Unveiling a dual-pathway prognostic model: Integrating T cell-related and ubiquitination-related genes in lung adenocarcinoma
- 1Department of Respiratory and Critical Care Medicine, The Second Hospital of Lanzhou University, Lanzhou, Gansu 730000, P.R. China
- 2The Second Clinical Medical School, Lanzhou University, Lanzhou, Gansu 730000, P.R. China
Abstract
The prognosis of lung adenocarcinoma (LUAD) is closely associated with T-cell function and ubiquitination; however, the underlying mechanisms have remained elusive. Therefore, there is an urgent need to identify robust prognostic biomarkers. Using The Cancer Genome Atlas (n=515) and the Gene Expression Omnibus Series GSE31210 (n=226) datasets, an integrated differential expression analysis, weighted gene co-expression network analysis, Cox regression and least absolute shrinkage and selection operator regression were performed to identify a prognostic signature. Based on an eight-gene risk model, patients were stratified into high-risk and low-risk groups. The model was subsequently evaluated through immune infiltration analysis, drug sensitivity assessment and reverse transcription-quantitative PCR (RT-qPCR) validation. Although the RT-qPCR validation cohort was relatively small (n=20), limiting statistical power, the observed expression trends were consistent with the bioinformatics findings. An eight-gene signature comprising RNF180, MAP3K3, TRIM2, RNF125, RWDD3, RNF144B, KCTD5 and TRIM27 was identified. In the training cohort, the risk model achieved area under the curve values of >0.6 for 1-, 3- and 5-year survival and was successfully validated in the independent GSE31210 cohort. A nomogram incorporating the risk score and M stage showed potential clinical utility within a limited threshold probability range. The high-risk group exhibited distinct immune infiltration patterns and significantly higher Tumour Immune Dysfunction and Exclusion scores. Drug sensitivity analysis identified 125 agents, including axitinib, with significantly different half-maximal inhibitory concentration (IC50) values between the two risk groups. Specifically, high-risk patients exhibited higher IC50 values for certain drugs, indicating lower sensitivity, whereas low-risk patients were more likely to respond to these agents. RT-qPCR analysis of an expanded cohort of 20 paired LUAD and adjacent normal tissues confirmed the differential expression of five key genes: KCTD5, MAP3K3, RNF144B, TRIM2 and TRIM27. In conclusion, this novel prognostic model integrating T cell-related and ubiquitination-related genes provides a potential tool for risk stratification and personalized treatment in LUAD. It may also help clinicians identify high-risk patients who could benefit from closer follow-up or targeted therapeutic strategies.
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BibTeX
@article{zeng2026unveiling,
title = {{Unveiling a dual-pathway prognostic model: Integrating T cell-related and ubiquitination-related genes in lung adenocarcinoma}},
author = {Shuang Zeng and Huidi Gao and Hongying Liang and Degang Zhang},
journal = {Oncology Letters},
year = {2026},
month = oct,
doi = {10.3892/ol.2026.15905},
url = {https://doi.org/10.3892/ol.2026.15905},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Unveiling a dual-pathway prognostic model: Integrating T cell-related and ubiquitination-related genes in lung adenocarcinoma
AU - Shuang Zeng
AU - Huidi Gao
AU - Hongying Liang
AU - Degang Zhang
PY - 2026
DA - 2026/10/13
JO - Oncology Letters
DO - 10.3892/ol.2026.15905
UR - https://doi.org/10.3892/ol.2026.15905
AB - The prognosis of lung adenocarcinoma (LUAD) is closely associated with T-cell function and ubiquitination; however, the underlying mechanisms have remained elusive. Therefore, there is an urgent need to identify robust prognostic biomarkers. Using The Cancer Genome Atlas (n=515) and the Gene Expression Omnibus Series GSE31210 (n=226) datasets, an integrated differential expression analysis, weighted gene co-expression network analysis, Cox regression and least absolute shrinkage and selection operator regression were performed to identify a prognostic signature. Based on an eight-gene risk model, patients were stratified into high-risk and low-risk groups. The model was subsequently evaluated through immune infiltration analysis, drug sensitivity assessment and reverse transcription-quantitative PCR (RT-qPCR) validation. Although the RT-qPCR validation cohort was relatively small (n=20), limiting statistical power, the observed expression trends were consistent with the bioinformatics findings. An eight-gene signature comprising RNF180, MAP3K3, TRIM2, RNF125, RWDD3, RNF144B, KCTD5 and TRIM27 was identified. In the training cohort, the risk model achieved area under the curve values of >0.6 for 1-, 3- and 5-year survival and was successfully validated in the independent GSE31210 cohort. A nomogram incorporating the risk score and M stage showed potential clinical utility within a limited threshold probability range. The high-risk group exhibited distinct immune infiltration patterns and significantly higher Tumour Immune Dysfunction and Exclusion scores. Drug sensitivity analysis identified 125 agents, including axitinib, with significantly different half-maximal inhibitory concentration (IC50) values between the two risk groups. Specifically, high-risk patients exhibited higher IC50 values for certain drugs, indicating lower sensitivity, whereas low-risk patients were more likely to respond to these agents. RT-qPCR analysis of an expanded cohort of 20 paired LUAD and adjacent normal tissues confirmed the differential expression of five key genes: KCTD5, MAP3K3, RNF144B, TRIM2 and TRIM27. In conclusion, this novel prognostic model integrating T cell-related and ubiquitination-related genes provides a potential tool for risk stratification and personalized treatment in LUAD. It may also help clinicians identify high-risk patients who could benefit from closer follow-up or targeted therapeutic strategies.
SN - 1792-1074
SN - 1792-1082
ER -