From cell lines to cancer patients: personalized drug synergy prediction.

ABSTRACT:

Motivation

Combination drug therapies are effective treatments for cancer. However, the genetic heterogeneity of the patients and exponentially large space of drug pairings pose significant challenges for finding the right combination for a specific patient. Current in silico prediction methods can be instrumental in reducing the vast number of candidate drug combinations. However, existing powerful methods are trained with cancer cell line gene expression data, which limits their applicability in clinical settings. While synergy measurements on cell line models are available at large scale, patient-derived samples are too few to train a complex model. On the other hand, patient-specific single-drug response data are relatively more available.

Results

In this work, we propos

SUBMITTER: Kuru HI 

PROVIDER: S-EPMC11215552 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature