Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Cancer Immunol Immunother. 2023 May;72(5):1121-1138. doi: 10.1007/s00262-022-03316-z. Epub 2022 Nov 7.
Ovarian metastasis (OM) poses a major threat to the outcome of gastric cancer (GC) patients. Recently, immunotherapy emerged as a novel promising therapeutic strategy to treat late-stage GC, whereas its efficacy is influenced by tumor immune microenvironment (TIME). M2 macrophage, a key subset within TIME, plays dual immunosuppressive and pro-tumorigenic roles in cancer progression and is recognized as a potential therapeutic target. However, molecular mechanisms underlying OM remain elusive and the TIME-related prognostic and immunotherapeutic index for these patients is yet to establish.
Differential expressed genes (DEGs) between paired normal mucosa, primary GC and OM of patients from Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 6) were identified by transcriptome sequencing, followed by the functional annotation of enriched hallmark pathways of DEGs between them. CIBERSORT was used to profile the relative expression level of 22 immune cell subsets in normal tissues, primary and metastatic tumors, followed by weighted gene coexpression network analysis (WGCNA) uncovering immune cell-correlated gene sets. The intersected genes between DEGs and M2 macrophage-related genes were processed by least absolute shrinkage and selection operator (LASSO) regression analysis to construct a predictive signature, M2GO, which was further validated by training set and test set of The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD), GSE62254 and GSE84437 cohorts. GC patients were divided into M2GO-high and -low subgroup according to the optimal cutoff value of the M2GO score. Furthermore, the clinical, molecular and immune features between M2GO-high and -low subgroups were analyzed. Clinical cohorts of immunotherapy were used to validate the predictive value of M2GO in regard to immunotherapy effectiveness.
Transcriptomic sequencing and follow-up analyses of triple-matched normal tissues, primary and ovarian metastatic tumors identified distinctive sets of DEGs and enriched immune-, cancer- and metastasis-related pathways between them. Of note, M2 macrophage, a major immunosuppressive and pro-tumorigenic component within TIME, was significantly up-regulated in OMs. WGCNA and LASSO regression were applied to establish a novel OM- and M2 macrophage-related predictive signature, M2GO, based on M2 macrophage-related prognostic genes including GJA1, MAGED1 and SERPINE1. M2GO served as an independent prognostic factor of GC patients. Comprehensive molecular and immune characterization of M2GO-based subgroups uncovered their distinctive features in terms of enriched functional pathways, tumor mutation burden, key immune checkpoints, major regulators of natural immune cGAS-STING pathway, infiltrated subsets of immune cells and tumor immune exclusion/dysfunction (TIDE) score. Notably, the M2GO score was significantly lower in responsive group than non-responsive group (P < 0.05) in clinical cohort of metastatic GC patients undergoing immunotherapy.
Transcriptomic characterization of paired normal mucosae, primary and ovarian metastatic tumors revealed their unique molecular and immune features. Follow-up analyses established a novel OM- and M2 macrophage-related signature, M2GO, which served as a promising prognostic and immunotherapeutic biomarker to distinguish the clinical outcome, molecular and immune features of GC patients and predict their differential responses to immunotherapy.
卵巢转移（OM）对胃癌（GC）患者的预后构成重大威胁。最近，免疫疗法作为一种治疗晚期 GC 的新的有前途的治疗策略出现，但其疗效受肿瘤免疫微环境（TIME）的影响。M2 巨噬细胞是 TIME 中的一个关键亚群，在癌症进展中发挥双重免疫抑制和促肿瘤作用，并被认为是一个潜在的治疗靶点。然而，OM 的分子机制仍不清楚，这些患者的 TIME 相关预后和免疫治疗指数尚未建立。
通过转录组测序鉴定了来自复旦大学上海癌症中心（FUSCC）队列的患者配对正常黏膜、原发性 GC 和 OM 之间的差异表达基因（DEGs），随后对它们之间的 DEGs 富集标志性通路进行功能注释。使用 CIBERSORT 分析正常组织、原发性和转移性肿瘤中 22 种免疫细胞亚群的相对表达水平，然后进行加权基因共表达网络分析（WGCNA），揭示与免疫细胞相关的基因集。将 DEGs 与 M2 巨噬细胞相关基因之间的交集基因通过最小绝对收缩和选择算子（LASSO）回归分析进行处理，构建一个预测性标志，M2GO，该标志进一步通过 The Cancer Genome Atlas-Stomach Adenocarcinoma（TCGA-STAD）、GSE62254 和 GSE84437 队列的训练集和测试集进行验证。根据 M2GO 评分的最佳截断值，GC 患者被分为 M2GO-高和 M2GO-低亚组。此外，分析了 M2GO-高和 M2GO-低亚组之间的临床、分子和免疫特征。使用免疫治疗的临床队列验证 M2GO 对免疫治疗效果的预测价值。
对三重配对正常组织、原发性和卵巢转移性肿瘤进行转录组测序和后续分析，确定了不同的 DEG 集和富集的免疫、癌症和转移相关通路。值得注意的是，M2 巨噬细胞，TIME 中的主要免疫抑制和促肿瘤成分，在 OM 中显著上调。WGCNA 和 LASSO 回归被应用于建立一个新的 OM 和 M2 巨噬细胞相关的预测标志，M2GO，基于 M2 巨噬细胞相关的预后基因，包括 GJA1、MAGED1 和 SERPINE1。M2GO 是 GC 患者的独立预后因素。基于 M2GO 的亚组的综合分子和免疫特征揭示了它们在富集功能途径、肿瘤突变负担、关键免疫检查点、天然免疫 cGAS-STING 途径主要调节剂、浸润性免疫细胞亚群和肿瘤免疫排斥/功能障碍（TIDE）评分方面的独特特征。值得注意的是，在接受免疫治疗的转移性 GC 患者的临床队列中，M2GO 评分在反应组显著低于非反应组（P<0.05）。
配对正常黏膜、原发性和卵巢转移性肿瘤的转录组特征揭示了它们独特的分子和免疫特征。后续分析建立了一个新的 OM 和 M2 巨噬细胞相关的标志，M2GO，它作为一个有前途的预后和免疫治疗生物标志物，可以区分 GC 患者的临床结果、分子和免疫特征，并预测他们对免疫治疗的不同反应。
