Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function.

ABSTRACT:

Background

Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown.

Methods

We used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks.

Results

Each tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be 'cores' of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes.

Conclusions

This approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies.

SUBMITTER: Fagny M

PROVIDER: S-EPMC7028992 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

SNPs in human miRNA genes affect biogenesis and function.

Project description:MicroRNAs (miRNAs) are 21-25-nucleotide-long, noncoding RNAs that are involved in translational regulation. Most miRNAs derive from a two-step sequential processing: the generation of pre-miRNA from pri-miRNA by the Drosha/DGCR8 complex in the nucleus, and the generation of mature miRNAs from pre-miRNAs by the Dicer/TRBP complex in the cytoplasm. Sequence variation around the processing sites, and sequence variations in the mature miRNA, especially the seed sequence, may have profound affects on miRNA biogenesis and function. In the context of analyzing the roles of miRNAs in Schizophrenia and Autism, we defined at least 24 human X-linked miRNA variants. Functional assays were developed and performed on these variants. In this study we investigate the affects of single nucleotide polymorphisms (SNPs) on the generation of mature miRNAs and their function, and report that naturally occurring SNPs can impair or enhance miRNA processing as well as alter the sites of processing. Since miRNAs are small functional units, single base changes in both the precursor elements as well as the mature miRNA sequence may drive the evolution of new microRNAs by altering their biological function. Finally, the miRNAs examined in this study are X-linked, suggesting that the mutant alleles could be determinants in the etiology of diseases.

| S-EPMC2743066 | biostudies-literature

Somatic selection distinguishes oncogenes and tumor suppressor genes.

Project description:MotivationFunctions of cancer driver genes vary substantially across tissues and organs. Distinguishing passenger genes, oncogenes (OGs) and tumor-suppressor genes (TSGs) for each cancer type is critical for understanding tumor biology and identifying clinically actionable targets. Although many computational tools are available to predict putative cancer driver genes, resources for context-aware classifications of OGs and TSGs are limited.ResultsWe show that the direction and magnitude of somatic selection of protein-coding mutations are significantly different for passenger genes, OGs and TSGs. Based on these patterns, we develop a new method (genes under selection in tumors) to discover OGs and TSGs in a cancer-type specific manner. Genes under selection in tumors shows a high accuracy (92%) when evaluated via strict cross-validations. Its application to 10 172 tumor exomes found known and novel cancer drivers with high tissue-specificities. In 11 out of 13 OGs shared among multiple cancer types, we found functional domains selectively engaged in different cancers, suggesting differences in disease mechanisms.Availability and implementationAn R implementation of the GUST algorithm is available at https://github.com/liliulab/gust. A database with pre-computed results is available at https://liliulab.shinyapps.io/gust.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC7703750 | biostudies-literature

Classical oncogenes and tumor suppressor genes: a comparative genomics perspective.

Project description:We have curated a reference set of cancer- related genes and reanalyzed their sequences in the light of molecular information and resources that have become available since they were first cloned. Homology studies were carried out for human oncogenes and tumor suppressors, compared with the complete proteome of the nematode, Caenorhabditis elegans, and partial proteomes of mouse and rat and the fruit fly, Drosophila melanogaster. Our results demonstrate that simple, semi-automated bioinformatics approaches to identifying putative functionally equivalent gene products in different organisms may often be misleading. An electronic supplement to this article provides an integrated view of our comparative genomics analysis as well as mapping data, physical cDNA resources and links to published literature and reviews, thus creating a "window" into the genomes of humans and other organisms for cancer biology.

| S-EPMC1507562 | biostudies-literature

An in vivo screen identifies ependymoma oncogenes and tumor-suppressor genes.

Project description:Cancers are characterized by non-random chromosome copy number alterations that presumably contain oncogenes and tumor-suppressor genes (TSGs). The affected loci are often large, making it difficult to pinpoint which genes are driving the cancer. Here we report a cross-species in vivo screen of 84 candidate oncogenes and 39 candidate TSGs, located within 28 recurrent chromosomal alterations in ependymoma. Through a series of mouse models, we validate eight new ependymoma oncogenes and ten new ependymoma TSGs that converge on a small number of cell functions, including vesicle trafficking, DNA modification and cholesterol biosynthesis, identifying these as potential new therapeutic targets.

| S-EPMC4520751 | biostudies-literature

Bioinformatic Analysis of Circadian Expression of Oncogenes and Tumor Suppressor Genes.

