Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Reannotation of cancer mutations based on expressed RNA transcripts reveals novel functional non-coding mutations in melanoma.

ABSTRACT: The role of synonymous mutations in cancer pathogenesis is currently underexplored. We developed a method to detect significant clusters of synonymous and missense mutations in public cancer genomics data. In melanoma, we show that 22% (11/50) of these mutation clusters are misannotated as coding mutations because the reference transcripts used for their annotation are not expressed. Instead, these mutations are actually non-coding. This, for instance, applies to the mutation clusters targeting known cancer genes kinetochore localized astrin (SPAG5) binding protein (KNSTRN) and BCL2 like 12 (BCL2L12), each affecting 4-5% of melanoma patients. For the latter, we show that these mutations are functional non-coding mutations that target the shared promoter region of the interferon regulatory factor 3 (IRF3) and BCL2L12 genes. This results in downregulation of IRF3, BCL2L12 and tumor protein p53 (TP53) expression in a CRISPR-Cas9 primary melanocyte model and in melanoma patients, in which these mutations are also associated to a worse response to immunotherapy. Finally, we propose a simple automated method to more accurately annotate cancer mutations based on expressed transcripts. This work shows the importance of integrating DNA- and RNA-sequencing data to properly annotate mutations, and identifies a number of previously overlooked and wrongly annotated functional non-coding mutations in melanoma.

ORGANISM(S): Homo sapiens

PROVIDER: GSE290597 | GEO | 2025/03/31

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

Project description:The identification of functional non-coding mutations is a key challenge in the field of genomics, where whole-genome re-sequencing can swiftly generate a set of all genomic variants in a sample, such as a tumor biopsy. The size of the human regulatory landscape places a challenge on finding recurrent cis-regulatory mutations across samples of the same cancer type. Therefore, powerful computational approaches are required to sift through the tens of thousands of non-coding variants, to identify potentially functional variants that have an impact on the gene expression profile of the sample. Here we introduce an integrative analysis pipeline, called μ-cisTarget, to filter, annotate and prioritize non-coding variants based on their putative effect on the underlying 'personal' gene regulatory network. We first validate μ-cisTarget by re-analyzing three cases of oncogenic non-coding mutations, namely the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genome of ten cancer cell lines of six different cancer types, and used matched transcriptome data and motif discovery to infer master regulators for each sample. We identified candidate functional non-coding mutations that generate de novo binding sites for these master regulators, and that result in the up-regulation of nearby oncogenic drivers. We finally validated the predictions using tertiary data including matched epigenome data. Our approach is generally applicable to re-sequenced cancer genomes, or other genomes, when a disease- or sample-specific gene signature is available for network inference. μ-cisTarget is available from http://mucistarget.aertslab.org.

2017-07-14 | GSE101408 | GEO

Compensating the fitness costs of synonymous mutations

Project description:Synonymous mutations do not change the sequence of the polypeptide but they may still influence fitness. We investigated in Salmonella enterica how four synonymous mutations in the rpsT gene (encoding ribosomal protein S20) reduce fitness (i.e. growth rate) and the mechanisms by which this cost can be genetically compensated. The reduced growth rates of the synonymous mutants were correlated with reduced levels of the rpsT transcript and S20 protein. In an adaptive evolution experiment these fitness impairments could be compensated by mutations that either caused up-regulation of S20 through increased gene dosage (due to duplications), increased transcription of the rpsT gene (due to an rpoD mutation or mutations in rpsT), or increased translation from the rpsT transcript (due to rpsT mutations). We suggest that the reduced levels of S20 in the synonymous mutants result in production of a defective subpopulation of 30S subunits lacking S20 that reduce protein synthesis and bacterial growth and that the compensatory mutations restore S20 levels and the number of functional ribosomes. Our results demonstrate how specific synonymous mutations can cause substantial fitness reductions and that many different types intra- and extragenic compensatory mutations can efficiently restore fitness. Furthermore, our study highlights that also synonymous sites can be under strong selection, which may have implications for the use of dN/dS ratios as signature for selection.

2016-03-11 | PXD003495 | Pride

Mutations primarily alter the inclusion of alternatively spliced exons

Project description:Systematic mutagenesis has revealed that synonymous, non-synonymous and intronic mutations frequently alter the inclusion levels of alternatively spliced exons, suggesting that altered splicing might be a common mechanism by which mutations cause disease. However, most exons expressed in any cell are highly-included in mature mRNAs. Here, by performing deep mutagenesis of highly-included exons and by analysing the association between sequence variation and exon inclusion across the genome, we report that mutations only very rarely alter the inclusion of highly-included exons. This is true for both exonic and intronic mutations as well as for perturbations in trans. Therefore, mutations that affect splicing are not evenly distributed across the genome but are focussed in and around alternatively spliced exons with intermediate inclusion levels. These results provide a resource for prioritising synonymous and other variants as disease-causing mutations.

