目的：采用生物信息学方法探索卵巢癌中与血管生成相关的免疫基因（ARIG），探讨其与卵巢癌患者预后的关系，并 说明不同预后患者肿瘤微环境和免疫治疗的潜在差异，为卵巢癌患者提供新的治疗靶点。方法：分别从TCGA和GEO数据库下 载卵巢癌的转录组数据和生存数据。利用R软件分析差异表达基因，利用Pearson相关系数鉴定血管生成相关基因与免疫相关 基因之间的相关性，筛选出差异表达的ARIG。通过Lasso回归分析构建预后模型，通过Cox分析临床特征和风险评分，将样本分 为高风险组和低风险组。通过单样本基因集富集分析（ssGSEA）、肿瘤免疫功能障碍和排斥（TIDE）分析预后风险模型与免疫浸 润、免疫治疗反应的相关性。最后，收集河北医科大学第四医院2015年5月至2016年5月手术的卵巢癌患者的肿瘤组织和输卵 管组织85对，通过qPCR和WB法验证五个差异表达的ARIG在卵巢癌组织中的表达情况，分析其与卵巢癌患者临床病理特征的 关系，并初步探索其在卵巢癌细胞的生物学功能。结果：通过生信分析筛选出142个差异表达的ARIG，通过Lasso和Cox回归分 析，得到5个基因作为预后基因（PTGER3、SCTR、IGHG1、HSPA8、IGF2），构建了预后风险模型，高风险组患者的预后更差；此外， 不同风险评分的患者在免疫细胞浸润和免疫治疗反应方面存在显著差异（均P<0.05）。通过qPCR和WB法验证这5个基因在卵 巢癌组织中均为高表达（均P<0.01），其中HSPA8表达量最高，且高表达HSPA8与卵巢癌患者FIGO分期晚、组织分级差、淋巴结 转移及腹膜转移呈显著正相关（P<0.001）。细胞功能实验证实，HSPA8可促进卵巢癌细胞的增殖、迁移和侵袭（P<0.01）。结论： 差异表达的5种ARIG能有效预测卵巢癌患者的预后，并且与免疫细胞浸润和免疫治疗疗效有关，初步证实其在卵巢中发挥促癌 作用。

Objective: To explore angiogenesis-related immune genes (ARIGs) in ovarian cancer using the bioinformatics method, investigate their relationship with ovarian cancer prognosis, and elucidate potential differences in tumor microenvironment and immunotherapy response among patients with different prognosis, so as to provide new therapeutic targets for ovarian cancer patients. Methods: Transcriptome and survival data for ovarian cancer were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, respectively. The differentially expressed genes were analyzed using R software, and the correlation between ARIGs and immune-related genes was identified by the Pearson correlation coefficient, leading to the selection of differentially expressed ARIGs. A prognostic model was constructed by LASSO regression analysis, and the clinical features and risk scores were evaluated through COX analysis. Patients were divided into a high-risk group and a low-risk group. Single sample gene set enrichment analysis (ssGSEA) and tumor immune dysfunction and exclusion (TIDE) were used to analyze the correlation between the prognostic risk model and immune invasion and immunotherapy response. Finally, 85 pairs of tumor tissues and fallopian tube tissues of ovarian cancer patients who were surgically treated in the Fourth Hospital of Hebei Medical University from May 2015 to May 2016 were collected. The expression of five differentially expressed ARIGs in ovarian cancer tissues was verified by qPCR and WB, and their relationship with clinicopathological features of ovarian cancer patients was analyzed. The biological function of these ARIGs in ovarian cancer cells was preliminarily explored. Results: A total of 142 differentially expressed ARIGs were screened by bioinformatics analysis. Lasso and Cox regression analyses identified five genes (PTGER3, SCTR, IGHG1, HSPA8, IGF2) as prognostic genes, and a prognostic risk model was constructed. Patients in the high-risk group had a worse prognosis. Moreover, significant differences were observed in immune cell infiltration and immunotherapy response between patients with different risk scores. Finally, qPCR and WB verified that these 5 genes were highly expressed in ovarian cancer tissues, with HSPA8 being the most highly expressed. High HSPA8 expression was positively correlated with advanced FIGO stage, poor histological grade, lymph node metastasis and peritoneal metastasis in ovarian cancer patients (all P<0.001). Cell function experiments confirmed that HSPA8 could promote the proliferation, migration, and invasion of ovarian cancer cells(P<0.01). Conclusion: The five differentially expressed ARIGs can effectively predict the prognosis of ovarian cancer patients and are related to immune cell infiltration and immunotherapy efficacy. Preliminary evidence suggests that these genes play a pro-carcinogenic role in ovary cancer.

国家自然科学基金（No. 81871894）