Abstract
Background:
Patients with early-stage lung adenocarcinoma (LUAD) exhibit significant heterogeneity in overall survival. The current tumour-node-metastasis staging system is insufficient to provide precise prediction for prognosis.
Methods:
We quantified the levels of various hallmarks of cancer and identified hypoxia as the primary risk factor for overall survival in early-stage LUAD. Different bioinformatic and statistical methods were combined to construct a robust hypoxia-related gene signature for prognosis. Furthermore, a decision tree and a nomogram were constructed based on the gene signature and clinicopathological features to improve risk stratification and quantify risk assessment for individual patients.
Results:
The hypoxia-related gene signature discriminated high-risk patients at an early stage in our investigated cohorts. Survival analyses demonstrated that our gene signature served as an independent risk factor for overall survival. The decision tree identified risk subgroups powerfully, and the nomogram exhibited high accuracy.
Conclusions:
Our study might contribute to the optimization of risk stratification for survival and personalized management of early-stage LUAD.
Keywords:
early-stage lung adenocarcinoma; gene signature; hypoxia; prognosis; therapeutic resistance.