# Identification of Paraptosis-Related Renal Cell Carcinoma Subtypes, Construction of a Prognostic Signature, and Determination of Tumor Microenvironment Landscape Using Bioinformatic Analysis and Experimental Verification

## TL;DR

This study identifies two subtypes of kidney cancer based on paraptosis-related genes and develops a four-gene signature to predict patient survival and guide treatment.

## Contribution

A novel four-gene prognostic signature and two RCC subtypes linked to paraptosis are identified, offering insights into tumor microenvironment and treatment response.

## Key findings

- A four-gene (COL7A1, RNASE2, SLC10A2, APOLD1) signature accurately predicts survival in renal cell carcinoma patients.
- Low-risk patients show enriched immune/stromal infiltration, while high-risk patients have elevated cancer stem cell content and tumor mutation burden.
- COL7A1 is upregulated in RCC cell lines and may serve as a potential therapeutic target.

## Abstract

Renal cell carcinoma (RCC) is a common and deadly urological cancer, for which there are no robust prognostic biomarkers or personalized treatment strategies. Paraptosis, a distinct form of regulated cell death marked by cytoplasmic vacuolization, is being increasingly recognized for its roles in tumorigenesis and therapy responses, yet its functional implications in RCC remain poorly defined. Transcriptomic profiles and corresponding clinical metadata from the TCGA-KIRC and GSE33371 datasets were systematically analyzed to characterize the paraptosis-related gene (PaRG) expression profile in renal cell carcinoma (RCC). Patients were categorized into two subtypes via consensus clustering, 574 overlapping differentially expressed genes (DEGs) were identified, and a four-gene (COL7A1, RNASE2, SLC10A2, and APOLD1) prognostic signature was constructed using LASSO and multivariate Cox regression. We analyzed the signature’s associations with tumor microenvironment (TME) features, cancer stem cell (CSC) indices, and tumor mutation burden (TMB), and validated the expression of the signature genes in RCC cell lines via qRT-PCR and Western blot. The four-gene signature showed robust prognostic performance (1-, 3-, and 5-year AUC: 0.751, 0.735, and 0.733 in the total cohort; 0.735, 0.731, and 0.767 in the training cohort), with high-risk patients having significantly poorer overall survival than the low-risk group. The low-risk group exhibited higher Stromal, Immune, and ESTIMATE scores (enriched immune/stromal infiltration), while the high-risk group had elevated CSC content and TMB, and the signature correlated with differential sensitivity to multiple chemotherapeutics. Both qRT-PCR and Western blot confirmed upregulation of COL7A1 and RNASE2 and downregulation of SLC10A2 and APOLD1 in RCC cell lines. Our study establishes a paraptosis-based two-subtype classification and four-gene prognostic signature for RCC that can reliably predicting patient survival, delineate TME characteristics, and guide personalized therapy, with COL7A1 emerging as a potential therapeutic target for advancing our understanding of paraptosis in RCC pathogenesis and optimizing treatment.