ArticleBioinformatics (Oxford, England)2017
WeSME: uncovering mutual exclusivity of cancer drivers and beyond.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed, 94 citations in OpenAlex.
- Variant-Specific Landscape of Mutual Exclusivity Among BRAF, EGFR, and KRAS Oncogenes Reveals Overlap With Functionally Antagonistic Mutant Pairs.International journal of cancer · 2026Article
- Evolving patterns of co-mutations from tumor initiation to metastatic progression.Nature genetics · 2026Article
- Succinylation related gene signature enables risk stratification and prognostic modeling in breast cancer patients.Amino acids · 2026Article
- A pathway-informed mutual exclusivity framework to detect genetic interactions in pediatric cancer.BMC medical genomics · 2025Article
- Candidate genes related to spiritual mediumship: a whole-exome sequencing analysis of highly gifted mediums.Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999) · 2025Article
- A latent variable model for evaluating mutual exclusivity and co-occurrence between driver mutations in cancer.bioRxiv : the preprint server for biology · 2024Article
- Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers.PLoS computational biology · 2024Article
- Exploration of molecular markers related to chemotherapy efficacy of hepatoid adenocarcinoma of the stomach.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- Proteomic analysis of breast cancer based on immune subtypes.Clinical proteomics · 2024Article
- Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways.American journal of human genetics · 2024Article
- SL-Miner: a web server for mining evidence and prioritization of cancer-specific synthetic lethality.Bioinformatics (Oxford, England) · 2024Article
- Modeling and predicting cancer clonal evolution with reinforcement learning.Genome research · 2023Article
- Integrative genomic profiling reveals characteristics of lymph node metastasis in small cell lung cancer.Translational lung cancer research · 2023Article
- The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients.European journal of medical research · 2023Article
- A network-based method for identifying cancer driver genes based on node control centrality.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- Using graph-based model to identify cell specific synthetic lethal effects.Computational and structural biotechnology journal · 2023Article
- Mutations in theInternational journal of general medicine · 2022Article
- Whole-genome characterization of large-cell lung carcinoma: A comparative analysis based on the histological classification.Frontiers in genetics · 2022Article
- Positive regulators of T cell proliferation as biomarkers for predicting prognosis and characterizing the immune landscape in lung adenocarcinoma.Frontiers in genetics · 2022Article
- A Novel Immune-Prognosis Index Predicts the Benefit of Lung Adenocarcinoma Patients.Frontiers in pharmacology · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Motivation: Mutual exclusivity is a widely recognized property of many cancer drivers. Knowledge about these relationships can provide important insights into cancer drivers, cancer-driving pathways and cancer subtypes. It can also be used to predict new functional interactions between cancer driving genes and uncover novel cancer drivers. Currently, most of mutual exclusivity analyses are preformed focusing on a limited set of genes in part due to the computational cost required to rigorously compute P -values. Results: To reduce the computing cost and perform less restricted mutual exclusivity analysis, we developed an efficient method to estimate P -values while controlling the mutation rates of individual patients and genes similar to the permutation test. A comprehensive mutual exclusivity analysis allowed us to uncover mutually exclusive pairs, some of which may have relatively low mutation rates. These pairs often included likely cancer drivers that have been missed in previous analyses. More importantly, our results demonstrated that mutual exclusivity can also provide information that goes beyond the interactions between cancer drivers and can, for example, elucidate different mutagenic processes in different cancer groups. In particular, including frequently mutated, long genes such as TTN in our analysis allowed us to observe interesting patterns of APOBEC activity in breast cancer and identify a set of related driver genes that are highly predictive of patient survival. In addition, we utilized our mutual exclusivity analysis in support of a previously proposed model where APOBEC activity is the underlying process that causes TP53 mutations in a subset of breast cancer cases. Availability and Implementation: http://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/index.cgi#wesme. Contact: przytyck@ncbi.nlm.nih.gov. Supplementary information: Supplementary data are available at Bioinformatics online.
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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.