Project description:BackgroundCircadian rhythms are physiological and behavioral cycles with a period of approximately 24 hours that control various functions including gene expression. Circadian disruption is associated with a variety of diseases, especially cancer. Although some of the oncogenes and tumor suppressor genes (TSGs) are known as clock-controlled genes (CCGs), the analysis and annotation of circadian expression of most human oncogenes and TSGs are still lacking. This study aims to investigate the circadian expression of a list of human oncogenes and TSGs.MethodsA bioinformatic analysis was conducted on a gene library comprising 120 genes to investigate the circadian expression of human oncogenes and TSGs. To achieve this purpose, the genotranscriptomic data were retrieved from COSMIC and analyzed by R statistical software. Furthermore, the acquired data were analyzed at the transcriptomic and proteomic levels using several publicly available databases. Also, the significance of all analyses was confirmed statistically.ResultsAltogether, our results indicated that 7 human oncogenes/TSGs may be expressed and function in a circadian manner. These oncogenes/TSGs showed a circadian expression pattern at CircaDB database and associated with at least one of the circadian genes/CCGs based on both genotranscriptomic and correlation analyses.ConclusionsAlthough 4 of 7 finally outputted genes have been previously reported to be clock controlled, heretofore there is no report about the circadian expression of 3 other genes. Considering the importance of oncogenes/TSGs in the initiation and progression of cancer, further studies are suggested for the identification of exact circadian expression patterns of these 3 human oncogenes/TSGs.

| S-EPMC5734456 | biostudies-literature

miR-196b directly targets both HOXA9/MEIS1 oncogenes and FAS tumour suppressor in MLL-rearranged leukaemia.

Project description:HOXA9 and MEIS1 have essential oncogenic roles in mixed lineage leukaemia (MLL)-rearranged leukaemia. Here we show that they are direct targets of miRNA-196b, a microRNA (miRNA) located adjacent to and co-expressed with HOXA9, in MLL-rearranged leukaemic cells. Forced expression of miR-196b significantly delays MLL-fusion-mediated leukemogenesis in primary bone marrow transplantation through suppressing Hoxa9/Meis1 expression. However, ectopic expression of miR-196b results in more aggressive leukaemic phenotypes and causes much faster leukemogenesis in secondary transplantation than MLL fusion alone, likely through the further repression of Fas expression, a proapoptotic gene downregulated in MLL-rearranged leukaemia. Overexpression of FAS significantly inhibits leukemogenesis and reverses miR-196b-mediated phenotypes. Targeting Hoxa9/Meis1 and Fas by miR-196b is probably also important for normal haematopoiesis. Thus, our results uncover a previously unappreciated miRNA-regulation mechanism by which a single miRNA may target both oncogenes and tumour suppressors, simultaneously, or, sequentially, in tumourigenesis and normal development per cell differentiation, indicating that miRNA regulation is much more complex than previously thought.

| S-EPMC3514459 | biostudies-literature

Impact of SNPs on CpG Islands in the MYC and HRAS oncogenes and in a wide variety of tumor suppressor genes: A multi-cancer approach.

Project description:Single nucleotide polymorphisms (SNPs) that occur within CpG Islands may lead to increased hypermethylation if a SNP allele has the potential to form a CpG dinucleotide, as well as potentially lead to hypomethylation if a SNP allele eliminates a CpG dinucleotide. We analyzed CpG-related SNP allele frequencies in whole genome sequences (WGS) across 5 TCGA cancer datasets, thereby exploiting a more recent appreciation for signaling pathway degeneracy in cancer. The cancer data sets were analyzed for SNPs in CpG islands associated with the oncogenes, HRAS and MYC, and in the CpG islands associated with the tumor suppressor genes, APC, DCC, and RB1. We determined that one SNP allele (rs3824120) in a CpG island associated with MYC which eliminated a CpG was more common in the cancer datasets than in the 100Genomes databases (p < 0.01). For HRAS, 2 SNP alleles (rs112690925, rs7939028) that created CpG's occurred significantly less frequently in the cancer data sets than in the general SNP databases (e.g., rs7939028, p < 0.0002, in comparison with AllSNPs(142)). Also, one SNP allele (rs4940177) that created a CpG in a CpG island associated with the DCC tumor suppressor gene, was more common in the cancer datasets (p < 0.0007). To understand a broader picture of the potential of SNP alleles to create CpG's in CpG islands of tumor suppressor genes, we developed a scripted algorithm to assess the SNP alleles associated with the CpG islands of 43 tumor suppressor genes. The following tumor suppressor genes have the possibility of significant, percent increases in their CpG counts, depending on which SNP allele(s) is present: VHL, BRCA1, BRCA2, CHEK2, PTEN and RB1.

