Discussion
tumor, TCGA, tumors, breast cancer
TUMOR, BREAST CANCER, COLD, TUMORS, INFILTRATING, REGRESSION, HOT SPOTS, PATHOGENESIS, TUMORIGENESIS
SEs are a subclass of enhancers that frequently contain multiple enhancer-like elements, characterized by dense binding of master transcription factors (TFs) and Mediator complexes and high signals of active histone marks [Recently, the role of SEs in the pathogenesis and prediction of breast cancer has been the research hot spots [In this study, we identified a total of 5,073 DEGs from TCGA-BRCA and 153 SERGs from SEdb 2.0. Then, based on overlapping genes between the two algorithms mentioned above, a total of 55 SERGs were screened and established a 6-SERGs signature with prognostic value on the basis of univariate Cox regression analysis and LASSO regression algorithm. Meanwhile, we also validated the prediction efficiency of risk score system in several subgroups. According to the risk score system, breast cancer patients were divided into low-risk and high-risk groups. The effective and stable of the risk score system were validated in training set (including several subgroups) and testing set by KM curve. Then, the age, N stage and risk score were integrated into a nomogram model and calibration plots revealed the robust predictive ability of the prognostic nomogram for OS in the training set. Besides, time-dependent ROC analysis and DCA for model in training and testing sets revealed the well discriminatory ability of the nomogram. Therefore, our prognostic model based on SERGs can competently predict the clinical outcomes of breast cancer patients.The 6-SERGs prognostic model was comprised of POU3F2, NFE2, FOXJ1, KLF15, SPIB, and ZIC2. Previous studies have indicated that the 6 SERGs are involved in invasion, angiogenesis, and malignant phenotypes of breast cancer [In our study, the expression level of ZIC2 in the TCGA databases were negative correlated with OS of breast cancer patients. The mRNA and protein expression levels of breast cancer cell lines were determined, showing that ZIC2 may act as an independent prognostic factor in breast cancer. The in vitro experiments revealed that the down-regulation of ZIC2 gene expression inhibited the cell viability, cellular migration, and cell cycle of breast cancer cells, and ZIC2 might serve as a therapeutic target for breast cancer. In addition, further experimental studies should be conducted to unravel the mechanism by which ZIC2 mediates the malignant function of breast cancer cells, resulting in a poor prognosis for patients.Then, we performed GO and KEGG analyses based on DEGs between low-risk and high-risk groups to evaluate risk score system. The results displayed that DEGs were significantly enriched in terms of T cell activation, lymphocyte differentiation, receptor ligand activity, and cytokine-cytokine receptor interaction, which were closely related to the tumorigenesis and immune microenvironment [Patients in the two risk groups had different TIME. The results revealed that the risk score was negatively correlated with ESTIMATE score, which was composed of stromal score and immune score. In tumor infiltrating immune cells, the risk score was negatively correlated with tumor-infiltration lymphocytes (TILs) (including CD4 + T cells, NK, and CD8 + T cells), which played an important role in immunotherapy [This study was innovative to some extent: it took the SEs as the entry point, with the purpose of discovering potential new biomarker for predicting the prognosis of breast cancer, and a prognostic model on the basis of SERGs was constructed; in addition to validating the model through testing set, the biological function of ZIC2 was also preliminarily explored in vitro experiments. Meanwhile, this study also had three limitations: firstly, it will be better if the performance of the model itself can be further improved; secondly, only one representative risk gene (ZIC2) in the prognostic model was validated in true bench work; thirdly, some patients from TCGA-BRCA lacked of HER-2 status, which might be a cause to the bias.In summary, the 6-SERGs signature is capable of attributing to screen the population with various TIME and is promising to act as prognostic biomarker for breast cancer patients. Therefore, how to accurately identify patients in high-risk and achieve superior immuno-infiltration of “cold” tumors may be the topic of future research [