicopathological features (ie, Cancer of the Prostate Risk Assessment‐Surgery).ConclusionOur validated 4GT score has prognostic value for metastatic‐lethal progression in men treated for localized PCa and warrants further evaluation for its clinical utility.