[HTML][HTML] Functional proteomics can define prognosis and predict pathologic complete response in patients with breast cancer

AM Gonzalez-Angulo, BT Hennessy… - Clinical proteomics, 2011 - Springer
AM Gonzalez-Angulo, BT Hennessy, F Meric-Bernstam, A Sahin, W Liu, Z Ju, MS Carey
Clinical proteomics, 2011Springer
Purpose To determine whether functional proteomics improves breast cancer classification
and prognostication and can predict pathological complete response (pCR) in patients
receiving neoadjuvant taxane and anthracycline-taxane-based systemic therapy (NST).
Methods Reverse phase protein array (RPPA) using 146 antibodies to proteins relevant to
breast cancer was applied to three independent tumor sets. Supervised clustering to identify
subgroups and prognosis in surgical excision specimens from a training set (n= 712) was …
Purpose
To determine whether functional proteomics improves breast cancer classification and prognostication and can predict pathological complete response (pCR) in patients receiving neoadjuvant taxane and anthracycline-taxane-based systemic therapy (NST).
Methods
Reverse phase protein array (RPPA) using 146 antibodies to proteins relevant to breast cancer was applied to three independent tumor sets. Supervised clustering to identify subgroups and prognosis in surgical excision specimens from a training set (n = 712) was validated on a test set (n = 168) in two cohorts of patients with primary breast cancer. A score was constructed using ordinal logistic regression to quantify the probability of recurrence in the training set and tested in the test set. The score was then evaluated on 132 FNA biopsies of patients treated with NST to determine ability to predict pCR.
Results
Six breast cancer subgroups were identified by a 10-protein biomarker panel in the 712 tumor training set. They were associated with different recurrence-free survival (RFS) (log-rank p = 8.8 E-10). The structure and ability of the six subgroups to predict RFS was confirmed in the test set (log-rank p = 0.0013). A prognosis score constructed using the 10 proteins in the training set was associated with RFS in both training and test sets (p = 3.2E-13, for test set). There was a significant association between the prognostic score and likelihood of pCR to NST in the FNA set (p = 0.0021).
Conclusion
We developed a 10-protein biomarker panel that classifies breast cancer into prognostic groups that may have potential utility in the management of patients who receive anthracycline-taxane-based NST.
Springer