Immunomodulatory gene networks predict treatment response and survival to de-escalated, anthracycline-free neoadjuvant chemotherapy in triple-negative breast cancer in the WSG-ADAPT-TN trial

Abstract

Anthracycline-containing neoadjuvant chemotherapy (NACT) is the standard treatment for early triple-negative breast cancer (eTNBC); however, it is associated with substantial toxicity. We performed whole transcriptome profiling of baseline tumor biopsies to identify gene networks predictive and prognostic for pathological complete response (pCR) and survival after de-escalated, anthracycline-free NACT in the WSG-ADAPT-TN trial (NCT01815242). eTNBC patients (cT1c-cT4c, cN +) were randomized to 12 weeks of nab-paclitaxel + gemcitabine (n = 182) or nab-paclitaxel + carboplatin (n = 154). The primary endpoint was pCR (ypT0/is, ypN0), and the secondary endpoints included survival and translational research. AmpliSeq RNA sequencing, allowing simultaneous analysis of the expression of > 20,000 genes, was performed in 135 patients. Differentially expressed genes were evaluated in training (n = 67) and validation (n = 68) sets, and a polygenic score (PS) for prediction of pCR (PS:pCR) and a PS for prediction of invasive disease-free survival (PS:iDFS) were found. 49/135 (36.3%) patients had pCR; 30 iDFS events occurred during 60-month median follow-up. Immune recruitment and viral defense gene networks were strongly associated with pCR, while metabolic pathways were associated with survival. PS:pCR and PS:iDFS predominantly included immune-related genes. Diagnostic accuracy (ROC AUC) in the validation cohort was 83% for PS:pCR and 64% for PS:iDFS. At optimized cut-off, PS:pCR identified a group with a 67.7% pCR rate (vs. 10.8%; p < .0001), and PS:iDFS detected a group with 79.5% (95%CI 64.1%, 88.8%) 5-year iDFS rate (vs. 55.0%, 95%CI 29.8%, 74.5%; p = .04). Polygenic scores incorporating immunoregulatory genes can predict pCR and survival and represent an opportunity to select patients for de-escalated, anthracycline-free NACT. This transcriptome network analysis also identifies potential new targets for personalized medicine approaches in patients without response to NACT. NCT01815242.