Expression of carcinoma ecotypes in the tumor microenvironment predicts response to neoadjuvant therapy in...

Immunotherapy is associated with modest pathologic complete response (pCR) rates in early-stage breast cancer, and a subset of patients still achieves a pCR after neoadjuvant chemotherapy (NAC) only. Identifying biomarkers in the complex tumor ecosystem which define the subsets of patients who achieve pCR benefit on immunotherapy versus not is of a critical need. Transcriptomic data for patients enrolled in the two neoadjuvant immunotherapy arms of 'pembrolizumab' (n = 69) and 'durvalumab' (n = 71), and the chemotherapy arm 'control' (n = 210) of the I-SPY2 breast cancer clinical trial were included. Using a machine learning algorithm for tumor ecosystem-based classification, we deconvoluted transcriptomic data into the established 10 multicellular organization systems known as 'Ecotypes'. We found that the most pro-inflammatory carcinoma ecotype (CE)9 predicts pCR in the 'pembrolizumab' arm (OR = 2.07; 95% CI 1.35-3.8; adjusted P value = 0.01), in the 'control' arm (OR = 1.89; 95% CI 1.36-2.63; adjusted P value = 0.002), and in the 'durvalumab' arm (OR = 1.66; 95%CI 1.18-2.34; adjusted P value = 0.03). In contrast, the basal-enriched ecotype CE2 was the most significant predictor of pCR in the 'durvalumab' arm, which included the addition of olaparib (OR = 3.22; 95%CI 2.25-4.60; adjusted P value < 0.0001), but not in NAC (OR = 1.18; 95%CI 0.81-1.72; adjusted P value = 0.94). Our findings suggest that CE9 could identify early-stage breast cancer patients who achieve a pCR after neoadjuvant therapy and may have a good prognosis. Whether CE9 patients could still be considered for immunotherapy or be candidates for de-escalation strategies in the neoadjuvant setting requires further investigation in future studies with link to survival outcomes. In contrast, CE2 tumors would benefit from the combination of immunotherapy with olaparib. Integrating tumor ecosystem-based patient classification could guide effective clinical management in early-stage breast cancer.