Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Pathology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Front Immunol. 2022 Aug 26;13:930488. doi: 10.3389/fimmu.2022.930488. eCollection 2022.
Cervical cancer (CC) is a malignancy that tends to have a poor prognosis when detected at an advanced stage; however, there are few studies on the early detection of CC at the genetic level. The tumor microenvironment (TME) and genomic instability (GI) greatly affect the survival of tumor patients effects on carcinogenesis, tumor growth, and resistance. It is necessary to identify biomarkers simultaneously correlated with components of the TME and with GI, as these could predict the survival of patients and the efficacy of immunotherapy. In this study, we extracted somatic mutational data and transcriptome information of CC cases from The Cancer Genome Atlas, and the GSE44001 dataset from the Gene Expression Omnibus database was downloaded for external verification. Stromal components differed most between genomic unstable and genomic stable groups. Differentially expressed genes were screened out on the basis of GI and StromalScore, using somatic mutation information and ESTIMATE methods. We obtained the intersection of GI- and StromalScore-related genes and used them to establish a four-gene signature comprising RIPOR2, CCL22, PAMR1, and FBN1 for prognostic prediction. We described immunogenomic characteristics using this risk model, with methods including CIBERSORT, gene set enrichment analysis (GSEA), and single-sample GSEA. We further explored the protective factor RIPOR2, which has a close relationship with ImmuneScore. A series of experiments, including immunohistochemistry, immunofluorescence, quantitative reverse transcription PCR, transwell assay, CCK8 assay, EdU assay, cell cycle detection, colony formation assay, and Western blotting were performed to validate RIPOR2 as an anti-tumor signature. Combined with integrative bioinformatic analyses, these experiments showed a strong relationship between RIPOR2 with tumor mutation burden, expression of genes related to DNA damage response (especially PARP1), TME-related scores, activation of immune checkpoint activation, and efficacy of immunotherapy. To summarize, RIPOR2 was successfully identified through comprehensive analyses of the TME and GI as a potential biomarker for forecasting the prognosis and immunotherapy response, which could guide clinical strategies for the treatment of CC patients.
宫颈癌(CC)是一种恶性肿瘤,当在晚期发现时往往预后不良;然而,在遗传水平上对 CC 的早期检测研究甚少。肿瘤微环境(TME)和基因组不稳定性(GI)极大地影响肿瘤患者的生存,对肿瘤的发生、肿瘤的生长和耐药性都有影响。有必要同时识别与 TME 成分和 GI 相关的生物标志物,因为这些标志物可以预测患者的生存和免疫治疗的疗效。在这项研究中,我们从癌症基因组图谱(TCGA)中提取了 CC 病例的体细胞突变数据和转录组信息,并从基因表达综合数据库(GEO)中下载了 GSE44001 数据集进行外部验证。基因组不稳定和基因组稳定组之间的间质成分差异最大。基于 GI 和 StromalScore,使用体细胞突变信息和 ESTIMATE 方法筛选出差异表达基因。我们获得了 GI 和 StromalScore 相关基因的交集,并使用它们建立了一个包含 RIPOR2、CCL22、PAMR1 和 FBN1 的四基因特征模型,用于预后预测。我们使用该风险模型描述了免疫基因组学特征,包括 CIBERSORT、基因集富集分析(GSEA)和单样本 GSEA。我们进一步探讨了保护性因子 RIPOR2,它与 ImmuneScore 密切相关。一系列实验,包括免疫组织化学、免疫荧光、定量逆转录 PCR、Transwell 测定、CCK8 测定、EdU 测定、细胞周期检测、集落形成测定和 Western blot 分析,用于验证 RIPOR2 作为一种抗肿瘤标志物。通过综合生物信息学分析,这些实验显示了 RIPOR2 与肿瘤突变负荷、与 DNA 损伤反应相关基因的表达(尤其是 PARP1)、TME 相关评分、免疫检查点激活的激活以及免疫治疗的疗效之间的强烈关系。总之,通过对 TME 和 GI 的综合分析,成功地鉴定了 RIPOR2 作为预测预后和免疫治疗反应的潜在生物标志物,这可以指导 CC 患者治疗的临床策略。