We performed a multistage genome-wide association study (GWAS) including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT; per-allele odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.74–0.84; P = 3.0×10−12), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2; OR = 1.46; 95% CI = 1.30–1.65; P = 1.1×10−10), rs9581943 at 13q12.2 (PDX1; OR = 1.15; 95% CI = 1.10–1.20; P = 2.4×10−9), and rs16986825 at 22q12.1 (ZNRF3; OR = 1.18; 95% CI = 1.12–1.25; P = 1.2×10−8). An independent signal was identified in exon 2 of TERT at the established region 5p15.33 (rs2736098; OR = 0.80; 95% CI = 0.76–0.85; P = 9.8×10−14). We also identified a locus at 8q24.21 (rs1561927; P = 1.3×10−7) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study has identified multiple new susceptibility alleles for pancreatic cancer worthy of follow-up studies.

Hp infection is associated with promoter methylation of genes which are relevant in the initiation and progression of gastric carcinogenesis. While CDH1 methylation seems to be an early event in Hp gastritis, MLH1 methylation occurs late along with IM. Hp eradication is able to significantly reduce gene methylation thus delaying or reversing Hp-induced gastric carcinogenesis.

The clock gene machinery controls cellular metabolism, proliferation, and key functions, such as DNA damage recognition and repair. Dysfunction of the circadian clock is involved in tumorigenesis, and altered expression of some clock genes has been found in cancer patients. The aim of this study was to evaluate the expression levels of core clock genes in colorectal cancer (CRC). Quantitative real-time polymerase chain reaction (qPCR) was used to examine ARNTL1, CLOCK, PER1, PER2, PER3, CRY1, CRY2, Timeless (TIM), TIPIN, and CSNK1? expression levels in the tumor tissue and matched apparently healthy mucosa of CRC patients. In the tumor tissue of CRC patients, compared to their matched healthy mucosa, expression levels of ARNTL1 (p=.002), PER1 (p=.002), PER2 (p=.011), PER3 (p=.003), and CRY2 (p=.012) were lower, whereas the expression level of TIM (p=.044) was higher. No significant difference was observed in the expression levels of CLOCK (p=.778), CRY1 (p=.600), CSNK1 (p=.903), and TIPIN (p=.136). As to the clinical and pathological features, a significant association was found between low CRY1 expression levels in tumor mucosa and age (p=.026), and female sex (p=.005), whereas high CRY1 expression levels in tumor mucosa were associated with cancer location in the distal colon (p?=?.015). Moreover, high TIM mRNA levels in the tumor mucosa were prevalent whenever proximal lymph nodes were involved (p= .013) and associated with TNM stages III-IV (p=.005) and microsatellite instability (p=.015). Significantly poorer survival rates were evidenced for CRC patients with lower expression in the tumor tissue of PER1 (p=.010), PER3 (p= .010), and CSNKIE (p=.024). In conclusion, abnormal expression levels of core clock genes in CRC tissue may be related to the process of tumorigenesis and exert an influence on host/tumor interactions.

Background and AimAltered expression of microRNAs (miRNAs) hallmarks many cancer types. The study of the associations of miRNA expression profile and cancer phenotype could help identify the links between deregulation of miRNA expression and oncogenic pathways.MethodsExpression profiling of 866 human miRNAs in 19 colorectal and 17 pancreatic cancers and in matched adjacent normal tissues was investigated. Classical paired t-test and random forest analyses were applied to identify miRNAs associated with tissue-specific tumors. Network analysis based on a computational approach to mine associations between cancer types and miRNAs was performed.ResultsThe merge between the two statistical methods used to intersect the miRNAs differentially expressed in colon and pancreatic cancers allowed the identification of cancer-specific miRNA alterations. By miRNA-network analysis, tissue-specific patterns of miRNA deregulation were traced: the driving miRNAs were miR-195, miR-1280, miR-140-3p and miR-1246 in colorectal tumors, and miR-103, miR-23a and miR-15b in pancreatic cancers.ConclusionMiRNA expression profiles may identify cancer-specific signatures and potentially useful biomarkers for the diagnosis of tissue specific cancers. miRNA-network analysis help identify altered miRNA regulatory networks that could play a role in tumor pathogenesis.