Prognostic Model for Lung Adenocarcinoma Based on Aging-Related Genes
Author Information
Author(s): Wang Jin, Zhang Hailong, Feng Yaohui, Gong Xian, Song Xiangrong, Wei Meidan, Hu Yaoyu, Li Jianxiang, Peña Cristina
Primary Institution: Department of Toxicology, School of Public Health, Suzhou Medicine College of Soochow University, Suzhou, China
Hypothesis
Can a model based on aging-related genes improve the prediction and treatment strategies for lung adenocarcinoma?
Conclusion
The study developed a prognostic model that effectively predicts outcomes for lung adenocarcinoma patients using aging-related genes.
Supporting Evidence
- The model achieved AUC values greater than 0.8 for one-year survival in both internal and external validation cohorts.
- Higher risk scores correlated with a more tumor-promoting microenvironment and increased immune suppression.
- XRCC6 was found to be upregulated in lung adenocarcinoma and its knockdown reduced cell proliferation.
Takeaway
Researchers created a new tool to help doctors predict how lung cancer will progress based on genes related to aging.
Methodology
The model was developed using datasets from TCGA and GEO, integrating 14 aging-related genes through LASSO and Cox regression analyses.
Participant Demographics
The study included 504 lung adenocarcinoma patients, with 183 alive and 321 deceased by the end of the follow-up period.
Statistical Information
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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