MTClin: Integrating MammaTyper® to predict neoadjuvant therapy response in HER2+ breast cancer

Aim: Neoadjuvant therapy (NAT) is the standard of care for most HER2-positive early breast cancer (BC). However, 25 to 50% of patients fail to achieve a pathological complete response (pCR). This study evaluates the CE/IVD MammaTyper (R) kit (Cerca Biotech) as a predictor of response in this setting. Methods: A total of 161 HER2-positive (IHC score 3+) invasive BC patients treated with trastuzumab-based NAT were enrolled. After excluding seven cases (insufficient RNA amount or dual anti-HER2 blockade), 154 FFPE preoperatory core-biopsies were tested: 79 hormone-positive (HR+) and 75 hormone-negative (HR-). Ninety-one achieved a pCR, 63 attained a pathological partial response (pPR). MammaTyper (R), an in vitro diagnostic RTqPCR test, assessed ERBB2, ESR1, PGR, MKI67 mRNA levels. A Python-based Decision Tree Algorithm was used to predict pCR using Delta Delta Cq values of the four genes alongside tumor size and nodal status (MTClin). The model was further applied to a cT1N0 subgroup and to predict the recurrence risk at 3 and 5 years. Hyper-parameters were tuned using GridSearchCV with a 5-fold cross-validation. Performance metrics included sensitivity, specificity, PPV and NPV. Results: Two decision trees were selected for optimal accuracy. In HR+ tumors, the model yielded 90.2 % sensitivity, 86.8 % specificity, 88.1 % PPV and 89.2 % NPV. In HR-tumors, sensitivity was 96 %, specificity 88 %, PPV 94.1 %, and NPV 91.7 %. Sensitivity and NPV were highest in the cT1N0 HR-subgroup. Recurrence prediction yielded AUCs of 0.98 (3 years) and 0.96 (5 years). Conclusions: MTClin may predict pCR and recurrence in HER2-positive BC, supporting tailored escalation or deescalation treatment.