Abstract 15: Imputing a more targeted therapy for triple-negative breast cancers

Abstract

Abstract Triple-negative breast cancer (TNBC) is a clinically defined subset of breast cancers that are inherently difficult to treat since, unlike the other breast cancer subtypes, they are defined by their lack of a distinct molecular target. Previously our lab developed a computational framework to impute drug response in patients that accurately mirrored the observed patient response. In short, this methodology involves building unsupervised linear regression models between cell line baseline gene expression values and the respective drug sensitivity metric (EC50 or AUC), which allows us to generate imputed sensitivity scores for cell line or patient tumor samples for which we have gene expression data. For this study, we applied this methodology to prospectively identify agents that are predicted to be more effective specifically in triple-negative breast cancer. We began by expanding the drug imputation training dataset to the Broad’s Cell Therapeutics Response Portal, which contains 545 drugs and over 1,000 cancer cell lines (CCLs) and imputed sensitivity in The Cancer Genome Atlas’s (TCGA’s) breast cancer cohort. Our imputation data indicated that TNBC tumors were expected to be comparatively sensitive to cell cycle pathway inhibitors. Among these compounds, the Wee1 inhibitor MK1775 (aka adavosertib and AZD1775) was identified for having the most significant predicted effect in TNBC patients compared to the receptor-positive patients. We were able to validate the accuracy of the MK1775 imputation model using traditional cross-validation approaches as well as in independent cell line dataset and showed that the measured and our predicted response to Wee1 inhibition strongly correlated. Additionally, we were able to uses our predicted MK1775 response scores to recapitulate the significant association between MK1775 response and p53 mutation status. We then looked to validate the efficacy of MK1775’s efficacy in TNBC cell line and xenograft experiments. We observed strong inhibition of cancer growth by MK1775 alone but also identified a combination effect between MK1775 and the TNBC standard-of-care agent paclitaxel as assayed by both in vitro viability experiments as well as in vivo tumor growth assays. We believe these results indicate that this methodology could generally be applied as a hypothesis-generating tool for identifying targeted agents for other disease subtypes as well as supporting the use of MK1775, especially in combination with paclitaxel, for TNBC. Citation Format: Robert F. Gruener, Geoffrey L. Greene, R. Stephanie Huang. Imputing a more targeted therapy for triple-negative breast cancers [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 15.