ENDORSE: a prognostic model for endocrine therapy in estrogen‐receptor‐positive breast cancers

Abstract

Abstract Advanced and metastatic estrogen receptor‐positive (ER+) breast cancers are often endocrine resistant. However, endocrine therapy remains the primary treatment for all advanced ER+ breast cancers. Treatment options that may benefit resistant cancers, such as add‐on drugs that target resistance pathways or switching to chemotherapy, are only available after progression on endocrine therapy. Here we developed an endocrine therapy prognostic model for early and advanced ER+ breast cancers. The endocrine resistance (ENDORSE) model is composed of two components, each based on the empirical cumulative distribution function of ranked expression of gene signatures. These signatures include a feature set associated with long‐term survival outcomes on endocrine therapy selected using lasso‐regularized Cox regression and a pathway‐based curated set of genes expressed in response to estrogen. We extensively validated ENDORSE in multiple ER+ clinical trial datasets and demonstrated superior and consistent performance of the model over clinical covariates, proliferation markers, and multiple published signatures. Finally, genomic and pathway analyses in patient data revealed possible mechanisms that may help develop rational stratification strategies for endocrine‐resistant ER+ breast cancer patients.

Keywords

• biomarker
• cox proportional hazards model
• endocrine resistance
• lasso
• survival analysis