Pan-cancer analysis of somatic mutations in miRNA genes

ABSTRACTmiRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied. Here, based on analysis of the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we identified and characterized over 10,000 somatic mutations in miRNA genes and showed that some of the genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival. Our results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.

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NEPdb: A Database of T-Cell Experimentally-Validated Neoantigens and Pan-Cancer Predicted Neoepitopes for Cancer Immunotherapy

Frontiers in Immunology ◽

10.3389/fimmu.2021.644637 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jiaqi Xia ◽

Peng Bai ◽

Weiliang Fan ◽

Qiming Li ◽

Yongzheng Li ◽

...

Keyword(s):

T Cell ◽

Cancer Immunotherapy ◽

Somatic Mutations ◽

Tumor Regression ◽

Human Leukocyte ◽

T Cell Recognition ◽

Leukocyte Antigens ◽

Pan Cancer ◽

Automatic Pipeline ◽

Cancer Studies

T-cell recognition of somatic mutation-derived cancer neoepitopes can lead to tumor regression. Due to the difficulty to identify effective neoepitopes, constructing a database for sharing experimentally validated cancer neoantigens will be beneficial to precise cancer immunotherapy. Meanwhile, the routine neoepitope prediction in silico is important but laborious for clinical use. Here we present NEPdb, a database that contains more than 17,000 validated human immunogenic neoantigens and ineffective neoepitopes within human leukocyte antigens (HLAs) via curating published literature with our semi-automatic pipeline. Furthermore, NEPdb also provides pan-cancer level predicted HLA-I neoepitopes derived from 16,745 shared cancer somatic mutations, using state-of-the-art predictors. With a well-designed search engine and visualization modes, this database would enhance the efficiency of neoantigen-based cancer studies and treatments. NEPdb is freely available at http://nep.whu.edu.cn/.

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Pan-cancer analysis of somatic mutations and epigenetic alterations in insulated neighbourhood boundaries

PLoS ONE ◽

10.1371/journal.pone.0227180 ◽

2020 ◽

Vol 15 (1) ◽

pp. e0227180 ◽

Cited By ~ 1

Author(s):

Pietro Pinoli ◽

Eirini Stamoulakatou ◽

An-Phi Nguyen ◽

María Rodríguez Martínez ◽

Stefano Ceri

Keyword(s):

Somatic Mutations ◽

Epigenetic Alterations ◽

Pan Cancer

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Comprehensive pan-cancer analysis of somatic mutations in drug transporters to reveal acquired and intrinsic drug resistance in 3149 metastatic cancer patients

Annals of Oncology ◽

10.1093/annonc/mdz239.011 ◽

2019 ◽

Vol 30 ◽

pp. v28-v29

Author(s):

S. Bins ◽

W.S. van de Geer ◽

J. van Riet ◽

N. Steeghs ◽

H.M.W. Verheul ◽

...

Keyword(s):

Drug Resistance ◽

Cancer Patients ◽

Somatic Mutations ◽

Metastatic Cancer ◽

Drug Transporters ◽

Intrinsic Drug Resistance ◽

Pan Cancer

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Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes

Nature Genetics ◽

10.1038/ng.3168 ◽

2014 ◽

Vol 47 (2) ◽

pp. 106-114 ◽

Cited By ~ 473

Author(s):

Mark D M Leiserson ◽

Fabio Vandin ◽

Hsin-Ta Wu ◽

Jason R Dobson ◽

Jonathan V Eldridge ◽

...

Keyword(s):

Network Analysis ◽

Somatic Mutations ◽

Protein Complexes ◽

Cancer Network ◽

Pan Cancer

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Motif Disruption Domains Lead To Cancer Gene Expression Rewiring

10.1101/126359 ◽

2017 ◽

Cited By ~ 1

Author(s):

Fabien C. Lamaze ◽

Aurelien Chateigner ◽

Hilary A. Edgington ◽

Marie-Julie Fave ◽

Armande Ang Houle ◽

...

Keyword(s):

Gene Expression ◽

Somatic Mutations ◽

Functional Characterization ◽

Mutation Accumulation ◽

Open Chromatin ◽

Coding Regions ◽

Gene Dysregulation ◽

Insulator Elements ◽

Gene Expression Dysregulation ◽

Pan Cancer

AbstractSomatic mutations accumulate in non-coding regions of the genome during tumorigenesis, but their functional characterization presents a challenge. Somatic non-coding mutations rarely overlap among patients, which necessitates large sample sizes to detect associations. We analysed somatic mutations called from whole-genome sequencing (WGS) and RNA sequencing (RNAseq) from 3000 tumors across the Pan-Cancer Analysis of Whole Genomes to identify and functionally characterize mutation accumulation and its impact on gene dysregulation in cancer. We identified 1.5 million motif disruption domains (MDDs) across 40 cancer types, which we characterized as pan-cancer targets for recurrent mutation accumulation. These MDDs deregulate gene expression in cancer-specific and pan-cancer patterns by disrupting transcription factor binding sites in regulatory and insulator elements. Disruption is most recurrent across individuals at MDDs in conserved open chromatin, revealing potential drivers. This accumulation of somatic variants targeting regulatory and structural elements in MDDs generates gene expression dysregulation during tumorigenesis.

