Development and validation of a stromal immune phenotype classifier for predicting immune activity and prognosis in triple‐negative breast cancer

Abstract

Our study aims to construct a prognosis-related immune phenotype classifier for predicting clinical prognosis and immune activity in triple-negative breast cancer (TNBC). A total of 237 patients with TNBC from Sun Yat-sen University Cancer Center (SYSUCC) and 533 patients with TNBC from public datasets were included in our study. A stromal immune quantified index was generated with a LASSO Cox regression model based on five prognosis-related immune cells evaluated by CIBERSORT or IHC and was used to determine immune phenotypes. Immune features were evaluated in the samples before chemotherapy. A total of 119 patients in the SYSUCC training cohort were classified into immune Phenotypes A and B according to the density of stromal CD4+ T cells, γδ T cells, monocytes, M1 macrophages and M2 macrophages. Phenotype A predicted better survival than Phenotype B, and the classification was further validated in the testing cohort of 118 patients and the validation cohort of 533 patients. In the combined cohort, significant differences were found in Phenotype A compared to Phenotype B for the 5-year overall survival (83.5% vs 65.8%, respectively, P < .01) and the 5-year disease-free survival (87.3% vs 76.0%, respectively, P < .01). In Phenotype A, immune-related pathways were significantly enriched, and a higher level of immune checkpoint molecules, including PD-L1, PD-1 and CTLA-4, could be observed. The immune phenotype classification was an independent prognostic indicator for TNBC and might serve as a potential predictor for immune activity within the tumor microenvironment. K E Y W O R D Sclassifier, immune phenotype, prognosis, stromal immune score, triple-negative breast cancer

Efficacy and predictive factors of immune checkpoint inhibitors in metastatic breast cancer: a systematic review and meta-analysis

“…[47][48][49] The immune microenvironment can exert great influence on the progression of breast cancer, which results in the different clinical prognosis of patients. [50][51][52] We found that patients with TNBC and HER2 overexpression breast cancer had a better response to immune checkpoint therapy, which could be NCT, national clinical trial; OS, overall survival; PFS, progression-free survival; TNBC, triple negative breast cancer; HER2+, human epidermal growth factor receptor 2 overexpression.…”

Identification and Validation of Immune-Related Methylation Clusters for Predicting Immune Activity and Prognosis in Breast Cancer

“…Singlecell RNA sequencing of breast cancer has confirmed that there is a complex mixture of immune T cell subtypes in tumors (6,7). Besides, a large number of transcriptomics analyses have been used to explore the immune microenvironment of breast cancer, which indicated that patients with different expression of genes involving multiple immune cells had different survival rates (8)(9)(10)(11). Most of the previous research methods to decipher the characteristics of tumor immune microenvironment infiltration were based on the transcriptome (8,9).…”

“…Besides, a large number of transcriptomics analyses have been used to explore the immune microenvironment of breast cancer, which indicated that patients with different expression of genes involving multiple immune cells had different survival rates (8)(9)(10)(11). Most of the previous research methods to decipher the characteristics of tumor immune microenvironment infiltration were based on the transcriptome (8,9). DNA methylation, RNA and protein levels can be used as prognostic markers (12).…”

Bioinformatics Analysis of GFAP as a Potential Key Regulator in Different Immune Phenotypes of Prostate Cancer

“…Similarly, Li et al reported both immune-reduced and immune-enhanced subtypes with differing immune-related and clinical characteristics to provide targets for new treatments [23]. For breast cancer, Zheng et al developed an immune phenotype classifier for predicting both immune activity within the tumor microenvironment and prognoses for patients with triple-negative breast cancer [24]. In addition, numerous investigations have been conducted using immune subtypes to predict clinical prognoses and treatment guidance for bladder cancer [25], ovarian carcinoma [26], uveal melanoma [27], lung cancer [28,29], and head and neck cancers [30].…”