Dataset Information

Rs488087 single nucleotide polymorphism as predictive risk factor for pancreatic cancers.

ABSTRACT: Pancreatic cancer (PC) is a devastating disease progressing asymptomatically until death within months after diagnosis. Defining at-risk populations should promote its earlier diagnosis and hence also avoid its development. Considering the known involvement in pancreatic disease of exon 11 of the bile salt-dependent lipase (BSDL) gene that encodes variable number of tandem repeat (VNTR) sequences, we hypothesized upon the existence of a genetic link between predisposition to PC and mutations in VNTR loci. To test this, BSDL VNTR were amplified by touchdown-PCR performed on genomic DNA extracted from cancer tissue or blood samples from a French patient cohort and amplicons were Sanger sequenced. A robust method using probes for droplet digital (dd)-PCR was designed to discriminate the C/C major from C/T or T/T minor genotypes. We report that the c.1719C > T transition (SNP rs488087) present in BSDL VNTR may be a useful marker for defining a population at risk of developing PC (occurrence: 63.90% in the PC versus 27.30% in the control group). The odds ratio of 4.7 for the T allele was larger than those already determined for other SNPs suspected to be predictive of PC. Further studies on tumor pancreatic tissue suggested that a germline T allele may favor Kras G12R/G12D somatic mutations which represent negative prognostic factors associated with reduced survival. We propose that the detection of the T allele in rs488087 SNP should lead to an in-depth follow-up of patients in whom an association with other potential risk factors of pancreatic cancer may be present.

SUBMITTER: Martinez E

PROVIDER: S-EPMC4741865 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Rs488087 single nucleotide polymorphism as predictive risk factor for pancreatic cancers.

Martinez Emmanuelle E Silvy Françoise F Fina Fréderic F Bartoli Marc M Krahn Martin M Barlesi Fabrice F Figarella-Branger Dominique D Iovanna Juan J Laugier René R Ouaissi Mehdi M Lombardo Dominique D Mas Eric E

Oncotarget 20151101 37

Pancreatic cancer (PC) is a devastating disease progressing asymptomatically until death within months after diagnosis. Defining at-risk populations should promote its earlier diagnosis and hence also avoid its development. Considering the known involvement in pancreatic disease of exon 11 of the bile salt-dependent lipase (BSDL) gene that encodes variable number of tandem repeat (VNTR) sequences, we hypothesized upon the existence of a genetic link between predisposition to PC and mutations in ...[more]

PMID: 26498142

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Project description:BACKGROUND: RECQL is a DNA helicase involved in DNA mismatch repair. The RECQL polymorphism, 3' untranslated region (UTR) A159C, was previously associated with overall survival of patients with resectable pancreatic adenocarcinoma treated with neoadjuvant chemoradiation. In the present study, we examined RECQL for somatic mutations and other polymorphisms and compared these findings with the outcome in patients who received adjuvant or neoadjuvant chemoradiation. We hypothesized that RECQL (i) would be mutated in cancer, (ii) would have polymorphisms linked to the 3'UTR A159C and that either or both events would affect function. We also hypothesized that (iii) these changes would be associated with survival in both cohorts of patients. MATERIAL AND METHODS: We sequenced RECQL's 15 exons and surrounding sequences in paired blood and tumour DNA of 39 patients. The 3'UTR A159C genotype was determined in blood DNA samples from 176 patients with resectable pancreatic adenocarcinoma treated with adjuvant (53) or neoadjuvant (123) chemoradiation. Survival was calculated using the Kaplan-Meier method, with log rank comparisons between groups. The relative impact of genotype on time to overall survival was performed using the Cox proportional hazards model. RESULTS: Somatic mutations were found in UTRs and intronic regions but not in exonic coding regions of the RECQL gene. Two single nucleotide polymorphisms (SNPs), located in introns 2 and 11, were found to be part of the same haplotype block as the RECQL A159C SNP and showed a similar association with overall survival. No short-term difference in survival between treatment strategies was found. We identified a subgroup of patients responsive to neoadjuvant therapy in which the 159 A allele conferred strikingly improved long-term survival. DISCUSSION: The RECQL 3'UTR A159C SNP is not linked with other functional SNPs within RECQL but may function as a site for regulatory molecules. The mechanism of action needs to be clarified further.

Project description:Risk prediction for a particular disease in a population through SNP genotyping exploits tests whose primary goal is to rank the SNPs on the basis of their disease association. This manuscript reveals a different approach of predicting the risk through network representation by using combined genotypic data (instead of a single allele/haplotype). The aim of this study is to classify diseased group and prediction of disease risk by identifying the responsible genotype. Genotypic combination is chosen from five independent loci present on platelet receptor genes P2RY1 and P2RY12. Genotype-sets constructed from combinations of genotypes served as a network input, the network architecture constituting super-nodes (e.g., case and control) and nodes representing individuals, each individual is described by a set of genotypes containing M markers (M = number of SNP). The analysis becomes further enriched when we consider a set of networks derived from the parent network. By maintaining the super-nodes identical, each network is carrying an independent combination of M-1 markers taken from M markers. For each of the network, the ratio of case specific and control specific connections vary and the ratio of super-node specific connection shows variability. This method of network has also been applied in another case-control study which includes oral cancer, precancer and control individuals to check whether it improves presentation and interpretation of data. The analyses reveal a perfect segregation between super-nodes, only a fraction of mixed state being connected to both the super-nodes (i.e. common genotype set). This kind of approach is favorable for a population to classify whether an individual with a particular genotypic combination can be in a risk group to develop disease. In addition with that we can identify the most important polymorphism whose presence or absence in a population can make a large difference in the number of case and control individuals.

Dataset Information

Rs488087 single nucleotide polymorphism as predictive risk factor for pancreatic cancers.

Publications

Rs488087 single nucleotide polymorphism as predictive risk factor for pancreatic cancers.

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