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A domain-resolution map of in vivo DNA binding reveals the regulatory consequences of somatic mutations in zinc finger transcription factors

10.1101/630756 ◽

2019 ◽

Cited By ~ 2

Author(s):

Berat Dogan ◽

Senthilkumar Kailasam ◽

Aldo Hernández Corchado ◽

Naghmeh Nikpoor ◽

Hamed S. Najafabadi

Keyword(s):

Transcription Factors ◽

Dna Binding ◽

Zinc Finger ◽

Somatic Mutations ◽

Eqtl Analysis ◽

Context Aware ◽

Dna Binding Specificity ◽

Binding Data ◽

Pan Cancer

ABSTRACTMulti-zinc finger proteins constitute the largest class of human transcription factors. Their DNA-binding specificity is usually encoded by a subset of their tandem Cys2His2 zinc finger (ZF) domains – the subset that binds to DNA, however, is often unknown. Here, by combining a context-aware machine-learning-based model of DNA recognition with in vivo binding data, we characterize the sequence preferences and the ZF subset that is responsible for DNA binding in 209 human multi-ZF proteins. We show that in vivo DNA binding is primarily driven by ∼50% of the ZFs – these DNA-binding ZFs are under strong selective pressure within and across species, and their mutations affect the expression of hundreds of genes as revealed by pan-cancer trans-eQTL analysis across 18 tissues. Among the genes affected by mutations in multi-ZF proteins, we identify several oncogenic factors regulated by SP1, and show that SP1 up-regulation in cancer promotes the expression of these genes while mutations in SP1 ZFs lead to their repression. Together, these analyses suggest that mutations in DNA-binding ZFs have distinct and widespread regulatory consequences that contribute to transcriptome remodelling in cancer.

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Ennet: construction of potential cancer-driving networks based on somatic enhancer mutations only

10.1101/216226 ◽

2017 ◽

Author(s):

Ya Cui ◽

Yiwei Niu ◽

Xueyi Teng ◽

Dan Wang ◽

Huaxia Luo ◽

...

Keyword(s):

Neural Development ◽

Somatic Mutations ◽

Gene Interactions ◽

Whole Genome ◽

Sequencing Technology ◽

Cancer Types ◽

Cancer Drivers ◽

New Perspective ◽

Pan Cancer ◽

Potential Cancer

AbstractWhole genome sequencing technology has facilitated the discovery of a large number of somatic mutations in enhancers (SMEs), whereas the utility of SMEs in tumorigenesis has not been fully explored. Here we present Ennet, a method to comprehensively investigate SMEs enriched networks (SME-networks) in cancer by integrating SMEs, enhancer-gene interactions and gene-gene interactions. Using Ennet, we performed a pan-cancer analysis in 2004 samples from 8 cancer types and found many well-known cancer drivers were involved in the SME-networks, includingESR1,SMAD3,MYC,EGFR,BCL2andPAX5. Meanwhile, Ennet also identified many new networks with less characterization but have potentially important roles in cancer, including a large SME-network in medulloblastoma (MB), which contains genes enriched in the glutamate receptor and neural development pathways. Interestingly, SME-networks are specific across cancer types, and the vast majority of the genes identified by Ennet have few mutations in gene bodies. Collectively, our work suggests that using enhancer-only somatic mutations can be an effective way to discover potential cancer-driving networks. Ennet provides a new perspective to explore new mechanisms for tumor progression from SMEs.

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Somatic Mutations in miRNA Genes in Lung Cancer—Potential Functional Consequences of Non-Coding Sequence Variants

Cancers ◽

10.3390/cancers11060793 ◽

2019 ◽

Vol 11 (6) ◽

pp. 793 ◽

Cited By ~ 10

Author(s):

Paulina Galka-Marciniak ◽

Martyna Olga Urbanek-Trzeciak ◽

Paulina Maria Nawrocka ◽

Agata Dutkiewicz ◽

Maciej Giefing ◽

...

Keyword(s):

Somatic Mutations ◽

Mirna Gene ◽

Lung Squamous Cell Carcinoma ◽

The Cancer Genome Atlas ◽

Mirna Biogenesis ◽

Regulatory Sequence ◽

Regulatory Sequences ◽

Sequence Variants ◽

Mirna Genes ◽

Mutational Hotspots

A growing body of evidence indicates that miRNAs may either drive or suppress oncogenesis. However, little is known about somatic mutations in miRNA genes. To determine the frequency and potential consequences of miRNA gene mutations, we analyzed whole exome sequencing datasets of 569 lung adenocarcinoma (LUAD) and 597 lung squamous cell carcinoma (LUSC) samples generated in The Cancer Genome Atlas (TCGA) project. Altogether, we identified 1091 somatic sequence variants affecting 522 different miRNA genes and showed that half of all cancers had at least one such somatic variant/mutation. These sequence variants occurred in most crucial parts of miRNA precursors, including mature miRNA and seed sequences. Due to our findings, we hypothesize that seed mutations may affect miRNA:target interactions, drastically changing the pool of predicted targets. Mutations may also affect miRNA biogenesis by changing the structure of miRNA precursors, DROSHA and DICER cleavage sites, and regulatory sequence/structure motifs. We identified 10 significantly overmutated hotspot miRNA genes, including the miR-379 gene in LUAD enriched in mutations in the mature miRNA and regulatory sequences. The occurrence of mutations in the hotspot miRNA genes was also shown experimentally. We present a comprehensive analysis of somatic variants in miRNA genes and show that some of these genes are mutational hotspots, suggesting their potential role in cancer.

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