Significantly mutated genes and regulatory pathways in SCLC-a meta-analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Sundaresan V
PROVIDER: S-EPMC5677515 | biostudies-literature | 2017 Oct
REPOSITORIES: biostudies-literature
Publications
Significantly mutated genes and regulatory pathways in SCLC-a meta-analysis.
Sundaresan Varsha V Lin Victor T VT Liang Faming F Kaye Frederic J FJ Kawabata-Iwakawa Reika R Shiraishi Kouya K Kohno Takashi T Yokota Jun J Zhou Lei L
Cancer genetics 20170607
Small cell lung cancer (SCLC) accounts for approximately 15% of all lung cancers and demands effective targeted therapeutic strategies. In this meta-analysis study, we aim to identify significantly mutated genes and regulatory pathways to help us better understand the progression of SCLC and to identify potential biomarkers. Besides ranking genes based on their mutation frequencies, we sought to identify statistically significant mutations in SCLC with the MutSigCV software. Our analysis identif ...[more]
Similar Datasets
Project description:Integration of the many available sources of cancer gene information--such as large-scale tumour-resequencing studies--identifies the 'usual suspect' genes, mutated in many tumour types, as well as different sets of mutated genes according to the specific tumour type. Scaling-up the analysis reveals that this large collection of mutated genes cluster into a smaller number of signalling pathways and processes. From this, we draw a map of the altered processes, and their combinations, in more than 10 tumours types. Literature searches identify pathways and processes that are covered sparsely in the literature, and invite the proposal of new hypotheses to investigate cancer initiation and progression.
| S-EPMC2948187 | biostudies-literature
Project description:BackgroundCancer 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 methodsWe 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.ResultsWe found 11 SNPs in 8 genes showed consistent association (P < 0.1) and 8 SNPs significantly associated with lung cancer risk (P < 0.05) in both discovery and validation phases. The most significant association was rs10412613 in PPP2R1A, with the minor G allele associated with a decreased risk of lung cancer [odds ratio = 0.91, 95% confidence interval (CI): 0.87-0.96, P = 2.3 × 10-4]. Cumulative analysis of risk score built as a weight sum of the 11 SNPs showed consistently elevated risk with increasing risk score (P for trend = 9.5 × 10-9). In stratified analyses, the association of PPP2R1A:rs10412613 and lung cancer risk appeared stronger among population of younger age at diagnosis and never smokers. The expression quantitative trait loci analysis indicated that rs10412613, rs10804682, rs635469 and rs6742399 genotypes significantly correlated with the expression of PPP2R1A, ATR, SETBP1 and ERBB4, respectively. From TCGA data, expression of the identified genes was significantly different in lung tumors compared with normal tissues, and the genes' highest mutation frequency was found in lung cancers. Integrative pathway analysis indicated the identified genes were mainly involved in AKT/NF-κB regulatory pathway suggesting the underlying biological processes.ConclusionThis study revealed novel genetic variants in SMGs associated with lung cancer risk, which might contribute to elucidating the biological network involved in lung cancer development.
| S-EPMC5834153 | biostudies-literature
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.
| S-EPMC9134657 | biostudies-literature
Project description:Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) whose aetiology is only partly understood. Investigating the intricate transcriptional changes occurring in MS brains is critical to unravel novel pathogenic mechanisms and therapeutic targets. Unfortunately, this process is often hindered by the difficulty in retrieving an adequate number of samples. However, by merging data from publicly available datasets, it is possible to identify alterations in gene expression profiles and regulatory pathways that were previously overlooked. Here, we merged microarray gene expression profiles obtained from CNS white matter samples taken from MS donors to identify novel differentially expressed genes (DEGs) linked with MS. Data from three independent datasets (GSE38010, GSE32915, and GSE108000) were combined and used to detect novel DEGs using the Stouffer's Z-score method. Corresponding regulatory pathways were analysed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, top up- and down-regulated transcripts were validated by real-time quantitative PCR (qPCR) using an independent set of white matter tissue samples obtained from MS donors with different disease subtypes. There were a total of 1446 DEGs, of which 742 were up-regulated and 704 genes were down-regulated. DEGs were associated with several myelin-related pathways and protein metabolism pathways. Validation studies of selected top up- or down-regulated genes highlighted MS subtype-specific differences in the expression of some of the identified genes, underlining a more complex scenario of white matter pathology amongst people afflicted by this devastating disease.
