Dataset Information

Genetic variations in cancer-related significantly mutated genes and lung cancer susceptibility.

ABSTRACT: Background:Cancer initiation and development are driven by key mutations in driver genes. Applying high-throughput sequencing technologies and bioinformatic analyses, The Cancer Genome Atlas (TCGA) project has identified panels of somatic mutations that contributed to the etiology of various cancers. However, there are few studies investigating the germline genetic variations in these significantly mutated genes (SMGs) and lung cancer susceptibility. Patients and methods:We comprehensively evaluated 1655 tagged single nucleotide polymorphisms (SNPs) located in 127 SMGs identified by TCGA, and test their association with lung cancer risk in large-scale case-control study. Functional effect of the validated SNPs, gene mutation frequency and pathways were analyzed. Results:We found 11 SNPs in 8 genes showed consistent association (P?

SUBMITTER: Zhang Y

PROVIDER: S-EPMC5834153 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic variations in cancer-related significantly mutated genes and lung cancer susceptibility.

Zhang Y Y Zhang L L Li R R Chang D W DW Ye Y Y Minna J D JD Roth J A JA Han B B Wu X X

Annals of oncology : official journal of the European Society for Medical Oncology 20170701 7

<h4>Background</h4>Cancer initiation and development are driven by key mutations in driver genes. Applying high-throughput sequencing technologies and bioinformatic analyses, The Cancer Genome Atlas (TCGA) project has identified panels of somatic mutations that contributed to the etiology of various cancers. However, there are few studies investigating the germline genetic variations in these significantly mutated genes (SMGs) and lung cancer susceptibility.<h4>Patients and methods</h4>We compre ...[more]

PMID: 28383694

Similar Datasets

Project description:BACKGROUND:Cytochrome P450 (CYPs) are heme proteins involved in the metabolism of a variety of endogenous and exogenous substances and play an important role in the carcinogenesis mechanisms of environmental and hereditary factors. The objective of this study was to investigate how polymorphisms of CYPs correlate with lung cancer (LC) susceptibility. METHODS:Six single nucleotide polymorphisms (SNPs) were genotyped in this study. The chi-square test and unconditional logistic regression model were used to evaluate the correlation between SNPs and LC susceptibility. The expressions and survival data of genes in patients with LC were mined using Oncomine and Kaplan-Meier Plotter database. RESULTS:Four SNPs were found to be significantly associated with the risk of LC development (P < 0.05). The most significant correlation was that the A allele and AA genotype of CYP2D6 rs1065852 were associated with increased risk of LC development (adjusted odds ratio [OR] = 1.35, 95% confidence interval [95%CI] = 1.13-1.60, P = 9.04e-4; OR = 1.83, 95%CI = 1.29-2.59, P = 0.001 respectively). Similar association of this variant was also found in the subgroups of male patients, cases in III-IV stages, positive lymph node, squamous cell carcinomas and adenocarcinomas. Whereas rs1065852 was considered as protective factor in females (adjusted OR = 0.33, 95% CI = 0.16-0.70, P = 0.004). In stratified analyses, the association of CYP24A1 rs2762934, CYP24A1 rs6068816, CYP20A1 rs2043449 polymorphism with LC risk appeared stronger in some subgroups. CYP2D6, CYP24A1 and CYP20A1 are overexpressed in some pathological types of LC (P < 0.05), and high levels of CYP2D6 and CYP20A1 indicate poor and good prognosis of LC, respectively. CONCLUSION:This study revealed that rs1065852, rs2043449, rs2762s934, and rs6068816 of CYPs were associated with LC susceptibility in the Northwestern Chinese Han population; CYP2D6 and CYP20A1 were overexpressed and correlated with prognosis of LC.

Project description:BackgroundMutated and non-mutated genes interact to drive cancer growth and metastasis. While research has focused on understanding the impact of mutated genes on cancer biology, understanding non-mutated genes that are essential to tumor development could lead to new therapeutic strategies. The recent advent of high-throughput whole genome sequencing being applied to many different samples has made it possible to calculate if genes are significantly non-mutated in a specific cancer patient cohort.MethodsWe carried out random mutagenesis simulations of the human genome approximating the regions sequenced in the publicly available Cancer Growth Atlas Project for ovarian cancer (TCGA-OV). Simulated mutations were compared to the observed mutations in the TCGA-OV cohort and genes with the largest deviations from simulation were identified. Pathway analysis was performed on the non-mutated genes to better understand their biological function. We then compared gene expression, methylation and copy number distributions of non-mutated and mutated genes in cell lines and patient data from the TCGA-OV project. To directly test if non-mutated genes can affect cell proliferation, we carried out proof-of-concept RNAi silencing experiments of a panel of nine selected non-mutated genes in three ovarian cancer cell lines and one primary ovarian epithelial cell line.ResultsWe identified a set of genes that were mutated less than expected (non-mutated genes) and mutated more than expected (mutated genes). Pathway analysis revealed that non-mutated genes interact in cancer associated pathways. We found that non-mutated genes are expressed significantly more than mutated genes while also having lower methylation and higher copy number states indicating that they could be functionally important. RNAi silencing of the panel of non-mutated genes resulted in a greater significant reduction of cell viability in the cancer cell lines than in the non-cancer cell line. Finally, as a test case, silencing ANKLE2, a significantly non-mutated gene, affected the morphology, reduced migration, and increased the chemotherapeutic response of SKOV3 cells.ConclusionWe show that we can identify significantly non-mutated genes in a large ovarian cancer cohort that are well-expressed in patient and cell line data and whose RNAi-induced silencing reduces viability in three ovarian cancer cell lines. Targeting non-mutated genes that are important for tumor growth and metastasis is a promising approach to expand cancer therapeutic options.

Dataset Information

Genetic variations in cancer-related significantly mutated genes and lung cancer susceptibility.

Publications

Genetic variations in cancer-related significantly mutated genes and lung cancer susceptibility.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets