Effect of tumor microenvironment on chemotherapy response of patients with triple-negative breast cancer receiving neoadjuvant chemotherapy.

Abstract

590 Background: Triple-negative breast cancer (TNBC) is a breast cancer subtype that has poor prognosis and exhibits a unique tumor microenvironment, including the corresponding immunological environment. Analysis of the tumor microbiome has indicated a relationship between the tumor microenvironment and treatment response. Therefore, we attempted to reveal the role of the tumor microbiome in patients with TNBC that were receiving neoadjuvant chemotherapy. Methods: We collected TNBC patient RNA-seq samples from the Gene Expression Omnibus (GEO; n of pathological complete response [pCR] = 38, n of residual disease [RD] = 50) and extracted microbiome count data using Kraken2 and Bracken. Differential and relative abundance were estimated with linear discriminant analysis effect size (LEfSe). We calculated the immune cell fraction with CIBERSORTx and conducted survival analysis using the Cancer Genome Atlas patient data (n = 115). Correlations between the microbiome and immune cell compositions were analyzed and a prediction model was constructed to estimate drug response using random forest (RF) and support vector machine (SVM). Results: Among the drug response group, the beta diversity varied considerably; consequently, 20 genera and 24 species were observed to express a significant differential and relative abundance using LEfSe analysis. The drug response prediction model accuracy exhibited 76.47 and 88.24 percent in RF and SVM, respectively; specifically, Pandoraea pulmonicola and Brucella melitensis were found to be important features in determining drug response. In correlation analysis, Geosporobacter ferrireducens, Streptococcus sanguinis, and resting natural killer cells were the most correlated factors in the pCR group, whereas Nitrosospira briensis, Plantactinospora sp. BC1, and regulatory T cells (Tregs) were key features in the RD group. Further, M2 macrophages and Brucella showed significant differences in survival between the pCR and RD groups (p < 0.05). Conclusions: Our study demonstrated that the microbiome analysis of tumor tissue can predict chemotherapy response of patients with TNBC receiving neoadjuvant chemotherapy. Further, the immunological tumor microenvironment may be impacted by the tumor microbiome, thereby affecting the corresponding survival and treatment response.