Single-Cell and Spatial Transcriptomics Explore Purine Metabolism–Related Prognostic Risk Model and Tumor Immune Microenvironment Modulation in Ovarian Cancer

IF 3.3 2区 医学 Q2 GENETICS & HEREDITY
Yinglei Liu, Rui Geng, Songyun Zhao, Jinjin Yang, Jinhui Liu, Yanli Zheng, Weichun Tang
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Abstract

Background: Ovarian cancer (OC) ranks as the second leading cause of gynecological cancer–related deaths in women globally. Single-cell and spatial transcriptomics could precisely describe the heterogeneity of OC that affect the clinical treatment.

Methods: Single-cell sequencing and spatial transcriptomics information were from different public datasets. A pseudotime analysis of cellular developmental pathways, score single-cell gene sets, and cell activity ratings in each metabolic pathway were performed. A prognostic model was created using univariate regression analysis, LASSO, and multivariate regression analysis. Finally, the immune microenvironment and immunotherapeutic effects were analyzed for their association with purine metabolism activity. Finally, RT-qPCR was used to estimate the mRNA level of OC in cell lines.

Results: We observed a higher purine metabolism score by a signature of 12 purine metabolism–related gene in tumor cells. When compared with fibroblasts, epithelial cells with high scores displayed more intense TGF-β signaling pathway activity. Forty-four differentially expressed purine metabolism–related genes were identified to be substantially expressed in the tumor’s core region and were closely linked to purine and pyrimidine metabolic activities. Low-risk population had higher immune infiltration level and immunotherapy results. The NME6+ epithelial cell high-expression group had a greater prognosis and showed a negative connection with the tumor immune dysfunction and exclusion score and cancer-associated fibroblast cell concentration.

Conclusion: Purine metabolism was a predictor for OC patients’ prognosis. The presence of positive NME6 expression in epithelial cells emerges as a protective factor for OC patients, presenting a possible therapeutic target for personalized treatment.

Abstract Image

单细胞和空间转录组学研究卵巢癌嘌呤代谢相关的预后风险模型和肿瘤免疫微环境调节
背景:卵巢癌(OC)是全球女性妇科癌症相关死亡的第二大原因。单细胞和空间转录组学可以准确描述影响临床治疗的OC异质性。方法:单细胞测序和空间转录组学信息来自不同的公共数据集。对细胞发育途径进行伪时间分析,对单细胞基因集进行评分,并对每个代谢途径中的细胞活性进行评分。采用单因素回归分析、LASSO和多因素回归分析建立预后模型。最后,分析了免疫微环境和免疫治疗效果与嘌呤代谢活性的关系。最后,采用RT-qPCR方法检测OC在细胞系中的mRNA表达水平。结果:通过对肿瘤细胞中12个嘌呤代谢相关基因的标记,我们观察到肿瘤细胞中嘌呤代谢评分较高。与成纤维细胞相比,得分高的上皮细胞表现出更强的TGF-β信号通路活性。鉴定出44个差异表达嘌呤代谢相关基因在肿瘤核心区域大量表达,与嘌呤和嘧啶代谢活性密切相关。低危人群免疫浸润水平和免疫治疗效果较高。NME6+上皮细胞高表达组预后较好,与肿瘤免疫功能障碍、排斥评分及癌相关成纤维细胞浓度呈负相关。结论:嘌呤代谢是卵巢癌患者预后的一个预测因素。上皮细胞中NME6阳性表达成为OC患者的保护因素,为个性化治疗提供了可能的治疗靶点。
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来源期刊
Human Mutation
Human Mutation 医学-遗传学
CiteScore
8.40
自引率
5.10%
发文量
190
审稿时长
2 months
期刊介绍: Human Mutation is a peer-reviewed journal that offers publication of original Research Articles, Methods, Mutation Updates, Reviews, Database Articles, Rapid Communications, and Letters on broad aspects of mutation research in humans. Reports of novel DNA variations and their phenotypic consequences, reports of SNPs demonstrated as valuable for genomic analysis, descriptions of new molecular detection methods, and novel approaches to clinical diagnosis are welcomed. Novel reports of gene organization at the genomic level, reported in the context of mutation investigation, may be considered. The journal provides a unique forum for the exchange of ideas, methods, and applications of interest to molecular, human, and medical geneticists in academic, industrial, and clinical research settings worldwide.
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