Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics.

ABSTRACT: Precision oncology involves identifying drugs that will effectively treat a tumor and then prescribing an optimal clinical treatment regimen. However, most first-line chemotherapy drugs do not have biomarkers to guide their application. For molecularly targeted drugs, using the genomic status of a drug target as a therapeutic indicator has limitations. In this study, machine learning methods (e.g., deep learning) were used to identify informative features from genome-scale omics data and to train classifiers for predicting the effectiveness of drugs in cancer cell lines. The methodology introduced here can accurately predict the efficacy of drugs, regardless of whether they are molecularly targeted or nonspecific chemotherapy drugs. This approach, on a per-drug basis, can identify sensitiv

SUBMITTER: Ding MQ 

PROVIDER: S-EPMC5821274 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature