Xu Lijun, Hu Yaomin, Liu Wenwen
Department of Geratology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Front Genet. 2022 Mar 25;13:840348. doi: 10.3389/fgene.2022.840348. eCollection 2022.
Numerous reports have highlighted that the tumor microenvironment (TME) is closely linked to survival outcome and therapeutic efficacy. However, a comprehensive investigation of the TME feature in breast cancer (BC) has not been performed. Here, we performed consensus clustering analysis based on TME cell expression profiles to construct TME pattern clusters and TME-related gene signature in BC. GSVA combined with CIBERSORT and ssGSEA algorithms were applied to evaluate the differences in biological pathway and immune cell infiltration level, respectively. The PCA method was employed to construct TME-score to quantify the TME-mediated pattern level in individual BC patients. We determined two distinct TME gene clusters among 3,738 BC samples, which exhibited distinct survival outcome and enriched biological processes. The TME features demonstrated that these two clusters corresponded to the established immune profiles: hot and cold tumor phenotypes, respectively. Based on TME-related signature genes, we constructed the TME-score and stratified BC patients into low and high TME-score groups. Patients with high TME-score exhibited favorable outcome and increased infiltration of immune cells. Further investigation revealed that high TME-score was also related with high expression of immunosuppressive molecules, decreased tumor mutation burden (TMB), and high rate of mutation in significantly mutated genes (SMGs) (e.g., PIK3CA and CDH1). Assessing the TME-mediated pattern level of individual BC patients will assist us in better understanding the responses of BC patients to immunotherapies and directing more effective immunotherapeutic approaches.
众多报告强调肿瘤微环境(TME)与生存结果和治疗效果密切相关。然而,尚未对乳腺癌(BC)中的TME特征进行全面研究。在此,我们基于TME细胞表达谱进行共识聚类分析,以构建BC中的TME模式簇和TME相关基因特征。分别应用GSVA结合CIBERSORT和ssGSEA算法评估生物途径和免疫细胞浸润水平的差异。采用主成分分析(PCA)方法构建TME评分,以量化个体BC患者中TME介导的模式水平。我们在3738例BC样本中确定了两个不同的TME基因簇,它们表现出不同的生存结果和丰富的生物学过程。TME特征表明,这两个簇分别对应于已确定的免疫谱:热肿瘤和冷肿瘤表型。基于TME相关的特征基因,我们构建了TME评分,并将BC患者分为低TME评分组和高TME评分组。高TME评分的患者表现出良好的预后和免疫细胞浸润增加。进一步研究表明,高TME评分还与免疫抑制分子的高表达、肿瘤突变负担(TMB)降低以及显著突变基因(SMG)(如PIK3CA和CDH1)的高突变率相关。评估个体BC患者的TME介导的模式水平将有助于我们更好地理解BC患者对免疫治疗的反应,并指导更有效的免疫治疗方法。