Shi Hanlu, Yao Hongfeng, Zhou Yi, Wu Gaoping, Li Keyi, Tang Lusheng, Yang Chen, Wang Dong, Jin Weidong
Laboratory Medicine Center, Department of Laboratory Medicine, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Department of Clinical Laboratory, Zhuji People's Hospital of Zhejiang Province, Zhuji, China.
Transl Cancer Res. 2024 Nov 30;13(11):5751-5770. doi: 10.21037/tcr-24-683. Epub 2024 Nov 27.
Gastric cancer (GC) is a malignancy with a grim prognosis, ranking as the second most common cause of cancer-related deaths globally. Various investigations have demonstrated the substantial involvement of ferroptosis and pyroptosis in the advancement of tumors. Nevertheless, the precise molecular mechanisms by which distinct genes associated with ferroptosis and pyroptosis influence the tumor microenvironment (TME) in GC remain elusive. Therefore, this study aims to elucidate the role of ferroptosis and pyroptosis in GC and provide insigths for GC therapy and prognosis evaluation.
The data including gene expression, clinicopathological characteristics and survival information of GC samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts were collected, and the expression level of ferroptosis and pyroptosis genes (FPGs) in GC samples were analyzed. Consensus clustering analysis, Cox logistic regression, principal component analysis (PCA), and the "survival", "survminer", "limma", "ggplot2" and other packages in R were utilized to compare the differences among different groups. In the level of GC cells, cell viability experiments were conducted by Cell Counting Kit-8 (CCK-8) assay.
Through the analysis of the expression level of FPGs in GC samples from the TCGA and GEO cohorts, twenty-three prognostic-related and differentially expressed FPGs were collected for further analysis. Through consensus clustering analysis, three distinct patterns of FPGs were identified and found to be correlated with clinicopathological characteristics, immune cell infiltration, and prognosis in patients with GC. Subsequently, 684 prognostic-related genes from 1,082 pattern-related differentially expressed genes (DEGs) were screened for constructing the FPG_Score system to quantify FPGs patterns in individual GC patients and predict the prognosis. The analysis indicated that GC patients with high FPG_Score exhibited improved survival rates, increased tumor mutation burden (TMB), higher microsatellite instability (MSI), and elevated programmed cell death protein ligand 1 (PD-L1) expression. These patients with high FPG_Score were more likely to benefit from immunotherapy and had a more favorable prognosis.
Our study innovatively provided a comprehensive analysis of FPGs in GC, and constructed the FPG_Score system for stratification of individual patients, so as to predict its benefit from immunotherapy and prognosis.
胃癌（GC）是一种预后严峻的恶性肿瘤，是全球癌症相关死亡的第二大常见原因。各种研究表明，铁死亡和焦亡在肿瘤进展中起重要作用。然而，与铁死亡和焦亡相关的不同基因影响GC肿瘤微环境（TME）的精确分子机制仍不清楚。因此，本研究旨在阐明铁死亡和焦亡在GC中的作用，并为GC治疗和预后评估提供见解。
收集来自癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）队列的GC样本的基因表达、临床病理特征和生存信息数据，并分析GC样本中铁死亡和焦亡相关基因（FPGs）的表达水平。使用R语言中的一致性聚类分析、Cox逻辑回归、主成分分析（PCA）以及“survival”“survminer”“limma”“ggplot2”等软件包比较不同组之间的差异。在GC细胞水平上，通过细胞计数试剂盒-8（CCK-8）试验进行细胞活力实验。
通过分析TCGA和GEO队列中GC样本的FPGs表达水平，收集了23个与预后相关且差异表达的FPGs进行进一步分析。通过一致性聚类分析，确定了三种不同的FPGs模式，并发现它们与GC患者的临床病理特征、免疫细胞浸润和预后相关。随后，从1082个模式相关的差异表达基因（DEGs）中筛选出684个与预后相关的基因，构建FPG_Score系统，以量化个体GC患者的FPGs模式并预测预后。分析表明，FPG_Score高的GC患者生存率提高、肿瘤突变负担（TMB）增加、微卫星不稳定性（MSI）更高以及程序性细胞死亡蛋白配体1（PD-L1）表达升高。这些FPG_Score高的患者更有可能从免疫治疗中获益，预后更有利。
我们的研究创新性地对GC中的FPGs进行了全面分析，并构建了FPG_Score系统用于个体患者分层，从而预测其从免疫治疗中的获益和预后。
