Abstract
BackgroundThe tumor microenvironment acts a pivotal part in the occurrence and development of tumor. However, there are few studies on the microenvironment of papillary renal cell carcinoma (PRCC). Our study aims to explore prognostic genes related to tumor microenvironment in PRCC.MethodsPRCC expression profiles and clinical data were extracted from The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Immune/stromal scores were performed utilizing the ESTIMATE algorithm. Three hundred fifty-seven samples were split into two groups on the basis of median immune/stromal score, and comparison of gene expression was conducted. Intersect genes were obtained by Venn diagrams. Hub genes were selected through protein-protein interaction (PPI) network construction, and relevant functional analysis was conducted by DAVID. We used Kaplan–Meier analysis to identify the correlations between genes and overall survival (OS) and progression-free survival (PFS). Univariate and multivariate cox regression analysis were employed to construct survival model. Cibersort was used to predict the immune cell composition of high and low risk group. Combined nomograms were built to predict PRCC prognosis. Immune properties of PRCC were validated by The Cancer Immunome Atlas (TCIA).ResultsWe found immune/stromal score was correlated with T pathological stages and PRCC subtypes. Nine hundred eighty-nine differentially expressed genes (DEGs) and 1169 DEGs were identified respectively on the basis of immune and stromal score. Venn diagrams indicated that 763 co-upregulated genes and 4 co-downregulated genes were identified. Kaplan-Meier analysis revealed that 120 genes were involved in tumor prognosis. Then PPI network analysis identified 22 hub genes, and four of which were significantly related to OS in patients with PRCC confirmed by cox regression analysis. Finally, we constructed a prognostic nomogram which combined with influence factors.ConclusionsFour tumor microenvironment-related genes (CD79A, CXCL13, IL6 and CCL19) were identified as biomarkers for PRCC prognosis.
Highlights
The incidence of renal cell carcinoma (RCC) is approximately 431,288 in 2020, accounting for 2.2% of common malignant neoplasm on a global scale [1]
Surgery is the primary choice of treatment for early stage papillary renal cell carcinoma (PRCC), and comprehensive therapeutic approaches which include surgery, and immunotherapy are applied for advanced stage patients [4]
Immune/stromal score were significantly associated with T pathological stage and PRCC subtypes We downloaded 323 and 34 PRCC samples from the The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) database
Summary
The incidence of renal cell carcinoma (RCC) is approximately 431,288 in 2020, accounting for 2.2% of common malignant neoplasm on a global scale [1]. Papillary, and chromophobe renal cell carcinoma are three main histologic subtypes of RCC. Study reported papillary renal cell carcinoma (PRCC) is the second most common type [2]. The prognosis for PRCC is various on account of tumor metastasis and complications. The World Health Organization (WHO) classification (2016), according to different clinicopathological and immunohistochemical features, split PRCC into two subtypes: type 1 and type 2 [5]. There are few studies on the microenvironment of papillary renal cell carcinoma (PRCC). Our study aims to explore prognostic genes related to tumor microenvironment in PRCC
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