Jiang Quan, Sun Jie, Chen Hao, Ding Chen, Tang Zhaoqing, Ruan Yuanyuan, Liu Fenglin, Sun Yihong
Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Human Phenome Institute, Fudan University, Shanghai, China.
Front Oncol. 2021 Jul 9;11:650673. doi: 10.3389/fonc.2021.650673. eCollection 2021.
The immune microenvironment plays a critical role in tumor biology. The molecular profiles of immune components and related genes are of tremendous value for the study of primary resistance to immune checkpoint blockers (ICBs) for gastric cancer (GC) and serve as prognostic biomarkers to predict GC survival. Recent studies have revealed that tumor immune cell infiltration (ICI) is an indicator of the survival and responsiveness to chemotherapy in GC patients. Here, we describe the immune cell landscape based on the ESTIMATE and CIBERSORT algorithms to help separate GC into 3 ICI clusters using the unsupervised clustering method. Further in-depth analyses, such as differential expression gene (DEG) analysis and principal component analysis (PCA), help to establish an ICI scoring system. A low ICI score is characterized by an increased tumor mutation burden (TMB). The combination of the ICI score and TMB score better predicts the survival of GC patients. Analyses based on public and our own database revealed that the ICI scoring system could also help predict the survival and chemotherapy responsiveness of GC patients. The present study demonstrated that the ICI score may be an effective prognostic biomarker and predictive indicator for chemotherapy and immunotherapy.
免疫微环境在肿瘤生物学中起着关键作用。免疫成分和相关基因的分子特征对于研究胃癌（GC）对免疫检查点阻断剂（ICB）的原发性耐药具有巨大价值，并可作为预测GC患者生存的预后生物标志物。最近的研究表明，肿瘤免疫细胞浸润（ICI）是GC患者生存和对化疗反应性的指标。在此，我们基于ESTIMATE和CIBERSORT算法描述免疫细胞格局，以使用无监督聚类方法将GC分为3个ICI簇。进一步的深入分析，如差异表达基因（DEG）分析和主成分分析（PCA），有助于建立ICI评分系统。低ICI评分的特征是肿瘤突变负担（TMB）增加。ICI评分和TMB评分的组合能更好地预测GC患者的生存情况。基于公共数据库和我们自己的数据库进行的分析表明，ICI评分系统还可以帮助预测GC患者的生存情况和化疗反应性。本研究表明，ICI评分可能是一种有效的预后生物标志物以及化疗和免疫治疗的预测指标。
