The purpose of this study was to determine the functional proteomic characteristics of residual breast cancer and hormone receptor (HR)-positive breast cancer after neoadjuvant systemic chemotherapy, and their relationship with patient outcomes.Methods
Reverse phase protein arrays of 76 proteins were carried out. A boosting approach in conjunction with a Cox proportional hazard model defined relapse predictors. A risk score (RS) was calculated with the sum of the coefficients from the final model. Survival outcomes and associations of the RS with relapse were estimated. An independent test set was used to validate the results.Results
Test (n = 99) and validation sets (n = 79) were comparable. CoxBoost revealed a three-biomarker (CHK1pS345, Caveolin1, and RAB25) and a two-biomarker (CD31 and Cyclin E1) model that correlated with recurrence-free survival (RFS) in all residual breast cancers and in HR-positive disease, respectively. Unsupervised clustering split patients into high- and low risk of relapse groups with different 3-year RFS (P ≤ 0.001 both). RS was a substantial predictor of RFS (P = 0.0008 and 0.0083) after adjustment for other substantial characteristics. Similar results were found in validation sets.Conclusions
We found models that independently predicted RFS in all residual breast cancer and in residual HR-positive disease that may represent potential targets of therapy in this resistant disease.