Background: Triple-negative breast cancer (TNBC) is considered a challenging tumor type since limited treatment options are available with minimum predicted capacity for response.Tumor-specific Major Histocompatibility Complex-II (tsMHC-II) expression is a proposed predictor of pathological complete response (PCR) to neoadjuvant chemotherapy in TNBC, with limited data in dose-dense regimens.The aim of this exploratory study is to investigate the association between tsMHC-II expression and PCR for better response prediction.Methods: Expression of tsMHC-II was assessed by immunohistochemistry on pretreatment biopsies using Monoclonal Mouse Anti-Human HLA-DR/DP/DQ/DX Antibody (Clone.CR3/43, 1:1000, sc-53302, Santa-Cruz) from 80 non-metastatic TNBC females receiving dose-dense (DD) doxorubicin/cyclophosphamide (AC) followed by either DD paclitaxel or weekly paclitaxel plus carboplatin, treated at Baheya Breast Cancer Foundation, Egypt.Tumors were classified as high (5%) or low (<5%) tsMHC-II expression.Following surgery, PCR was analyzed in addition to clinicopathological data.Results: Patient's baseline clinical characteristics including age, BMI, menopausal status, BC family history, tumor and nodal stages were comparable between MHC-IIhigh and low groups across both treatment arms.Most patients were premenopausal, with predominant T2-T3 tumors and N0-N1 nodal disease.Among 40 TNBC patients analyzed in DD AC paclitaxel-carboplatin arm, 72.5% expressed high MHC-II from which 72.4 % achieved PCR.Conversely, only 18.2% achieved PCR from those expressing low MHC-II (p=0.0034).From 40 TNBC patients analyzed in DD AC paclitaxel arm, 62.5% expressed high MHC-II from which 64% achieved PCR.However, only 13% achieved PCR from those expressing low MHC-II (p=0.0028).Conclusions: These data support MHC-II as a surrogate marker for tumor immune competence governing chemosensitivity, where carboplatin confers incremental benefit without altering this biological effect.This is especially relevant in resourcelimited settings, where robust predictive biomarkers are critical for treatment personalization.
Nogueira et al. (Fri,) studied this question.