Identification and Validation of a Prognostic Signature Based on Fibroblast Immune-related Genes to Predict the Prognosis and Therapeutic Response of renal clear cell carcinoma by Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data

基于成纤维细胞免疫相关基因的预后特征的鉴定和验证:通过单细胞和批量RNA测序数据的整合分析预测肾透明细胞癌的预后和治疗反应

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Abstract

Background: The importance of fibroblasts in cancer progression is becoming more acknowledged, particularly the significance of their immune-related genes. However, the precise roles these genes play in fibroblasts throughout tumor development remains unclear. Exploring how these genes function in advancing kidney renal clear cell carcinoma (KIRC) could provide answers to these uncertainties. Material and method: The Cancer Genome Atlas (TCGA) database served as the source of data for KIRC patients. We distinguished fibroblast immune-related genes (FIGs), which are used to construct risk score. Further analysis conducted including enrichment analysis, assessment of tumor mutation burden (TMB), evaluation of tumor microenvironment (TME), analysis of immune cell infiltration, and drug sensitivity prediction. Result: The risk score using 6 FIGs effectively predicts the outcomes for KIRC patients. Nomogram which is based on the risk score and clinical data, demonstrated superior predictive performance compared to the version without the risk score. Enrichment analysis identified that coagulation pathway predominates in high-risk group, the protein secretion pathway is prevalent in low-risk patients' cohort. The adverse prognosis in high-risk patient cohort could be linked to an elevated TMB. TME analysis showed that high-risk group's tumor tissues contain more immune and stromal cells. Furthermore, the amount of regulatory T cells increases with the risk score. Low-risk group response better to immunotherapy. Finally, RT-qPCR confirmed the differential expression of FIGs in KIRC patients. Conclusion: This risk score and nomogram are valuable tools assessing KIRC patients' prognosis. Poorer prognosis in high-risk categories may have relationship with activation of coagulation pathway and a higher TMB.

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