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Cancer Res DOI:10.1158/0008-5472.CAN-21-1208

Cell line-specific network models of ER+ breast cancer identify potential PI3Kα inhibitor resistance mechanisms and drug combinations.

Publication TypeJournal Article
Year of Publication2021
AuthorsZañudo, JGómez Tej, Mao, P, Alcon, C, Kowalski, K, Johnson, GN, Xu, G, Baselga, J, Scaltriti, M, Letai, A, Montero, J, Albert, R, Wagle, N
JournalCancer Res
Date Published2021 Jul 13
ISSN1538-7445
Abstract

Durable control of invasive solid tumors necessitates identifying therapeutic resistance mechanisms and effective drug combinations. In this work, we used a network-based mathematical model to identify sensitivity regulators and drug combinations for the PI3Kα inhibitor alpelisib in ER+ PIK3CA mutant breast cancer. The model-predicted efficacious combination of alpelisib and BH3 mimetics, e.g., MCL1 inhibitors, was experimentally validated in ER+ breast cancer cell lines. Consistent with the model, FOXO3 downregulation reduced sensitivity to alpelisib, revealing a novel potential resistance mechanism. Cell line-specific sensitivity to combinations of alpelisib and BH3 mimetics depended on which BCL-2 family members were highly expressed. Based on these results, newly developed cell line-specific network models were able to recapitulate the observed differential response to alpelisib and BH3 mimetics. This approach illustrates how network-based mathematical models can contribute to overcoming the challenge of cancer drug resistance.

DOI10.1158/0008-5472.CAN-21-1208
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/34257082?dopt=Abstract

Alternate JournalCancer Res
PubMed ID34257082