Prediction of Recurrence and Survival for Triple-Negative Breast Cancer (TNBC) by a Protein Signature in Tissue Samples

Abstract

To date, there is no available targeted therapy for patients who are diagnosed with triple-negative breast cancers (TNBC). The aim of this study was to identify a new specific target for specific treatments. Frozen primary tumors were collected from 83 adjuvant therapy-naive TNBC patients. These samples were used for global proteome profiling by iTRAQ-OFFGEL-LC-MS/MS approach in two series: a training cohort (n = 42) and a test set (n = 41). Patients who remains free of local or distant metastasis for a minimum of 5 years after surgery were classified in the no-relapse group; the others were in the relapse group. OPLS and Kaplan-Meier analyses were performed to select candidate markers, which were validated by immunohistochemistry. Three proteins were identified in the training set and validated in the test set by Kaplan-Meier method and immunohistochemistry (IHC): TrpRS as a good prognostic markers and DP and TSP1 as bad prognostic markers. We propose the establishment of an IHC test to calculate the score of TrpRS, DP, and TSP1 in TNBC tumors to evaluate the degree of aggressiveness of the tumors. Finally, we propose that DP and TSP1 could provide therapeutic targets for specific treatments.

Fig. 1.

Flow chart of experimental design for the development and validation of the biomarkers.

Fig. 2.

Supervised orthogonal partial least squares discrimination analysis (OPLS-DA) to distinguish between no-relapse and relapse groups. OPLS-DA analysis was performed on 549 proteins for which quantitative value was available in all the tumors. The optimized OPLS model included 59 proteins. Among these proteins, 33 were assigned to the group without recurrence and 26 to the group with recurrence. Error bars indicate the confidence intervals of the coefficients.

Fig. 3.

Kaplan–Meier survival estimates. Kaplan–Meier analysis shows that high TrpRS and low DP-TSP1 are strongly predictive of overall survival.

Fig. 4.

Validation of TrpRS as good pronostic biomarker and TSP1 and DP as bad prognostic biomarkers. Different distribution of IHC scores (staining intensity X staining percentage) between relapse and no-relapse groups for TrpRS (A), DP (B), TSP1 (C), and combined DP-TSP1 (D) (mean ± S.D. are shown).

Fig. 5.

Receiver operating characteristics curves of the 3 protein signature in the training set (A) and in the test set (B).