A novel model based on CD8+ T cell-related genes predicts prognosis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and exhibits poor prognosis in advanced and metastatic cases, highlighting the urgent need for reliable prognostic biomarkers. In this study, CD8+ T cells infiltration related genes were screened using least absolute shrinkage and selection operator (LASSO) regression, and a novel prognostic risk model for ccRCC was constructed. The differential expression of model genes was further analyzed, correlations of these genes with drug sensitivity were evaluated, and the association between risk score and immune checkpoint molecules was explored. The risk signature functioned as an independent prognostic indicator with moderate predictive performance (AUC = 0.705), and elevated risk scores corresponded to inferior survival outcomes. All model genes except ZBED2 were significantly overexpressed in ccRCC tumor tissues. Drug sensitivity analysis demonstrated that CD7 and TTC24 were strongly correlated with nelarabine sensitivity, whereas PDCD1 and RTP5 were highly associated with bendamustine response (Correlation > 0.6, p < 0.001). Moreover, the risk score was closely linked to multiple immune checkpoint markers. The risk model based on genes associated with CD8+ T cells infiltration is an independent prognostic factor for patients with ccRCC, providing new insights into the prognosis of this disease.

Authors

Institutions

Publication Details

Journal
Discover Oncology
Published
2026-09-13
DOI
https://doi.org/10.1007/s12672-026-05854-9
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A novel model based on CD8+ T cell-related genes predicts prognosis in clear cell renal cell carcinoma

Shuang Liu
Discover Oncology
Renal cell carcinoma treatment
article

A novel model based on CD8+ T cell-related genes predicts prognosis in clear cell renal cell carcinoma

Shuang Liu
article en

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and exhibits poor prognosis in advanced and metastatic cases, highlighting the urgent need for reliable prognostic biomarkers. In this study, CD8+ T cells infiltration related genes were screened using least absolute shrinkage and selection operator (LASSO) regression, and a novel prognostic risk model for ccRCC was constructed. The differential expression of model genes was further analyzed, correlations of these genes with drug sensitivity were evaluated, and the association between risk score and immune checkpoint molecules was explored. The risk signature functioned as an independent prognostic indicator with moderate predictive performance (AUC = 0.705), and elevated risk scores corresponded to inferior survival outcomes. All model genes except ZBED2 were significantly overexpressed in ccRCC tumor tissues. Drug sensitivity analysis demonstrated that CD7 and TTC24 were strongly correlated with nelarabine sensitivity, whereas PDCD1 and RTP5 were highly associated with bendamustine response (Correlation > 0.6, p < 0.001). Moreover, the risk score was closely linked to multiple immune checkpoint markers. The risk model based on genes associated with CD8+ T cells infiltration is an independent prognostic factor for patients with ccRCC, providing new insights into the prognosis of this disease.

Discover Oncology
Wuhan University (CN), China International Science and Technology Cooperation (CN), Renmin Hospital of Wuhan University (CN)
Good health and well-being
Openalex Percentile: Top 11%
Renal cell carcinoma treatment
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.