DataSheet1_Integrated analysis of single-cell and bulk transcriptome reveals hypoxia-induced immunosuppressive microenvironment to predict immunotherapy response in high-grade serous ovarian cancer.zip

BackgroundHypoxia is significantly associated with cancer progression and treatment outcomes. Nevertheless, the precise molecular mechanisms underlying the hypoxia-induced immunosuppressive microenvironment in high-grade serous ovarian cancer (HGSOC) are still not fully understood.
MethodsBy analyzing five independent transcriptomic datasets, we investigated the effect of hypoxia on prognosis and tumor microenvironment (TME) in HGSOC. The hypoxia levels and the intercellular communication signaling pathways were studied by using single-cell analysis. Furthermore, the Hypoxia-TME classifier was developed and then validated in the multiple HGSOC datasets. In addition, we also investigated the prognostic significance, genetic variations, signaling pathways, and the potential for immunotherapy benefits in different Hypoxia-TME subgroups.
ResultsHypoxia was identified as a crucial risk factor in HGSOC, and strongly correlated with an immunosuppressive microenvironment characterized by alterations in the composition and distribution of immune cells. Single-cell analysis elucidated the heterogeneity inherent within the TME in HGSOC, and demonstrated an association between the hypoxic TME and fibroblasts as well as macrophages. CellChat analysis identified SPP1-CD44 and CXCL12-CXCR4 as the principal signaling axes through which macrophages and fibroblasts interact with T cells, respectively. Moreover, a personalized Hypoxia-TME classifier was constructed and validated through the integration of the hypoxia (18 genes) and TME (7 immune cells) scores. It was observed that patients in the Hypoxialow/TMEhigh subgroup displayed a significantly better prognosis than other subgroups. Different subgroups exhibited unique genomic alterations and variations in signaling pathway differences, including TGF-β and Wnt/β-catenin pathways, which are closely associated with various biological functions. Finally, our results indicated that patients in the Hypoxialow/TMEhigh subgroup exhibit a better response to immunotherapy, suggesting the potential utility of the Hypoxia-TME classifier as a new biomarker in HGSOC.
ConclusionOur study revealed hypoxia-induced immunosuppressive microenvironment, and developed Hypoxia-TME classifier to distinguish the prognosis, immune characteristics, and potential benefits of immunotherapy in HGSOC.

背景：缺氧（Hypoxia）与癌症进展及治疗结局显著相关。然而，高级别浆液性卵巢癌（high-grade serous ovarian cancer, HGSOC）中缺氧诱导免疫抑制微环境的确切分子机制仍未完全阐明。
方法：本研究通过分析5个独立的转录组数据集，探讨了缺氧对高级别浆液性卵巢癌（HGSOC）患者预后及肿瘤微环境（tumor microenvironment, TME）的影响。采用单细胞分析手段探究了缺氧水平及细胞间通信信号通路。此外，本研究构建了缺氧-肿瘤微环境（Hypoxia-TME）分类器，并在多组HGSOC数据集中完成验证。同时，还分析了不同缺氧-TME亚组的预后价值、遗传变异、信号通路特征及免疫治疗获益潜力。
结果：研究证实缺氧是高级别浆液性卵巢癌（HGSOC）的关键危险因素，且与以免疫细胞组成及分布异常为特征的免疫抑制微环境密切相关。单细胞分析阐明了HGSOC肿瘤微环境（TME）固有的异质性，并证实缺氧型TME与成纤维细胞及巨噬细胞存在关联。CellChat分析发现，巨噬细胞与成纤维细胞分别通过SPP1-CD44及CXCL12-CXCR4这两条主要信号轴与T细胞发生相互作用。此外，本研究整合缺氧相关18个基因评分与7种免疫细胞评分，构建并验证了个体化缺氧-肿瘤微环境（Hypoxia-TME）分类器。分析显示，缺氧低表达/高TME亚组患者的预后显著优于其他亚组。不同亚组具有独特的基因组变异及信号通路差异，包括与多种生物学功能密切相关的转化生长因子-β（TGF-β）及Wnt/β-连环蛋白（Wnt/β-catenin）通路。最后，本研究结果表明，缺氧低表达/高TME亚组患者对免疫治疗的响应更佳，提示缺氧-肿瘤微环境（Hypoxia-TME）分类器有望成为HGSOC的新型生物标志物。
结论：本研究揭示了缺氧诱导的免疫抑制微环境，并构建了缺氧-肿瘤微环境（Hypoxia-TME）分类器，以区分高级别浆液性卵巢癌（HGSOC）患者的预后、免疫特征及免疫治疗潜在获益人群。