Year: 2008
Type: preprint
Abstract: ~ 0.9). Additionally, the model was able to predict a highly synergistic combination of Trametinib (MEK inhibitor) and Omipalisib (PI3K inhibitor) for TNBC treatment, which incidentally was recently in phase I clinical trials for TNBC. Our choice of tree-based models over networks for greater interpretability also allowed us to further interrogate which specific kinases were highly predictive of cell sensitivity in each cancer type, and we saw confirmatory strong predictive power in the inhibition of MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.
Source: PubMed
DOI: 10.21985/n2bb2t
Author: Shields, Ben
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
Awards: MICROFABRICATED INSTRUMENTATION TO MEASURE SPHINGOLIPID SIGNALING IN HUMAN ACUTE MYELOID LEUKEMIA, Predictive Modeling of the EGFR-MAPK pathway for Triple Negative Breast Cancer Patients, Illuminating Function of the Understudied Druggable Kinome, Integrating tumor and stroma to understand and predict treatment response
OpenAlex ID: W37577663