Zhang Lu, Yang Mengjie, Zhang Yiqian, Lan Jianfa, Chen Qionghua
Laboratory of Research and Diagnosis of Gynecological Diseases of Xiamen City, Clinical Medical Research Center for Obstetrics and Gynecology Diseases of Fujian Province, Department of Obstetrics and Gynecology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China.
Sci Rep. 2025 May 28;15(1):18645. doi: 10.1038/s41598-025-02723-3.
Endometrial cancer (EC) is one of the most common malignancies in women. In recent years, immunotherapy has gradually become a significant treatment option. However, the mechanisms underlying immune checkpoint inhibitor (ICI)-related Adverse Events (AEs) remain poorly understood, posing significant challenges for optimizing clinical treatment strategies. This study aims to integrate the FAERS database and single-cell transcriptomic data to investigate potential mechanisms underlying PD-1 inhibitor-related AEs in EC immunotherapy, with a focus on exploring the PD-1-associated cell communication network and its potential compensatory activation pathways. Data related to AEs were extracted from the FAERS database. Disproportionality analyses, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS), were used to quantify signals of immune-related AEs (irAEs) associated with ICIs. We compared the occurrence timing and characteristics of AEs across different drugs. Subsequently, scRNA-seq was performed to analyze the tumor microenvironment of EC, focusing on PD-1-high expressing cell populations. Cell Communication was analyzed and key receptor-ligand pairs were identified. From Q1 2004 to Q3 2024, 21,838,627 drug-related reports were retrieved from FAERS, including 2,202 related to ICIs. ICI-associated irAEs involved 26 organ systems, with general disorders, gastrointestinal disorders, and injury/poisoning as the top System Organ Class (SOC). Fatigue, product use issues, and diarrhea were the most reported Preferred Terms (PTs). PD-1 inhibitors were associated with faster onset of AEs compared to PD-L1 inhibitors and Weibull modeling indicated an early failure-type AE pattern for both treatments. Single-cell analysis further demonstrated that PD-1 was highly expressed in CD8 + cytotoxic T cells and Tfh cells, which communicated with other cells within the tumor microenvironment through key receptor-ligand pairs such as CXCL12-CXCR4 and CXCL16-CXCR6. These findings suggested that PD-1 inhibitors may induce AEs through compensatory activation of the CXCR4 and CXCR6 pathways. This study suggested that PD-1 inhibitors may contribute to irAEs in EC, potentially through compensatory activation of the CXCR4 and CXCR6 pathways. By integrating FAERS and scRNA-seq data, key receptor-ligand interactions were identified, providing preliminary insights that could inform future efforts to optimize immunotherapy efficacy and mitigate AEs. However, further validation through clinical studies and mechanistic research is needed to confirm these findings.
子宫内膜癌(EC)是女性最常见的恶性肿瘤之一。近年来,免疫疗法逐渐成为一种重要的治疗选择。然而,免疫检查点抑制剂(ICI)相关不良事件(AE)的潜在机制仍知之甚少,这给优化临床治疗策略带来了重大挑战。本研究旨在整合FAERS数据库和单细胞转录组数据,以探究EC免疫治疗中PD-1抑制剂相关AE的潜在机制,重点探索与PD-1相关的细胞通讯网络及其潜在的代偿性激活途径。从FAERS数据库中提取与AE相关的数据。采用比例失衡分析,包括报告比值比(ROR)、比例报告比(PRR)、贝叶斯置信传播神经网络(BCPNN)和多项目伽马泊松收缩器(MGPS),来量化与ICI相关的免疫相关AE(irAE)信号。我们比较了不同药物AE的发生时间和特征。随后,进行单细胞RNA测序(scRNA-seq)以分析EC的肿瘤微环境,重点关注高表达PD-1的细胞群体。分析细胞通讯并确定关键的受体-配体对。2004年第一季度至2024年第三季度,从FAERS中检索到21,838,627份与药物相关的报告,其中2202份与ICI相关。ICI相关的irAE涉及26个器官系统,其中全身性疾病、胃肠道疾病以及损伤/中毒是最主要的系统器官分类(SOC)。疲劳、药物使用问题和腹泻是报告最多的首选术语(PT)。与PD-L1抑制剂相比,PD-1抑制剂相关AE的起病更快,威布尔模型表明两种治疗均呈现早期失效型AE模式。单细胞分析进一步表明,PD-1在CD8+细胞毒性T细胞和滤泡辅助性T细胞(Tfh细胞)中高表达,这些细胞通过CXCL12-CXCR4和CXCL16-CXCR6等关键受体-配体对与肿瘤微环境中的其他细胞进行通讯。这些发现表明,PD-1抑制剂可能通过CXCR4和CXCR6途径的代偿性激活诱导AE。本研究表明,PD-1抑制剂可能导致EC中的irAE,可能是通过CXCR4和CXCR6途径的代偿性激活。通过整合FAERS和scRNA-seq数据,确定了关键的受体-配体相互作用,为未来优化免疫治疗疗效和减轻AE的努力提供了初步见解。然而,需要通过临床研究和机制研究进行进一步验证以证实这些发现。