Supplementary Figure 3 from Pharmacological Profiling of Kinase Dependency in Cell Lines across Triple-Negative Breast Cancer Subtypes
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posted on 2023-04-03, 14:20 authored by Lauren S. Fink, Alexander Beatty, Karthik Devarajan, Suraj Peri, Jeffrey R. PetersonSupplementary Figure 3: Kinase inhibitors showing selective toxicity for Group 1 cell lines. Dot-plots showing response of Groups 1, 2, and 3 cell lines to additional kinase inhibitors with selective toxicity for Group 1. Black lines indicate mean EC50 for each group. Group 1 selectivity is shown for inhibitors with p < 0.05, and inhibitors are displayed by increasing p value.
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ARTICLE ABSTRACT
Triple-negative breast cancers (TNBC), negative for estrogen receptor, progesterone receptor, and ERBB2 amplification, are resistant to standard targeted therapies and exhibit a poor prognosis. Furthermore, they are highly heterogeneous with respect to genomic alterations, and common therapeutic targets are lacking though substantial evidence implicates dysregulated kinase signaling. Recently, six subtypes of TNBC were identified based on gene expression and were proposed to predict sensitivity to a variety of therapeutic agents including kinase inhibitors. To test this hypothesis, we screened a large collection of well-characterized, small molecule kinase inhibitors for growth inhibition in a panel of TNBC cell lines representing all six subtypes. Sensitivity to kinase inhibition correlated poorly with TNBC subtype. Instead, unsupervised clustering segregated TNBC cell lines according to clinically relevant features including dependence on epidermal growth factor signaling and mutation of the PTEN tumor suppressor. We further report the discovery of kinase inhibitors with selective toxicity to these groups. Overall, however, TNBC cell lines exhibited diverse sensitivity to kinase inhibition consistent with the lack of common driver mutations in this disease. Although our findings support specific kinase dependencies in subsets of TNBC, they are not associated with gene expression–based subtypes. Instead, we find that mutation status can be an effective predictor of sensitivity to inhibition of particular kinase pathways for subsets of TNBC. Mol Cancer Ther; 14(1); 298–306. ©2014 AACR.Usage metrics
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