Xin Dao, Man Yuxin, Yang Yalan, Wang Feng
Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Medical Oncology, Sichuan Cancer Hospital, Medical School of University of Electronic Science and Technology of China, Chengdu, China.
Front Genet. 2022 Aug 25;13:953997. doi: 10.3389/fgene.2022.953997. eCollection 2022.
Gastric cancer is a major global public health burden worldwide. Although treatment strategies are continuously improving, the overall prognosis remains poor. Necroptosis is a newly discovered form of cell death associated with anti-tumor immunity. Gastric cancer (GC) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were downloaded. Bioinformatics analysis was performed to construct a necroptosis-related risk model and to establish cancer subtypes. Potential associations of the tumor immune microenvironment and immunotherapy response with necroptosis-related prognostic risk score (NRG risk score) were comprehensively explored. 16 GC and paired normal tissues were collected and RT-PCR was performed to examine expression of NRG related genes. GC samples were stratified into three subtypes according to prognostic necroptosis gene expression. A necroptosis risk model based on 12 genes (, , , , , , , , , , and ) was constructed and validated. The model was significantly associated with the OS and PFS of GC patients and the tumor immune microenvironment including immune cell infiltration, microsatellite instability (MSI) status, tumor mutational burden (TMB) score, immune checkpoint, and human leukocyte antigen (HLA) gene expression. A prognostic nomogram based on the NRG_score was additionally constructed. A low NRG risk score was correlated with high tumor immunogenicity and might benefit from immunotherapy. We have identified a useful prognostic model based on necroptosis-related genes in GC and comprehensively the relationship between necroptosis and tumor immunity. Predicting value to immunotherapy response is promising, and further research to validate the model in clinical practice is needed.
胃癌是全球主要的公共卫生负担。尽管治疗策略在不断改进，但总体预后仍然很差。坏死性凋亡是一种新发现的与抗肿瘤免疫相关的细胞死亡形式。从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载了胃癌（GC）数据。进行生物信息学分析以构建坏死性凋亡相关风险模型并建立癌症亚型。全面探讨了肿瘤免疫微环境和免疫治疗反应与坏死性凋亡相关预后风险评分（NRG风险评分）的潜在关联。收集了16例GC及配对的正常组织，并进行RT-PCR检测NRG相关基因的表达。根据预后坏死性凋亡基因表达将GC样本分为三种亚型。构建并验证了基于12个基因（、、、、、、、、、、和）的坏死性凋亡风险模型。该模型与GC患者的总生存期（OS）和无进展生存期（PFS）以及肿瘤免疫微环境显著相关，包括免疫细胞浸润、微卫星不稳定性（MSI）状态、肿瘤突变负荷（TMB）评分、免疫检查点和人类白细胞抗原（HLA）基因表达。此外，还构建了基于NRG_score的预后列线图。低NRG风险评分与高肿瘤免疫原性相关，可能从免疫治疗中获益。我们已经在GC中鉴定出一种基于坏死性凋亡相关基因的有用预后模型，并全面阐述了坏死性凋亡与肿瘤免疫之间的关系。对免疫治疗反应的预测价值很有前景，需要进一步研究在临床实践中验证该模型。
