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Ref Type Journal Article
PMID (25485619)
Authors Klijn C, Durinck S, Stawiski EW, Haverty PM, Jiang Z, Liu H, Degenhardt J, Mayba O, Gnad F, Liu J, Pau G, Reeder J, Cao Y, Mukhyala K, Selvaraj SK, Yu M, Zynda GJ, Brauer MJ, Wu TD, Gentleman RC, Manning G, Yauch RL, Bourgon R, Stokoe D, Modrusan Z, Neve RM, de Sauvage FJ, Settleman J, Seshagiri S, Zhang Z
Title A comprehensive transcriptional portrait of human cancer cell lines.
Journal Vol Issue Date Pages Journal Short Title
Nature biotechnology 33 3 2015 Mar 306-12 Nat Biotechnol
URL
Abstract Text Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.

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Molecular Profile Treatment Approach
Gene Name Source Synonyms Protein Domains Gene Description Gene Role
Therapy Name Drugs Efficacy Evidence Clinical Trials
Drug Name Trade Name Synonyms Drug Classes Drug Description
Gene Variant Impact Protein Effect Variant Description Associated with drug Resistance
Molecular Profile Indication/Tumor Type Response Type Therapy Name Approval Status Evidence Type Efficacy Evidence References