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Published on: September 19, 2018
Pharmacological profiling of kinase dependency in cell lines across triple-negative breast cancer subtypes
Lauren S Fink1, Alexander Beatty1, Karthik Devarajan2
1Cancer Biology Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania.
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.
Insights
Triple-negative breast cancer (TNBC) subtypes do not predict kinase inhibitor sensitivity. Instead, PTEN mutation status and epidermal growth factor signaling dependence identify TNBCs sensitive to specific kinase inhibitors, guiding targeted therapy development.
Area of Science:
- Oncology
- Molecular Biology
- Pharmacology
Background:
- Triple-negative breast cancer (TNBC) lacks targeted therapies due to heterogeneity and absence of common drivers.
- Kinase signaling is implicated in TNBC, but effective therapeutic targets remain elusive.
- Gene expression-based TNBC subtypes were proposed to predict sensitivity to kinase inhibitors.
Purpose of the Study:
- To evaluate the correlation between TNBC subtypes and sensitivity to kinase inhibitors.
- To identify alternative predictors of kinase inhibitor response in TNBC.
- To discover novel kinase inhibitors with selective toxicity for TNBC subsets.
Main Methods:
- Screening of a diverse panel of TNBC cell lines representing six subtypes against numerous small molecule kinase inhibitors.
- Unsupervised clustering of cell lines based on growth inhibition data.
- Correlation analysis between TNBC subtypes, gene expression, mutation status (e.g., PTEN), and response to kinase inhibition.
Main Results:
- TNBC subtype did not correlate with sensitivity to kinase inhibitors.
- Unsupervised clustering revealed TNBC cell lines segregated based on dependence on epidermal growth factor signaling and PTEN mutation status.
- Specific kinase inhibitors demonstrated selective toxicity against TNBC groups defined by these features.
- Diverse sensitivity to kinase inhibition was observed across TNBC cell lines, reflecting disease heterogeneity.
Conclusions:
- Gene expression-based TNBC subtypes are poor predictors of kinase inhibitor response.
- PTEN mutation status and signaling pathway dependence are more effective biomarkers for predicting sensitivity to specific kinase inhibitors in TNBC subsets.
- Targeted therapy development for TNBC should consider mutation status and signaling dependencies over gene expression subtypes.
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