ArticleBioinformatics (Oxford, England)2016
Computational discovery of pathway-level genetic vulnerabilities in non-small-cell lung cancer.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Susceptibility loci of CNOT6 in the general mRNA degradation pathway and lung cancer risk-A re-analysis of eight GWASs.Molecular carcinogenesis · 2017Pooled it
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- The proteasome regulator PSME4 modulates proteasome activity and antigen diversity to abrogate antitumor immunity in NSCLC.Nature cancer · 2023Article
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- Biology of the mRNA Splicing Machinery and Its Dysregulation in Cancer Providing Therapeutic Opportunities.International journal of molecular sciences · 2021Review
- Therapy-induced stress response is associated with downregulation of pre-mRNA splicing in cancer cells.Genome medicine · 2018Article
- Article
- Comparative Network Analysis of Patients with Non-Small Cell Lung Cancer and Smokers for Representing Potential Therapeutic Targets.Scientific reports · 2017Article
- A Role for Mitochondrial Translation in Promotion of Viability in K-Ras Mutant Cells.Cell reports · 2017Article
- Object Weighting: A New Clustering Approach to Deal with Outliers and Cluster Overlap in Computational Biology.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
motivationNovel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets.
resultsUnsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding. In particular, many NSCLC cell lines were especially sensitive to the loss of components of the LSm2-8 protein complex or the CCT/TRiC chaperonin. Different vulnerabilities were also found for different cell line subgroups. Furthermore, the predicted vulnerability of a single adenocarcinoma cell line to loss of the Wnt pathway was experimentally validated with screening of small-molecule Wnt inhibitors against an extensive cell line panel. AVAILABILITY AND IMPLEMENTATION: The clustering algorithm is implemented in Python and is freely available at https://bitbucket.org/youngjh/nsclc_paper CONTACT: marcotte@icmb.utexas.edu or jon.young@utexas.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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