Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers

Adopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes (SCLC-A, SCLC-N, and S...

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Veröffentlicht in:	PLoS computational biology 2019-10, Vol.15 (10), p.e1007343
Hauptverfasser:	Wooten, David J, Groves, Sarah M, Tyson, Darren R, Liu, Qi, Lim, Jing S, Albert, Réka, Lopez, Carlos F, Sage, Julien, Quaranta, Vito
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Animals ASCL1 protein Basic Helix-Loop-Helix Transcription Factors - metabolism Bayes Theorem Biochemistry Biology Biology and Life Sciences Boolean algebra Breast cancer Cancer therapies Cell Line, Tumor Cluster Analysis Databases, Genetic Departments DNA binding proteins Drug Resistance, Neoplasm Funding Gene Expression Gene Expression Regulation, Neoplastic - genetics Gene Ontology Gene Regulatory Networks - genetics Genes Health aspects Heterogeneity Humans Lung cancer Medical research Medicine and Health Sciences Mice Models, Theoretical Pediatrics Regulators Research and Analysis Methods Small cell lung cancer Small cell lung carcinoma Small Cell Lung Carcinoma - classification Small Cell Lung Carcinoma - metabolism Software Systems Analysis Transcription factors Transcription Factors - metabolism Tumors Workflow Workflow software
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