A PDCD4-Based Gene Expression Signature Predicts Overall Survival in Renal Cell Carcinoma: A TCGA-Based Discovery and External Validation Study

Renal cell carcinoma (RCC) is a heterogeneous disease with variable clinical outcomes. PDCD4 functions as a tumor suppressor, but its role in RCC prognosis remains unclear. We aimed to develop and validate a PDCD4-based gene expression signature for predicting overall survival in RCC. We analyzed RNA-seq data from 541 clear cell RCC patients in The Cancer Genome Atlas (TCGA-KIRC). We identified 100 genes (50 positively and 50 negatively correlated with PDCD4) to create a prognostic signature. Patients were stratified into high- and low-signature groups using median cutoff. Kaplan-Meier analysis and Cox regression models assessed prognostic value. External validation was performed in four independent cohorts: GSE29609, GSE73731, GSE53757, and GSE40435. Low PDCD4 signature scores were associated with significantly worse overall survival (HR = 2.17, 95% CI: 1.58-2.98, <i>p</i> < 0.001) and advanced tumor stage. The median survival difference was approximately 46 months. In multivariate analysis adjusting for age, gender, stage, and grade, the signature remained an independent prognostic factor (HR = 1.57, 95% CI: 1.11-2.22, <i>p</i> = 0.011). The signature demonstrated consistent prognostic patterns across platforms, with high signature scores associated with early-stage disease and low-grade tumors, and with potential clinical utility for risk stratification and treatment planning.

Authors

Institutions

Publication Details

Journal
Current Issues in Molecular Biology
Published
2025-12-25
DOI
https://doi.org/10.3390/cimb48010022
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A PDCD4-Based Gene Expression Signature Predicts Overall Survival in Renal Cell Carcinoma: A TCGA-Based Discovery and External Validation Study

Bandar A. Suliman
Current Issues in Molecular Biology
Ferroptosis and cancer prognosis
article

A PDCD4-Based Gene Expression Signature Predicts Overall Survival in Renal Cell Carcinoma: A TCGA-Based Discovery and External Validation Study

Bandar A. Suliman
article en

Abstract

Renal cell carcinoma (RCC) is a heterogeneous disease with variable clinical outcomes. PDCD4 functions as a tumor suppressor, but its role in RCC prognosis remains unclear. We aimed to develop and validate a PDCD4-based gene expression signature for predicting overall survival in RCC. We analyzed RNA-seq data from 541 clear cell RCC patients in The Cancer Genome Atlas (TCGA-KIRC). We identified 100 genes (50 positively and 50 negatively correlated with PDCD4) to create a prognostic signature. Patients were stratified into high- and low-signature groups using median cutoff. Kaplan-Meier analysis and Cox regression models assessed prognostic value. External validation was performed in four independent cohorts: GSE29609, GSE73731, GSE53757, and GSE40435. Low PDCD4 signature scores were associated with significantly worse overall survival (HR = 2.17, 95% CI: 1.58-2.98, <i>p</i> < 0.001) and advanced tumor stage. The median survival difference was approximately 46 months. In multivariate analysis adjusting for age, gender, stage, and grade, the signature remained an independent prognostic factor (HR = 1.57, 95% CI: 1.11-2.22, <i>p</i> = 0.011). The signature demonstrated consistent prognostic patterns across platforms, with high signature scores associated with early-stage disease and low-grade tumors, and with potential clinical utility for risk stratification and treatment planning.

Current Issues in Molecular BiologyVol. 48(1)
Taibah University (SA)
Good health and well-being
Openalex Percentile: Top 28%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.