ArticleNature communications2015
Systematic analysis of somatic mutations impacting gene expression in 12 tumour types.
Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
64 citing papers in PubMed, 119 citations in OpenAlex.
- Comprehensive genomic profiling of mucosal melanoma reveals novel fusion transcripts and dysregulation of cell-cycle, MAPK, and PI3K pathways.The Journal of pathology · 2026Article
- A Novel Cancer Driver Genes Identification Method Based on Self-Supervised Dual Masked Graph Autoencoder.Interdisciplinary sciences, computational life sciences · 2026Article
- Integrating Multi-Source Directed Gene Networks and Multi-Omics Data to Identify Cancer Driver Genes Based on Graph Neural Networks.International journal of molecular sciences · 2025Article
- MLGCN-Driver: a cancer driver gene identification method based on multi-layer graph convolutional neural network.BMC bioinformatics · 2025Article
- Gene expression in tumor and adjacent normal tissues in lung adenocarcinoma subtypes.BMC cancer · 2025Article
- Mutation impact on mRNA versus protein expression across human cancers.GigaScience · 2025Article
- Inferring Phenotypes of Copy Number Clones in Cancer Populations Using TreeAlign.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Integrative Computational Framework,bioRxiv : the preprint server for biology · 2024Article
- Low-level brain somatic mutations in exonic regions are collectively implicated in autism with germline mutations in autism risk genes.Experimental & molecular medicine · 2024Article
- Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers.Genome biology · 2024Article
- Allele-specific transcriptional effects of subclonal copy number alterations enable genotype-phenotype mapping in cancer cells.Nature communications · 2024Article
- The effects of mutations on gene expression and alternative splicing.Proceedings. Biological sciences · 2023Article
- The origins and functional effects of postzygotic mutations throughout the human life span.Science (New York, N.Y.) · 2023Article
- Exploiting allele-specific transcriptional effects of subclonal copy number alterations for genotype-phenotype mapping in cancer cell populations.bioRxiv : the preprint server for biology · 2023Article
- Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism.BMC bioinformatics · 2023Article
- Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers.Nucleic acids research · 2022Article
- SYSMut: decoding the functional significance of rare somatic mutations in cancer.Briefings in bioinformatics · 2022Article
- Widespread redundancy in -omics profiles of cancer mutation states.Genome biology · 2022Article
- Introduction and expression of PIK3CAJournal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale · 2022Article
- A computational approach for the discovery of significant cancer genes by weighted mutation and asymmetric spreading strength in networks.Scientific reports · 2021Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a novel hierarchical Bayes statistical model, xseq, to systematically quantify the impact of somatic mutations on expression profiles. We establish the theoretical framework and robust inference characteristics of the method using computational benchmarking. We then use xseq to analyse thousands of tumour data sets available through The Cancer Genome Atlas, to systematically quantify somatic mutations impacting expression profiles. We identify 30 novel cis-effect tumour suppressor gene candidates, enriched in loss-of-function mutations and biallelic inactivation. Analysis of trans-effects of mutations and copy number alterations with xseq identifies mutations in 150 genes impacting expression networks, with 89 novel predictions. We reveal two important novel characteristics of mutation impact on expression: (1) patients harbouring known driver mutations exhibit different downstream gene expression consequences; (2) expression patterns for some mutations are stable across tumour types. These results have critical implications for identification and interpretation of mutations with consequent impact on transcription in cancer.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.