Abstract 872: Development of a nomogram and prognostic model based on immune-related genes in kidney renal papillary cell carcinoma

Abstract

Abstract Background: Kidney renal papillary cell carcinoma (KIRP) is frequently associated with an unfavorable prognosis for affected individuals. Unfortunately, there has been insufficient exploration in search for a reliable prognosis signature and predictive indicators to forecast outcomes for KIRP patients. Thus, we have used bioinformatics of existing transcriptomic and health data to identify survival-related and prognostic immune genes. Methods: Processed RNA-seq FPKM data of 289 KIRP and 32 adjacent normal KIRP tissues were downloaded from the TCGA data portal. We downloaded 2499 immune-related genes via the Immunology Database and Analysis portal database and used the Cistrome database to identify and extract 318 total transcription factors (TFs). The differentially expressed immune-related genes and TFs were detected using the Wilcoxon test method. R was used to generate heatmaps and volcano plots. R was also used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Multivariate Cox regression analysis was implemented to investigate the prognostic value of differentially expressed immune-related genes used to construct the predictive model and nomogram. Kaplan-Meier analysis was performed to compare overall survival. We used Tumor Immune Estimation Resource (TIMER) and the Human Protein Atlas database (HPA) to validate expression and explore associations between a prognostic model and immune cell infiltration. Statistical analyses were performed using R; a p-value < 0.05 was considered to be significant. Results: A total of 368 immune-related genes and 60 TFs were identified as differentially expressed in KIRP tissues compared with normal tissues. Of the 368, 23 were found to be related to overall survival. GO and KEGG analysis suggested that these prognostic immune-related genes mainly participated in the ERK1 and ERK2 cascades, Rap1 signaling pathway, and the PI3K-Akt signaling pathway - pathways shown to be significantly correlated with the development of cancer. Of these 23 genes, 9 (GRN, PDGFRB, APOH, BIRC5, CCL19, RETN, HTR3A, PTGER1, TRAV39) were identified from Cox regression to be statistically significant prognostic-related genes. Survival analysis showed that a model based on these 9 prognostic-related genes has high predictive performance. Our constructed nomogram has good predictive power and clinical practicability. Immunohistochemistry results show that APOH, BIRC5, CCL19 and GRN were significantly increased in kidney cancer. B cells and CD4+ T cells were positively correlated with risk score model. Conclusion: We were able to create a prognostic model based on 9 immune-related genes correlated with overall survival in KIRP. We hope that this work helps to provide some insight into therapeutic approaches and prognostic predictors of KIRP. Citation Format: Adrian Lim, Mouad Edderkaoui, Yi Zhang, Stephen J. Pandol, Yan Ou. Development of a nomogram and prognostic model based on immune-related genes in kidney renal papillary cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 872.