AUTHOR=Yang Yan , He Xin , Tang Qian-Qian , Shao You-Cheng , Song Wen-Jing , Gong Peng-Ju , Zeng Yi-Fan , Huang Si-Rui , Zhou Jiang-Yao , Wan Hui-Fang , Wei Lei , Zhang Jing-Wei TITLE=GMFG Has Potential to Be a Novel Prognostic Marker and Related to Immune Infiltrates in Breast Cancer JOURNAL=Frontiers in Oncology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.629633 DOI=10.3389/fonc.2021.629633 ISSN=2234-943X ABSTRACT=

A growing amount of evidence has indicated immune genes perform a crucial position in the development and progression of breast cancer microenvironment. The purpose of our study was to identify immunogenic prognostic marker and explore potential regulatory mechanisms for breast cancer. We identified the genes related to ImmuneScore using ESTIMATE algorithm and WGCNA analysis, and we identified the differentially expressed gene (DEGs). Then, Glia maturation factor γ (GMFG) was determined as a predictive factor by intersecting immune-related genes with DEGs and survival analysis. We found the expression of GMFG was lower in breast cancer tissues compared with normal breast tissues, which was further verified by immunohistochemical (IHC). Moreover, the decreased expression of GMFG was significantly related to the poor prognosis. Besides, the expression of GMFG was related to the age, ER status, PR status, HER2 status and tumor size, which further suggested that the expression of GMFG was correlated with the subtype and the growth of tumor. The univariate and multivariate Cox regression analyses revealed that age, stage, the expression level of GMFG and radiotherapy were independent factors for predicting the prognosis of breast cancer patients. Subsequently, a prognostic model to predict the 3-year, 5-year and 10-year overall survival rate was developed based on the above four variables, and visualized as a nomogram. The values of area under the curve of the nomogram at 3-year, 5-year and 10-year were 0.897, 0.873 and 0.922, respectively, which was higher than stage in prognostic accuracy. In addition, we also found that GMFG expression level was correlated with sensitivity of some breast cancer chemotherapy drugs. Furthermore, the results of GSEA indicated immune-related pathways were mainly enriched in GMFG-high-expression group. CIBERSORT analysis for the proportion of tumor-infiltrating immune cells (TIICs) suggested that expression of GMFG was positively association with multiple kinds T-cell in BC. Among them, CD8+ T cells had the strongest correlation with GMFG expression, which revealed that GMFG might has an antitumor effect by increasing the infiltration of CD8+ T cells in breast cancer. Accordingly, GMFG has the potential to become a novel immune biomarker for the diagnosis and treatment of breast cancer.