Genomic characteristics of breast cancer to predict response of neoadjuvant chemotherapy and long-term prognosis.

Abstract

557 Background: To precisely predict neoadjuvant chemotherapy (NAC) response and long-term prognosis, we developed prediction model with clinical and genomic characteristics of breast cancer (BC). Methods: We included early and locally advanced BC that would be scheduled to receive standard NAC (four cycles of anthracycline and cyclophosphamide and four cycles of docetaxel or docetaxel plus trastuzumab for HER2+ BC) followed by curative surgery. For each patient, tumor tissue and matched blood were prospectively collected three times: at diagnosis (T1), three weeks after the first cycle of chemotherapy (T2), and curative surgery (T3). Whole exome sequencing (WES) was performed to detect somatic mutation, mutational signature and tumor mutational burden (TMB) while RNASeq with PAM50 prediction was to classify intrinsic subtype. In terms of clinical variables, clinical stage and IHC subtype at diagnosis, residual cancer burden (RCB) class and distant recurrence free survival (DRFS) were used. Logistic regression was used for predicting RCB class with clinical and genomic variables at T1. Univariate and multivariate Cox regression were performed to identify prognostic factors for DRFS. Results: In total, 210 patients were enrolled and treated with NAC as scheduled. We successfully conducted WES in 231 BC tissues (T1:117, T2:101 and T3:13) from 117 patients. In NAC response, 13 patients were in RCB class 3, 39 in class 2, 14 in class 1 and 46 in class 0. Median follow up duration was 44months and distant recurrence was observed in 13 patients. TP53 mutation (68%) was the most commonly detected genetic alteration. ARID1A, CDH1, CSMD3, LRP1B, PIK3CA, RUNX1 and TP53 were significantly mutated genes in driver gene analysis. Median TMB was 87 (range, 14-570) and signature 3 was most frequently observed. Among genetic characteristics, high TMB was significantly associated with better NAC response compared with low TMB (hazard ratio[HR] for RCB class III: 0.11, 95% confident interval[CI]: 0.01, 0.74, p = 0.05). In prediction model, combination of seven variables: intrinsic subtype, TMB, LRRK1, OPLAH, and PIK3CA hotspot mutation, ERBB2 amplification, and clinical stage had 0.83 in area under curve (AUC) and 0.75 in accuracy. High clinical stage, PTEN and PIK3CA hotspot mutation negatively affected to DRFS while high TMB had protective effect (all ps < 0.05). Prediction model made with five variables: intrinsic subtype, TMB, PTEN mutation, PIK3CA hotspot mutation and clinical stage had 0.88 in c-index (95% CI: 0.81, 0.95). Conclusions: TMB, PIK3CA hotspot mutation and clinical stage showed predictive roles on NAC response and distant recurrence of BC in NAC setting. In prediction model, intrinsic subtype, TMB, LRRK1, OPLAH, and PIK3CA hotspot mutation, ERBB2 amplification, and clinical stage affected to RCB class while intrinsic subtype, TMB, PTEN, PIK3CA hotspot mutation and clinical stage did to DRFS. Clinical trial information: NCT02591966.