ArticleNature communications2013
Reconstructing targetable pathways in lung cancer by integrating diverse omics data.
Article in Nature communications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
45 citing papers in PubMed, 90 citations in OpenAlex.
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- Therapeutic Targeting of Regulated Signaling Pathways of Non-Small Cell Lung Carcinoma.ACS omega · 2023Review
- An Expectation-Maximization Algorithm for Combining a Sample of Partially Overlapping Covariance Matrices.Axioms · 2023Article
- Identifying individualized risk subpathways reveals pan-cancer molecular classification based on multi-omics data.Computational and structural biotechnology journal · 2022Article
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- Oncoprotein-specific molecular interaction maps (SigMaps) for cancer network analyses.Nature biotechnology · 2021Article
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- Developing a network view of type 2 diabetes risk pathways through integration of genetic, genomic and functional data.Genome medicine · 2019Article
- Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma.PeerJ · 2019Article
Corrections and comments
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Authors and funding
14 authors at 2 institutions in 1 country.
Funding
Abstract
Global 'multi-omics' profiling of cancer cells harbours the potential for characterizing the signalling networks associated with specific oncogenes. Here we profile the transcriptome, proteome and phosphoproteome in a panel of non-small cell lung cancer (NSCLC) cell lines in order to reconstruct targetable networks associated with KRAS dependency. We develop a two-step bioinformatics strategy addressing the challenge of integrating these disparate data sets. We first define an 'abundance-score' combining transcript, protein and phospho-protein abundances to nominate differentially abundant proteins and then use the Prize Collecting Steiner Tree algorithm to identify functional sub-networks. We identify three modules centred on KRAS and MET, LCK and PAK1 and β-Catenin. We validate activation of these proteins in KRAS-dependent (KRAS-Dep) cells and perform functional studies defining LCK as a critical gene for cell proliferation in KRAS-Dep but not KRAS-independent NSCLCs. These results suggest that LCK is a potential druggable target protein in KRAS-Dep lung cancers.
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Registered trials
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.