| S-EPMC4934054 | biostudies-literature

RNA-DNA differences are rarer in proto-oncogenes than in tumor suppressor genes.

Project description:It has long been assumed that DNA sequences and corresponding RNA transcripts are almost identical; a recent discovery, however, revealed widespread RNA-DNA differences (RDDs), which represent a largely unexplored aspect of human genome variation. It has been speculated that RDDs can affect disease susceptibility and manifestations; however, almost nothing is known about how RDDs are related to disease. Here, we show that RDDs are rarer in proto-oncogenes than in tumor suppressor genes; the number of RDDs in coding exons, but not in 3'UTR and 5'UTR, is significantly lower in the former than the latter, and this trend is especially pronounced in non-synonymous RDDs, i.e., those cause amino acid changes. A potential mechanism is that, unlike proto-oncogenes, the requirement of tumor suppressor genes to have both alleles affected to cause tumor 'buffers' these genes to tolerate more RDDs.

| S-EPMC3270091 | biostudies-literature

Integrated transcriptome interactome study of oncogenes and tumor suppressor genes in breast cancer.

Project description:Breast cancer is the leading cause for mortality among women worldwide. Dysregulation of oncogenes and tumor suppressor genes is the major reason for the cause of cancer. Understanding these genes will provide clues and insights about their regulatory mechanism and their interplay in cancer. In the present study, an attempt is made to compare the functional characteristics and interactions of oncogenes and tumor suppressor genes to understand their biological role. 431 breast cancer samples from seven publicly available microarray datasets were collected and analysed using GEO2R tool. The identified 416 differentially expressed genes were classified into five gene sets as oncogenes (OG), tumor suppressor genes (TSG), druggable genes, essential genes and other genes. The gene sets were subjected to various analysis such as enrichment analysis (viz., GO, Pathways, Diseases and Drugs), network analysis, calculation of mutation frequencies and Guanine-Cytosine (GC) content. From the results, it was observed that the OG were having high GC content as well as high interactions than TSG. Moreover, the OG are found to have frequent mutations than TSG. The enrichment analysis results suggest that the oncogenes are involved in positive regulation of cellular protein metabolic process, macromolecule biosynthetic process and majorly in cell cycle and focal adhesion pathway in cancer. It was also found that these oncogenes are involved in other diseases such as skin diseases and viral infections. Collagenase, paclitaxel and docetaxel are some of the drugs found to be enriched for oncogenes.

| S-EPMC6411624 | biostudies-literature

DORGE: Discovery of Oncogenes and tumoR suppressor genes using Genetic and Epigenetic features.

Project description:Data-driven discovery of cancer driver genes, including tumor suppressor genes (TSGs) and oncogenes (OGs), is imperative for cancer prevention, diagnosis, and treatment. Although epigenetic alterations are important for tumor initiation and progression, most known driver genes were identified based on genetic alterations alone. Here, we developed an algorithm, DORGE (Discovery of Oncogenes and tumor suppressoR genes using Genetic and Epigenetic features), to identify TSGs and OGs by integrating comprehensive genetic and epigenetic data. DORGE identified histone modifications as strong predictors for TSGs, and it found missense mutations, super enhancers, and methylation differences as strong predictors for OGs. We extensively validated DORGE-predicted cancer driver genes using independent functional genomics data. We also found that DORGE-predicted dual-functional genes (both TSGs and OGs) are enriched at hubs in protein-protein interaction and drug-gene networks. Overall, our study has deepened the understanding of epigenetic mechanisms in tumorigenesis and revealed previously undetected cancer driver genes.

| S-EPMC7673741 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data