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


Authors: Zañudo, J. G. T.; Mao, P.; Alcon, C.; Kowalski, K.; Johnson, G. N.; Xu, G.; Baselga, J.; Scaltriti, M.; Letai, A.; Montero, J.; Albert, R.; Wagle, N.
Article Title: Cell line-specific network models of ER(+) breast cancer identify potential PI3Kα inhibitor resistance mechanisms and drug combinations
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 PI3Ka inhibitor alpelisib in estrogen receptor positive (ER) PIK3CAmutant breast cancer. The model-predicted efficacious combination of alpelisib and BH3 mimetics, for example, 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 BCL2 family members were highly expressed. On the basis of 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. © 2021 American Association for Cancer Research Inc.. All rights reserved.
Keywords: controlled study; protein expression; treatment response; gene mutation; human cell; validation process; sensitivity analysis; protein bcl 2; prediction; cancer resistance; mathematical model; down regulation; everolimus; pik3ca gene; transcription factor fkhrl1; fulvestrant; bh3 protein; estrogen receptor positive breast cancer; phosphatidylinositol 4,5 bisphosphate 3 kinase; human; article; palbociclib; breast cancer cell line; alpelisib
Journal Title: Cancer Research
Volume: 81
Issue: 17
ISSN: 0008-5472
Publisher: American Association for Cancer Research  
Date Published: 2021-09-01
Start Page: 4603
End Page: 4617
Language: English
DOI: 10.1158/0008-5472.Can-21-1208
PUBMED: 34257082
PROVIDER: scopus
PMCID: PMC8744502
DOI/URL:
Notes: Article -- Export Date: 1 October 2021 -- Source: Scopus
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MSK Authors
  1. Jose T Baselga
    484 Baselga
  2. Maurizio Scaltriti
    169 Scaltriti
  3. Guotai Xu
    14 Xu