DataSheet_1_ATP2C2 Has Potential to Define Tumor Microenvironment in Breast Cancer.pdf

Tumor microenvironment (TME) is vital for the occurrence and development of breast cancer (BRCA). However, it remains challenging to understand the dynamic modulation of the stromal and immune components comprehensively in TME. Herein, we used ESTIMATE and CIBERSORT algorithm to estimate the number of stromal and immune components and the abundance of tumor-infiltrating immune cells (TICs) in 582 BRCA cases from gene expression omnibus (GEO) database. We employed three regression models including univariable Cox proportion, LASSO regression model and multivariate Cox regression, and identified 7 immune-specific genes related to BRCA survival. Of 7 genes, ATPase Secretory Pathway Ca2+ Transporting 2 (ATP2C2) attracts our attention for significantly predicting prognosis of BRCA patients. Further analysis indicated that ATP2C2 expression was closely related to the clinicopathological features (age, T- and N-staging) and negatively correlated with patients’ survival in BRCA. Gene Set Enrichment Analysis (GSEA) was performed to reveal pathway enrichment between ATP2C2high and ATP2C2low groups. The low ATP2C2 expression groups’ genes were mainly enriched for immune-related activities, while those in the ATP2C2 high-expression group were largely enriched in metabolic-related pathways. Notably, Pearson’s correlation analysis identified that ATP2C2 expression was positively correlated with T follicular helper (Tfh) cells, and negatively correlated with gamma delta (γδ) T cell, suggesting that ATP2C2 might be accountable for the maintenance of immune-dominant status for TME. To sum up, this study comprehensively analyzed the TME and shed light on prognostic immune-related biomarkers for BRCA. In particular, ATP2C2 might be helpful for predicting the prognosis of BRCA patients, which provided an extra insight for BRCA treatment.

肿瘤微环境（Tumor microenvironment, TME）对于乳腺癌（Breast cancer, BRCA）的发生与发展至关重要。然而，全面解析肿瘤微环境中基质与免疫组分的动态调控机制仍颇具挑战。本研究借助ESTIMATE与CIBERSORT算法，对基因表达综合数据库（Gene Expression Omnibus, GEO）中582例乳腺癌病例的基质与免疫组分丰度，以及肿瘤浸润免疫细胞（Tumor-infiltrating immune cells, TICs）的浸润水平进行了评估。随后采用单变量Cox比例风险回归、LASSO回归及多变量Cox回归三种回归模型，筛选出7个与乳腺癌生存预后相关的免疫特异性基因。在这7个基因中，ATP酶分泌通路Ca²+转运蛋白2（ATPase Secretory Pathway Ca2+ Transporting 2, ATP2C2）因可显著预测乳腺癌患者预后而受到关注。进一步分析显示，ATP2C2的表达水平与患者的临床病理特征（年龄、T分期与N分期）密切相关，且与乳腺癌患者的生存预后呈负相关。本研究通过基因集富集分析（Gene Set Enrichment Analysis, GSEA），对比了ATP2C2高表达组与低表达组的通路富集特征：ATP2C2低表达组的基因主要富集于免疫相关生物学过程，而高表达组的基因则主要富集于代谢相关通路。值得注意的是，Pearson相关性分析结果表明，ATP2C2的表达水平与滤泡辅助性T细胞（T follicular helper, Tfh）呈正相关，与γδ T细胞（Gamma delta T cell, γδ T）呈负相关，提示ATP2C2可能参与维持肿瘤微环境的免疫主导状态。综上，本研究全面解析了肿瘤微环境，并筛选出与乳腺癌预后相关的免疫标志物；其中ATP2C2或可用于预测乳腺癌患者的预后，为乳腺癌的临床治疗提供了新的视角。