Multi-Omics Alleviates the Limitations of Panel Sequencing for Cancer Drug Response Prediction

SIMPLE SUMMARY: Cancer is a complex, heterogeneous collection of diseases with hundred of different subtypes. Genomic aberrations that are primarily thought to be the root causes of different cancers have been clinically used as evidence for both the diagnosis and also matching individual patients to proper treatment options. However, the complexity of cancer manifests itself differently in each patient when inspected at the molecular level. Even patients with the same cancer type rarely have identical root causes for the same disease. Without an extensive molecular profile of a patient, it has been challenging to match the patients to the best treatment options. To remedy this, comprehensive genomic profiling panels have been developed to monitor hundreds of genes for a given patient, which has helped broaden the treatment options for patients. However, genomic aberrations detected in such panels still do not reflect the full complexity of how a tumour responds to cancer drugs. In this study, we demonstrate that using an additional layer of molecular information (called the transcriptome) on top of genomic aberrations that can be detected with cancer gene panels can provide significant improvements in predicting the cancer drug response in pre-clinical cancer models. Thus, this study serves as a push towards incorporating the transcriptome measurements more routinely in (pre-)clinical practice. ABSTRACT: Comprehensive genomic profiling using cancer gene panels has been shown to improve treatment options for a variety of cancer types. However, genomic aberrations detected via such gene panels do not necessarily serve as strong predictors of drug sensitivity. In this study, using pharmacogenomics datasets of cell lines, patient-derived xenografts, and ex vivo treated fresh tumor specimens, we demonstrate that utilizing the transcriptome on top of gene panel features substantially improves drug response prediction performance in cancer.