| S-EPMC10253947 | biostudies-literature
Project description:Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of >10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine.
| S-EPMC4945827 | biostudies-literature
Project description:Dysregulation of transcriptional pathways is observed in multiple forms of neurodevelopmental disorders (NDDs), such as intellectual disability (ID), epilepsy and autism spectrum disorder (ASD). We previously demonstrated that the NDD genes encoding lysine-specific demethylase 5C (KDM5C) and its transcriptional regulators Aristaless related-homeobox (ARX), PHD Finger Protein 8 (PHF8) and Zinc Finger Protein 711 (ZNF711) are functionally connected. Here, we show their relation to each other with respect to the expression levels in human and mouse datasets and in vivo mouse analysis indicating that the coexpression of these syntenic X-chromosomal genes is temporally regulated in brain areas and cellular sub-types. In co-immunoprecipitation assays, we found that the homeotic transcription factor ARX interacts with the histone demethylase PHF8, indicating that this transcriptional axis is highly intersected. Furthermore, the functional impact of pathogenic mutations of ARX, KDM5C, PHF8 and ZNF711 was tested in lymphoblastoid cell lines (LCLs) derived from children with varying levels of syndromic ID establishing the direct correlation between defects in the KDM5C-H3K4me3 pathway and ID severity. These findings reveal novel insights into epigenetic processes underpinning NDD pathogenesis and provide new avenues for assessing developmental timing and critical windows for potential treatments.
| S-EPMC8305412 | biostudies-literature
Project description:Abstract Age is major risk factor for AD; however, relationships between aging and AD are not well understood. Decline in physiological resilience is universal feature of human aging that may also play role in AD. Aging-related pathways (such as IGF-I/P53/mTOR-mediated) that are involved in tissue resilience work in concert to decide outcomes of cell responses to stress/damage, such as survival, apoptosis, autophagy, etc. We hypothesized that interplay among genes in these pathways may influence AD risk as result of epistasis (GxG). We estimated effects of pairwise epistasis between SNPs in 53 genes from respective pathways on AD risk in the LLFS compared with other data (HRS, CHS, LOADFS). We found significant (fdr<0.05) GxG effects on AD risk in older adults across datasets. The SNP rs11765954 in CDK6 gene was involved in top GxG effects on AD in all datasets, when paired with SNPs in BCL2 and PPARGC1A. The CDK6 role in AD could be pleiotropic, depending on its activity in neurons: CDK6 expression is needed for DNA repair and neuronal survival; however, CDK6 overexpression may lead to the cell cycle reentry in postmitotic neurons resulting in apoptosis, which may contribute to neurodegeneration. CDK6 was earlier found to interfere with BCL2 effects on apoptosis, and with PPARGC1A effects on energy metabolism, which might contribute to observed GxG between these genes. We conclude that interactions among genes from biologically connected aging pathways may significantly influence AD risk. Uncovering such GxG effects has a potential to yield new genetic targets for AD prevention/treatment.
