基于批量与单细胞RNA测序鉴定微卫星稳定型胃癌中乳酸化相关基因特征
Identification of a lactylation-related gene signature in microsatellite stable gastric cancer based on bulk and single-cell RNA-seq.
摘要(中文译文)
微卫星稳定（MSS）胃癌（GC）对免疫治疗反应不佳，且预后异质性明显。组蛋白乳酸化在肿瘤进展中发挥关键作用。然而，乳酸化相关基因特征（LRGS）在MSS胃癌中的预后和治疗潜力在很大程度上仍未被探索。从癌症基因组图谱和基因表达综合数据库中获取MSS胃癌患者的数据。基于乳酸化相关基因表达谱进行共识聚类以对患者进行分层。我们进一步使用机器学习算法构建了LRGS。我们还评估了其与临床病理参数、肿瘤微环境和化疗敏感性的相关性。采用肿瘤免疫功能障碍与排斥（TIDE）算法预测对免疫治疗的潜在反应。整合单细胞分析、细胞间通讯分析、计算机模拟基因敲除和免疫组化验证，以探索关键基因的功能作用。共识聚类揭示了两个总生存结局显著不同的聚类。建立了一个九基因LRGS，并有效地将患者分为高风险组和低风险组。高风险组表现出免疫抑制性微环境、化疗敏感性降低和更高的TIDE评分。单细胞分析显示，LRGS评分在癌症相关成纤维细胞（CAFs）中最高，且 和 分别在PDGFRA+ CAFs和CA9+ CAFs中高表达。细胞间通讯分析表明，这两种CAF亚型通过COLLAGEN和MIF通路表现出不同的信号模式。计算机模拟基因敲除进一步验证了 和 对于各自CAF亚型中的基质重塑和缺氧适应至关重要。免疫组化分析证实MSS胃癌中 和 的蛋白水平升高。本研究开发并验证了一个稳健的MSS胃癌LRGS。该特征有助于准确的预后预测，并显示出预测化疗和免疫治疗反应的潜力。
Abstract
Microsatellite stable (MSS) gastric cancer (GC) responds poorly to immunotherapy and exhibits heterogeneous outcomes. Histone lactylation plays a critical role in cancer progression. However, the prognostic and therapeutic potential of a lactylation-related gene signature (LRGS) in MSS GC remains largely unexplored. Data of MSS GC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering based on lactylation-related gene expression profiles was performed to stratify patients. We further constructed the LRGS using machine learning algorithms. We also assessed its correlations with clinicopathological parameters, the tumor microenvironment, and chemosensitivity. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was employed to predict potential responses to immunotherapy. Single-cell analysis, cell-cell communication analysis, in silico knockout, and immunohistochemical validation were integrated to explore the functional roles of key genes. Consensus clustering uncovered two clusters with significantly different overall survival outcomes. A nine-gene LRGS was established and effectively stratified patients into high- and low-risk groups. The high-risk group displayed an immunosuppressive microenvironment, reduced chemosensitivity, and higher TIDE scores. Single-cell analysis revealed that LRGS scores were highest in cancer-associated fibroblasts (CAFs), with and highly expressed in PDGFRA+ CAFs and CA9+ CAFs, respectively. Cell-cell communication analysis showed that these two CAF subtypes exhibited distinct signaling patterns via the COLLAGEN and MIF pathways. In silico knockout further validated that and are essential for matrix remodeling and hypoxia adaptation in their respective CAF subtypes. Immunohistochemical analysis confirmed elevated protein levels of and in MSS GC. This study developed and validated a robust LRGS for MSS GC. This signature facilitates accurate prognosis prediction and shows potential to predict responses to both chemotherapy and immunotherapy.
如何引用
AMA
Zhong-Tai Lin, Yuan-Chun Chen, Li-Sheng You, Yuan-Zhao Wang, Xiang-Yu Wang, Liang-Jie Chi. Identification of a lactylation-related gene signature in microsatellite stable gastric cancer based on bulk and single-cell RNA-seq.. Frontiers in immunology. 2026; doi:10.3389/fimmu.2026.1838771.
APA
Zhong-Tai Lin, Yuan-Chun Chen, Li-Sheng You, Yuan-Zhao Wang, Xiang-Yu Wang, Liang-Jie Chi (2026). Identification of a lactylation-related gene signature in microsatellite stable gastric cancer based on bulk and single-cell RNA-seq.. Frontiers in immunology. https://doi.org/10.3389/fimmu.2026.1838771
GB/T 7714
Zhong-Tai Lin, Yuan-Chun Chen, Li-Sheng You, Yuan-Zhao Wang, Xiang-Yu Wang, Liang-Jie Chi. Identification of a lactylation-related gene signature in microsatellite stable gastric cancer based on bulk and single-cell RNA-seq.[J]. Frontiers in immunology, 2026 doi:10.3389/fimmu.2026.1838771.
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