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单细胞和批量转录组的综合分析揭示了缺氧诱导的免疫抑制微环境以预测高级别浆液性卵巢癌的免疫治疗反应。

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

作者信息

Chen Qingshan, Zhang Yue, Wang Chao, Ding Hui, Chi Liqun

机构信息

Department of Pharmacy, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.

Department of Gynecology, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.

出版信息

Front Pharmacol. 2024 Nov 13;15:1450751. doi: 10.3389/fphar.2024.1450751. eCollection 2024.

Abstract

BACKGROUND

Hypoxia 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.

METHODS

By 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.

RESULTS

Hypoxia 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 Hypoxia/TME 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 Hypoxia/TME subgroup exhibit a better response to immunotherapy, suggesting the potential utility of the Hypoxia-TME classifier as a new biomarker in HGSOC.

CONCLUSION

Our study revealed hypoxia-induced immunosuppressive microenvironment, and developed Hypoxia-TME classifier to distinguish the prognosis, immune characteristics, and potential benefits of immunotherapy in HGSOC.

摘要

背景

缺氧与癌症进展及治疗结果显著相关。然而,高级别浆液性卵巢癌(HGSOC)中缺氧诱导的免疫抑制微环境的精确分子机制仍未完全阐明。

方法

通过分析五个独立的转录组数据集,我们研究了缺氧对HGSOC预后和肿瘤微环境(TME)的影响。使用单细胞分析研究缺氧水平和细胞间通讯信号通路。此外,开发了缺氧-TME分类器,并在多个HGSOC数据集中进行验证。另外,我们还研究了不同缺氧-TME亚组中的预后意义、基因变异、信号通路以及免疫治疗获益潜力。

结果

缺氧被确定为HGSOC中的关键危险因素,并与以免疫细胞组成和分布改变为特征的免疫抑制微环境密切相关。单细胞分析阐明了HGSOC中TME固有的异质性,并证明了缺氧TME与成纤维细胞和巨噬细胞之间的关联。CellChat分析确定SPP1-CD44和CXCL12-CXCR4分别为巨噬细胞和成纤维细胞与T细胞相互作用的主要信号轴。此外,通过整合缺氧(18个基因)和TME(7种免疫细胞)评分构建并验证了个性化的缺氧-TME分类器。观察到缺氧/TME亚组的患者预后明显优于其他亚组。不同亚组表现出独特的基因组改变和信号通路差异,包括与各种生物学功能密切相关的TGF-β和Wnt/β-连环蛋白通路。最后,我们的结果表明缺氧/TME亚组的患者对免疫治疗反应更好,提示缺氧-TME分类器作为HGSOC新生物标志物的潜在效用。

结论

我们的研究揭示了缺氧诱导的免疫抑制微环境,并开发了缺氧-TME分类器以区分HGSOC的预后、免疫特征和免疫治疗的潜在获益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/393a/11598517/fde2f92d8b7c/fphar-15-1450751-g001.jpg

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