| S-EPMC7741718 | biostudies-literature
Project description:Regulation of gene transcription in response to stress is central to a cell's ability to cope with environmental challenges. Taf14 is a YEATS domain protein in S.cerevisiae that physically associates with several transcriptionally relevant multisubunit complexes including the general transcription factors TFIID and TFIIF and the chromatin-modifying complexes SWI/SNF, INO80, RSC and NuA3. TAF14 deletion strains are sensitive to a variety of stresses suggesting that it plays a role in the transcriptional stress response.In this report we survey published genome-wide transcriptome and occupancy data to define regulatory properties associated with Taf14-dependent genes. Our transcriptome analysis reveals that stress related, TATA-containing and SAGA-dependent genes were much more affected by TAF14 deletion than were TFIID-dependent genes. Comparison of Taf14 and multiple transcription factor occupancy at promoters genome-wide identified a group of proteins whose occupancy correlates with that of Taf14 and whose proximity to Taf14 suggests functional interactions. We show that Taf14-repressed genes tend to be extensively regulated, positively by SAGA complex and the stress dependent activators, Msn2/4 and negatively by a wide number of repressors that act upon promoter chromatin and TBP.Taken together our analyses suggest a novel role for Taf14 in repression and derepression of stress induced genes, most probably as part of a regulatory network which includes Cyc8-Tup1, Srb10 and histone modifying enzymes.
| S-EPMC5312515 | biostudies-literature
Project description:Type 1 diabetes (T1D) is characterized by non-ideal mass and low survival rate of islets. Therefore, it is necessary to find intrinsic factors that prolong the survival of islets. This study aimed to track out hub genes and pathways in the process of islet culture by bioinformatic analysis. We downloaded the gene expression microarray of GSE42591 from the Gene Expression Omnibus (GEO). Aberrant Differentially methylated genes (DMGs) were obtained using the GEO2R tool. Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analyses were performed on selected genes by using the Database for Annotation Visualization and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed with the Retrieval of Interacting Genes (STRING) and visualized in Cytoscape 3.7.2. A total of 434 genes were overexpressed and 114 genes underexpressed in fresh to cultured 4 h tissue. KEGG pathway enrichment analyses revealed the TGF-beta signaling pathway, MAPK signaling pathway, or VEGF signaling pathway. The genes FN1, MKI67, IGF1, MAPK14, COL1A1 might be involved in islet culture. In general, this work scrutinized islet culture-relevant knowledge and provided insight into the regulation and mediation of islet survival.
| S-EPMC7868784 | biostudies-literature
Project description:Background:Esophageal squamous cell carcinoma (ESCC) is often diagnosed at an advanced and incurable stage. Information on driver genes and prognosticators in ESCC remains incomplete. The objective was to elucidate significantly mutated genes (SMGs), mutational signatures, and prognosticators in ESCC. Patients and methods:Three MutSig algorithms (i.e. MutSigCV, MutSigCL and MutSigFN) and '20/20+' ratio-metric were employed to identify SMGs. Nonnegative matrix factorization was used to decipher mutational signatures. Kaplan-Meier survival analysis, multivariate Cox and logistic regression models were applied to analyze association between mutational features and clinical parameters. Results:We identified 26 SMGs, including 8 novel (NAV3, TENM3, PTCH1, TGFBR2, RIPK4, PBRM1, USP8 and BAP1) and 18 that have been previously reported. Three mutational signatures were identified to be prevalent in ESCC including clocklike C>T at CpG, APOBEC overactive C>T at TpCp[A/T], and a signature featured by T>C substitution. The T>C mutational signature was significantly correlated with alcohol consumption (OR: 3.59; 95% CI: 2.30-5.67; P?<?0.001). This alcohol consumption signature was also observed in liver cancer and head and neck squamous cell carcinoma, and its mutational activity was substantially higher in samples with mutations in TP53. Survival analysis revealed that TENM3 mutations (HR: 5.54; CI: 2.68-11.45; P?<?0.001) and TP53 hotspot mutation p.R213* (HR: 3.37; CI: 1.73-8.06; P?<?0.001) were significantly associated with shortened survival outcome. The association remained statistically significant after controlling for age, gender, TNM stage and tumor grade. Conclusions:We have uncovered several new SMGs in ESCC and defined an alcohol consumption related mutational signature. TENM3 mutations and the TP53 hotspot mutation p.R213* are independent prognosticators for poor survival in ESCC.
| S-EPMC5913594 | biostudies-literature