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Manway Liu

Researcher at Novartis

Publications -  16
Citations -  10523

Manway Liu is an academic researcher from Novartis. The author has contributed to research in topics: Cancer & Breast cancer. The author has an hindex of 12, co-authored 16 publications receiving 8137 citations.

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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

TL;DR: The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.
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Next-generation characterization of the Cancer Cell Line Encyclopedia

Mahmoud Ghandi, +79 more
- 08 May 2019 - 
TL;DR: The original Cancer Cell Line Encyclopedia is expanded with deeper characterization of over 1,000 cell lines, including genomic, transcriptomic, and proteomic data, and integration with drug-sensitivity and gene-dependency data, which reveals potential targets for cancer drugs and associated biomarkers.
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Erratum: Addendum: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity (Nature (2012) 483 7391 (603-607))

TL;DR: Jordi Barretina, Giordano Caponigro, Nicolas Stransky, Kavitha Venkatesan, Adam A. Golub, Michael P. Morais, Jodi Meltzer, Judit Jané-Valbuena, Felipa A. Mapa, Joseph Thibault, Eva Bric-Furlong, Pichai Raman, Aaron Shipway, Ingo H. Engels, Jill Cheng, Guoying K. Yu
Journal ArticleDOI

Characterization of the Novel and Specific PI3Kα Inhibitor NVP-BYL719 and Development of the Patient Stratification Strategy for Clinical Trials

TL;DR: The biologic properties of the 2-aminothiazole derivative NVP-BYL719, a selective inhibitor of PI3Kα and its most common oncogenic mutant forms, are reported and it is found that PIK3CA mutation was the foremost positive predictor of sensitivity while revealing additional positive and negative associations such as Pik3CA amplification and PTEN mutation, respectively.