Reverse-Phase Protein Array for Prediction of Patients at Low Risk of Developing Bone Metastasis From Breast Cancer

Abstract

©AlphaMed Press 2014. Patients and Methods. Tumor samples were obtained from 169 patients with primary invasive breast carcinoma who underwent surgery.The patients were categorized by whether they developed breast cancer bone metastasis (BCBM) during follow-up. Clinical characteristics and protein expression by RPPA were compared and verified by leave-one-out cross-validation. Results. Lymph node status (p = .023) and expression level of 22proteins by RPPA were significantly correlated with BCBM in logistic regression analysis.These variables were used to build a logistic regression model.After filtering the variables through a stepwise algorithm, the final model, consisting of 8 proteins and lymph node status, had sensitivity of 30.0%, specificity of 90.5%, positive predictive value of 30.0%, and negative predictive value of 90.5% in the cross-validation. Most of the identified proteins were associated with cell cycle or signal transduction (CDK2, CDKN1A, Rb1, Src, phosphorylated-ribosomal S6 kinase, HER2, BCL11A, and MYH11). Conclusion. Our validated model, in which the primary tumor is tested with RPPA, can predict patients who are at low risk of developing BCBM and thus who likely would not benefit from receiving a bisphosphonate in the adjuvant setting. Clinical trials excluding these patients have the potential to clarify the benefit of bisphosphonates in the adjuvant setting. Background. A biomarker that predicts bone metastasis based on a protein laboratory assay has not been demonstrated. Reverse-phase protein array (RPPA) enables quantification of total and phosphorylated proteins, providing information about their functional status. The aim of this study was to identify bone-metastasis-related markers in patients with primary breast cancer using RPPA analysis.