Cao Qi, Xue Ruidong, Zhang Ning
Translational Cancer Research Center, Peking University First Hospital, Beijing 100034, China.
International Cancer Institute, Peking University Health Science Center, Beijing 100191, China.
Chin J Cancer Res. 2023 Jun 30;35(3):299-315. doi: 10.21147/j.issn.1000-9604.2023.03.08.
Cancer immunotherapy has made remarkable advances in recent years, but its effectiveness in treating gastric cancer is often limited by the complexity of the tumor microenvironment and the lack of effective biomarkers. This study aimed to identify effective biomarkers for immunotherapy treatment by characterizing the tumor microenvironment.
We retrieved the RNA-seq data from gastric cancer patients treated with the programmed death 1 (PD-1) blockade pembrolizumab. Differentially expressed genes associated with clinical outcomes were identified and further analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Gene signature scores were calculated by single sample Gene Set Enrichment Analysis (ssGSEA). The infiltration levels of immune cells were quantified using the xCell website. Cell type enrichment analysis was performed to compare treatment response and non-response groups, and regression analysis was used to investigate the relationship between interferon gamma (IFNγ) immune response and immune cell infiltration. Biomarkers were identified using least absolute shrinkage and selection operator (LASSO) analysis.
Compared to normal tissues, cytokine activity and interleukin-6 production were highly activated in gastric tumors. Responders to pembrolizumab showed significantly up-regulated expression of IFNγ response-related genes. Cell type enrichment analysis revealed that Th1 cells were significantly enriched in the tumor microenvironment of responders. Regression analysis indicated that Th1 cells induced IFNγ response more efficiently than other cell types. Using signatures of Th1 cells, stromal cells and IFNγ response, a set of eight genes were identified that effectively predicted the efficacy of immunotherapy treatment and patient prognosis.
Th1 cells promote therapeutic efficacy of PD-1 blockade by promoting IFNγ immune response in gastric cancer. The identified biomarkers have the potential to improve the effectiveness of immunotherapy treatment for gastric cancer patients.
近年来癌症免疫疗法取得了显著进展，但其在治疗胃癌方面的有效性常常受到肿瘤微环境的复杂性以及缺乏有效生物标志物的限制。本研究旨在通过对肿瘤微环境进行特征分析来确定免疫疗法治疗的有效生物标志物。
我们检索了接受程序性死亡1（PD-1）阻断剂派姆单抗治疗的胃癌患者的RNA测序数据。鉴定与临床结果相关的差异表达基因，并使用基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析进行进一步分析。通过单样本基因集富集分析（ssGSEA）计算基因特征分数。使用xCell网站对免疫细胞的浸润水平进行量化。进行细胞类型富集分析以比较治疗反应组和无反应组，并使用回归分析来研究干扰素γ（IFNγ）免疫反应与免疫细胞浸润之间的关系。使用最小绝对收缩和选择算子（LASSO）分析来鉴定生物标志物。
与正常组织相比，胃癌组织中的细胞因子活性和白细胞介素-6产生高度激活。派姆单抗治疗的反应者显示IFNγ反应相关基因的表达显著上调。细胞类型富集分析表明，Th1细胞在反应者的肿瘤微环境中显著富集。回归分析表明，Th1细胞比其他细胞类型更有效地诱导IFNγ反应。利用Th1细胞、基质细胞和IFNγ反应的特征，鉴定出一组八个基因，它们能够有效预测免疫疗法治疗的疗效和患者预后。
Th1细胞通过促进胃癌中的IFNγ免疫反应来提高PD-1阻断的治疗效果。所鉴定的生物标志物有可能提高胃癌患者免疫疗法治疗的有效性。
