MicroRNA co-expression networks exhibit increased complexity in pancreatic ductal compared to Vater’s papilla adenocarcinoma

iRNA expression abnormalities in adenocarcinoma arising from pancreatic ductal system (PDAC) and Vater’s papilla (PVAC) could be associated with distinctive pathologic features and clinical cancer behaviours. Our previous miRNA expression profiling data on PDAC (n=9) and PVAC (n=4) were revaluated to define differences/ similarities in miRNA expression patterns. Afterwards, in order to uncover target genes and core signalling pathways regulated by specific miRNAs in these two tumour entities, miRNA interaction networks were wired for each tumour entity, and experimentally validated target genes underwent pathways enrichment analysis. One hundred and one miRNAs were altered, mainly over-expressed, in PDAC samples. Twenty-six miRNAs were deregulated in PVAC samples, where more miRNAs were down-expressed in tumours compared to normal tissues. Four miRNAs were significantly altered in both subgroups of patients, while 27 miRNAs were differentially expressed between PDAC and PVAC. Although miRNA interaction networks were more complex and dense in PDAC than in PVAC, pathways enrichment analysis uncovered a functional overlapping between PDAC and PVAC. However, shared signalling events were influenced by different miRNA and/or genes in the two tumour entities. Overall, specific miRNA expression patterns were involved in the regulation of a limited core signalling pathways in the biology landscape of PDAC and PVAC

Mirna Expression Profiles Identify Drivers in Colorectal and Pancreatic Cancers

Altered 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.Expression 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. in pancreatic cancers.MiRNA 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

SLC22A3 polymorphisms do not modify pancreatic cancer risk, but may influence overall patient survival

Expression of the solute carrier (SLC) transporter SLC22A3 gene is associated with overall survival of pancreatic cancer patients. This study tested whether genetic variability in SLC22A3 associates with pancreatic cancer risk and prognosis. Twenty four single nucleotide polymorphisms (SNPs) tagging the SLC22A3 gene sequence and regulatory elements were selected for analysis. Of these, 22 were successfully evaluated in the discovery phase while six significant or suggestive variants entered the validation phase, comprising a total study number of 1,518 cases and 3,908 controls. In the discovery phase, rs2504938, rs9364554, and rs2457571 SNPs were significantly associated with pancreatic cancer risk. Moreover, rs7758229 associated with the presence of distant metastases, while rs512077 and rs2504956 correlated with overall survival of patients. Although replicated, the association for rs9364554 did not pass multiple testing corrections in the validation phase. Contrary to the discovery stage, rs2504938 associated with survival in the validation cohort, which was more pronounced in stage IV patients. In conclusion, common variation in the SLC22A3 gene is unlikely to significantly contribute to pancreatic cancer risk. The rs2504938 SNP in SLC22A3 significantly associates with an unfavorable prognosis of pancreatic cancer patients. Further investigation of this SNP effect on the molecular and clinical phenotype is warranted

Promoter methylation correlates with reduced NDRG2 expression in advanced colon tumour

<p>Abstract</p> <p>Background</p> <p>Aberrant DNA methylation of CpG islands of cancer-related genes is among the earliest and most frequent alterations in cancerogenesis and might be of value for either diagnosing cancer or evaluating recurrent disease. This mechanism usually leads to inactivation of tumour-suppressor genes. We have designed the current study to validate our previous microarray data and to identify novel hypermethylated gene promoters.</p> <p>Methods</p> <p>The validation assay was performed in a different set of 8 patients with colorectal cancer (CRC) by means quantitative reverse-transcriptase polymerase chain reaction analysis. The differential RNA expression profiles of three CRC cell lines before and after 5-aza-2'-deoxycytidine treatment were compared to identify the hypermethylated genes. The DNA methylation status of these genes was evaluated by means of bisulphite genomic sequencing and methylation-specific polymerase chain reaction (MSP) in the 3 cell lines and in tumour tissues from 30 patients with CRC.</p> <p>Results</p> <p>Data from our previous genome search have received confirmation in the new set of 8 patients with CRC. In this validation set six genes showed a high induction after drug treatment in at least two of three CRC cell lines. Among them, the N-myc downstream-regulated gene 2 (<it>NDRG2) </it>promoter was found methylated in all CRC cell lines. <it>NDRG2 </it>hypermethylation was also detected in 8 out of 30 (27%) primary CRC tissues and was significantly associated with advanced AJCC stage IV. Normal colon tissues were not methylated.</p> <p>Conclusion</p> <p>The findings highlight the usefulness of combining gene expression patterns and epigenetic data to identify tumour biomarkers, and suggest that NDRG2 silencing might bear influence on tumour invasiveness, being associated with a more advanced stage.</p

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

We performed a multistage genome-wide association study 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 x 10(-12)), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2, OR = 1.46, 95% CI 1.30-1.65, P = 1.1 x 10(-10)), rs9581943 at 13q12.2 (PDX1, OR = 1.15, 95% CI 1.10-1.20, P = 2.4 x 10(-9)) and rs16986825 at 22q12.1 (ZNRF3, OR = 1.18, 95% CI 1.12-1.25, P = 1.2 x 10(-8)). We identified an independent signal in exon 2 of TERT at the established region 5p15.33 (rs2736098, OR = 0.80, 95% CI 0.76-0.85, P = 9.8 x 10(-14)). We also identified a locus at 8q24.21 (rs1561927, P = 1.3 x 10(-7)) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study identified multiple new susceptibility alleles for pancreatic cancer that are worthy of follow-up studies

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

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

Biological and functional analysis of statistically significant pathways deregulated in colon cancer by using gene expression profiles

Gene expression profiling offers a great opportunity for studying multi-factor diseases and for understanding the key role of genes in mechanisms which drive a normal cell to a cancer state. Single gene analysis is insufficient to describe the complex perturbations responsible for cancer onset, progression and invasion. A deeper understanding of the mechanisms of tumorigenesis can be reached focusing on deregulation of gene sets or pathways rather than on individual genes. We apply two known and statistically well founded methods for finding pathways and biological processes deregulated in pathological conditions by analyzing gene expression profiles. In particular, we measure the amount of deregulation and assess the statistical significance of predefined pathways belonging to a curated collection (Molecular Signature Database) in a colon cancer data set. We find that pathways strongly involved in different tumors are strictly connected with colon cancer. Moreover, our experimental results show that the study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. Our study shows the importance of using gene sets rather than single genes for understanding the main biological processes and pathways involved in colorectal cancer. Our analysis evidences that many of the genes involved in these pathways are strongly associated to colorectal tumorigenesis. In this new perspective, the focus shifts from finding differentially expressed genes to identifying biological processes, cellular functions and pathways perturbed in the phenotypic conditions by analyzing genes co-expressed in a given pathway as a whole, taking into account the possible interactions among them and, more importantly, the correlation of their expression with the phenotypical conditions.</p