Alternative splicing (AS) is a widespread process that increases structural transcript variation and proteome diversity. Aberrant splicing patterns are frequently observed in cancer initiation, progress, prognosis and therapy. Increasing evidence has demonstrated that AS events could undergo modulation by genetic variants. The identification of splicing quantitative trait loci (sQTLs), genetic variants that affect AS events, might represent an important step toward fully understanding the contribution of genetic variants in disease development. However, no database has yet been developed to systematically analyze sQTLs across multiple cancer types. Using genotype data from The Cancer Genome Atlas and corresponding AS values calculated by TCGASpliceSeq, we developed a computational pipeline to identify sQTLs from 9 026 tumor samples in 33 cancer types. We totally identified 4 599 598 sQTLs across all cancer types. We further performed survival analyses and identified 17 072 sQTLs associated with patient overall survival times. Furthermore, using genome-wide association study (GWAS) catalog data, we identified 1 180 132 sQTLs overlapping with known GWAS linkage disequilibrium regions. Finally, we constructed a user-friendly database, CancerSplicingQTL (http://www.cancersplicingqtl-hust.com/) for users to conveniently browse, search and download data of interest. This database provides an informative sQTL resource for further characterizing the potential functional roles of SNPs that control transcript isoforms in human cancer.

Protein post-translational modifications (PTMs), including phosphorylation, ubiquitination, methylation, acetylation, glycosylation et al, are very important biological processes. PTM changes in some critical genes, which may be induced by base-pair substitution, are shown to affect the risk of diseases. Recently, large-scale exome-wide association studies found that missense single nucleotide polymorphisms (SNPs) play an important role in the susceptibility for complex diseases or traits. One of the functional mechanisms of missense SNPs is that they may affect PTMs and leads to a protein dysfunction and its downstream signaling pathway disorder. Here, we constructed a database named AWESOME (A Website Exhibits SNP On Modification Event, http://www.awesome-hust.com), which is an interactive web-based analysis tool that systematically evaluates the role of SNPs on nearly all kinds of PTMs based on 20 available tools. We also provided a well-designed scoring system to compare the performance of different PTM prediction tools and help users to get a better interpretation of results. Users can search SNPs, genes or position of interest, filter with specific modifications or prediction methods, to get a comprehensive PTM change induced by SNPs. In summary, our database provides a convenient way to detect PTM-related SNPs, which may potentially be pathogenic factors or therapeutic targets.

Genome-wide association studies have identified common variants associated with risk of esophageal squamous cell carcinoma (ESCC). However, these common variants cannot explain all heritability of ESCC. Here we report an exome-wide interrogation of 3,714 individuals with ESCC and 3,880 controls for low-frequency susceptibility loci, with two independent replication samples comprising 7,002 cases and 8,757 controls. We found six new susceptibility loci in CCHCR1, TCN2, TNXB, LTA, CYP26B1 and FASN (P = 7.77 × 10−24 to P = 1.49 × 10−11), and three low-frequency variants had relatively high effect size (odds ratio > 1.5). Individuals with the rs138478634-GA genotype had significantly lower levels of serum all-trans retinoic acid, an anticancer nutrient, than those with the rs138478634-GG genotype (P = 0.0004), most likely due to an enhanced capacity of variant CYP26B1 to catabolize this agent. These findings emphasize the important role of rare coding variants in the development of ESCC.

Background MYC is a well-established cancer driver gene regulating the expression of numerous genes, indicating that polymorphisms in MYC response elements could affect tumorigenesis through altering MYC regulation. We performed integrative multistage study to evaluate the effects of variants in MYC response elements and colorectal cancer (CRC) risk. Patients and methods We systematically integrated ChIP-Seq, DNase-Seq and transcription factor motif data to screen variants with potential ability to affect the MYC binding affinity. Then, we conducted a two-stage case–control study, totally consisting of 4830 CRC cases and 4759 controls in Chinese population to identify risk polymorphisms and interactions. The effects of risk variants were confirmed by functional assays in CRC LoVo, SW480 and HCT15 cells. Results We identified a novel polymorphism rs11777210 in KBTBD11 significantly associated with CRC susceptibility (P = 2.43 × 10−12). Notably, we observed a significant interaction between rs11777210 and MYC nearby rs6983267 (P-multi = 0.003, P-add = 0.005), subjects carrying rs6983267 GG and rs11777210 CC genotypes showing higher susceptibility to CRC (2.83-fold) than those carrying rs6983267 TT and rs11777210 TT genotypes. We further demonstrated that rs6983267 T > G increased MYC expression, and MYC bound to and negatively regulated KBTBD11 expression when the rs11777210 C risk allele was present. KBTBD11 was downregulated in tumor tissues, and KBTBD11 knockdown promoted cell proliferation and inhibited cell apoptosis. Conclusion The rs11777210 is a potential predictive biomarker of CRC susceptibility, and KBTBD11 functions as a putative tumor suppressor in tumorigenesis. Our study highlighted the high CRC risk of people carrying rs6983267 G and rs11777210 C alleles, and provided possible biological mechanism of the interaction.

Germline coding variants have not been systematically investigated for pancreatic ductal adenocarcinoma (PDAC). Here we report an exome-wide investigation using the Illumina Human Exome Beadchip with 943 PDAC cases and 3908 controls in the Chinese population, followed by two independent replicate samples including 2142 cases and 4697 controls. We identify three low-frequency missense variants associated with the PDAC risk: rs34309238 in PKN1 (OR = 1.77, 95% CI: 1.48–2.12, P = 5.35 × 10−10), rs2242241 in DOK2 (OR = 1.85, 95% CI: 1.50–2.27, P = 4.34 × 10−9), and rs183117027 in APOB (OR = 2.34, 95% CI: 1.72–3.16, P = 4.21 × 10−8). Functional analyses show that the PKN1 rs34309238 variant significantly increases the level of phosphorylated PKN1 and thus enhances PDAC cells' proliferation by phosphorylating and activating the FAK/PI3K/AKT pathway. These findings highlight the significance of coding variants in the development of PDAC and provide more insights into the prevention of this disease.