A method of gene expression data transfer from cell lines to cancer patients for machine-learning prediction of drug efficiency.

ABSTRACT: Personalized medicine implies that distinct treatment methods are prescribed to individual patients according several features that may be obtained from, e.g., gene expression profile. The majority of machine learning methods suffer from the deficiency of preceding cases, i.e. the gene expression data on patients combined with the confirmed outcome of known treatment methods. At the same time, there exist thousands of various cell lines that were treated with hundreds of anti-cancer drugs in order to check the ability of these drugs to stop the cell proliferation, and all these cell line cultures were profiled in terms of their gene expression. Here we present a new approach in machine learning, which can predict clinical efficiency of anti-cancer drugs for individual patients by transferr

SUBMITTER: Borisov N 

PROVIDER: S-EPMC5927638 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature