Model for predicting immunotherapy based on M2 macrophage infiltration in TNBC - Wu, Haoming; Feng, Jikun; Zhong, Wenjing; Zouxu, Xiazi; Xiong, Zhengchong; Huang, Weiling; Zhang, Chao; Wang, Xi; Yi, Jiarong (Frontiers in Immunology, 2023)
Compared to other types of breast cancer, triple-negative breast cancer (TNBC) does not effectively respond to targeted therapy and has a poor prognosis. There are currently a limited number of immunotherapeutic drugs available for TNBC, a field that requires additional development. Herein, co-expressing genes with M2 macrophages were analyzed based on the infiltration of M2 macrophages in TNBC and the sequencing data in The Cancer Genome Atlas (TCGA) database. Consequently, the influence of these genes on the prognoses of TNBC patients was analyzed. Our findings revealed that OLFML2B, MS4A7, SPARC, POSTN, THY1, and CD300C genes significantly influenced the prognosis of TNBC. Moreover, using lasso regression analysis, MS4A7, SPARC, and CD300C were finally determined for model construction. Subsequently, the accuracy of model was further verified using GEO database and patients information from the Cancer Center of Sun Yat-sen University. The TNBC patients were scored by the model, and patients were divided into high- and low-risk groups. On this basis, we analyzed the accuracy of prognosis prediction, correlation with immune checkpoint, and immunotherapy drug sensitivity in different groups. Compared to other types of breast cancer, TNBC does not effectively respond to targeted therapy and has a poor prognosis. In total, 50 immunotherapy drugs with therapeutic significance were screened. Ultimately, we assessed possible immunotherapeutics that have potential application and demonstrated the high precision of our prognostic model for predictive analysis. Our research not only broadened the scope of previous work on TNBC immunotherapy but also developed a reliable predictive model for the disease.