2020-06-29 | GSE151942 | GEO

LC-MSMS of the MHC-I immunopeptidome of human NSCLC samples

Project description:While immune checkpoint blockade (ICB) therapy has significantly improved the outcome of metastatic melanoma and non-small cell lung cancer (NSCLC), most patients do not derive long-term benefits. Previous studies suggest that treatment failure is partly due to insufficient immune recognition of tumor antigens (TAs). Notably, immune targeting of TAs has focused on TAs derived from non-synonymous genomic mutations. We used a proteogenomic approach combining RNA-sequencing and mass spectrometry to study the MHC I-immunopeptidome of cutaneous melanoma and NSCLC samples. The RNA-sequencing of each sample was used to construct sample-specific databases for the mass spectrometry-based identification of MHC I-associated peptides (MAPs). MAPs were then filtered based on their RNA expression in the respective cancer types from The Cancer Genome Atlas (TCGA-SKCM for melanoma MAPs, or TCGA-LUSC and TCGA-LUAD for NSCLC MAPs) vs. benign tissues (from the Genotype-Tissue Expression (GTEx) Project, medullary thymic epithelial cells, purified blood and bone marrow cells, and normal melanocytes for melanoma or bronchial brushing samples for NSCLC). MAPs were classified as mutated tumor-specific antigens (mTSAs, derived from non-synonymous mutations expressed in the sample of origin), or unmutated tumor antigens: aberrantly expressed tumor-specific antigens (aeTSAs, no/low expression in benign tissues and at least two times higher expression in TCGA), tumor-associated antigens (TAAs, significant expression in benign tissues and at least two times higher expression in TCGA), lineage-associated antigens (LSAs, specific expression to cancer and normal tissue of origin, i.e., lung and bronchial brushing samples for NSCLC or skin and melanocytes for melanoma). The tumor antigens described here represent attractive targets for immunotherapy of melanoma and NSCLC.

2025-02-19 | PXD043057 | Pride

LC-MSMS of the MHC-I immunopeptidome of human melanoma

2025-02-19 | PXD043059 | Pride

Desmosome mutations impact the tumor microenvironment to promote melanoma proliferation [Spatial transcriptomics]

Project description:Desmosomes are transmembrane protein complexes that contribute to cell-cell adhesion in epithelia and other tissues. Here, we report the discovery of frequent genetic alterations in the desmosome in human cancers, with the strongest signal seen in cutaneous melanoma where desmosomes are mutated in >70% of cases. In primary but not metastatic melanoma biopsies, the burden of coding mutations in desmosome genes associates with a strong reduction in desmosome gene expression. Analysis by spatial transcriptomics and protein immunofluorescence suggests that these expression decreases occur in keratinocytes in the microenvironment rather than in primary melanoma cells. In further support of a microenvironmental origin, we find that desmosome gene knockdown in keratinocytes yields markedly increased proliferation of adjacent melanoma cells in keratinocyte/melanoma co-cultures. Similar increases in melanoma proliferation are observed in media preconditioned by desmosome-deficient keratinocytes. Thus, gradual accumulation of desmosome mutations in neighboring cells may prime melanoma cells for neoplastic transformation.

2025-03-05 | GSE291159 | GEO

Desmosome mutations impact the tumor microenvironment to promote melanoma proliferation [scRNA-seq]

2025-03-08 | GSE291160 | GEO

GNPS - Tumour mitochondrial DNA mutations drive aerobic glycolysis to enhance checkpoint blockade

Project description:The mitochondrial genome encodes essential machinery for respiration and metabolic homeostasis but is paradoxically among the most common targets of somatic mutation in the cancer genome, with truncating mutations in respiratory complex I genes being most over-represented1. While mitochondrial DNA (mtDNA) mutations have been associated with both improved and worsened prognoses in several tumour lineages, whether these mutations are drivers or exert any functional effect on tumour biology remains controversial. Here we discovered that complex I-encoding mtDNA mutations are sufficient to remodel the tumour immune landscape and therapeutic resistance to immune checkpoint blockade. Using mtDNA base editing technology we engineered recurrent truncating mutations in the mtDNA-encoded complex I gene, Mt-Nd5, into murine models of melanoma. Mechanistically, these mutations promoted utilisation of pyruvate as a terminal electron acceptor and increased glycolytic flux driven by an over-reduced NAD pool and NADH shuttling between GAPDH and MDH1, mediating a Warburg-like metabolic shift. In turn, without modifying tumour growth, this altered cancer cell-intrinsic metabolism reshaped the tumour microenvironment promoting an anti-tumour immune response characterised by loss of resident neutrophils. This subsequently sensitised tumours bearing high mtDNA mutant heteroplasmy to immune checkpoint blockade, with phenocopy of key metabolic changes being sufficient to mediate this effect. Strikingly, patient lesions bearing >50% mtDNA mutation heteroplasmy also demonstrated a >2.5-fold improved response rate to checkpoint inhibitor blockade. Taken together these data nominate mtDNA mutations as functional regulators of cancer metabolism and tumour biology, with potential for therapeutic exploitation and treatment stratification.

2023-03-13 | MSV000091475 | GNPS

UVA-induced DNA damage and mutations in melanocytes and melanoma mutations

Project description:UVA-induced DNA damage and mutations in melanocytes and melanoma mutations

| PRJNA1251560 | ENA

Pathogenic mtDNA mutations inhibit melanoma metastasis

Project description:Pathogenic mtDNA mutations inhibit melanoma metastasis

| PRJNA1154298 | ENA