Abstract Background: Genomic expression profiles have enabled the classification of lung adenocarcinoma (LUAD) into molecular sub-types and provide prognostic information, which have implications for the personalized treatment of LUAD beyond clinical and pathological features. Methods: Gene-expression profiling was performed on 459 patients in TCGA-LUAD(I-IIIa) for which RNA sequencing data and clinical covariates were available. A single-sample gene set enrichment analysis (ssGSEA) algorithm were used to quantified the levels of various hallmarks of cancer. And LASSO Cox regression model was used to screen robust prognostic biomarkers to identify the best set of survival-associated gene signatures in LUAD. Statistical analyses were performed using R version 3.4.4. Results: We identified glycolysis as the primary risk factor for survival(HR=0.55 [0.38-0.8], P<0.001)among various hallmarks of cancer in TCGA-LUAD. And glycolysis ssGESA scores were significantly elevated in patients who died during follow up (P<0.001). Kaplan-Meier analysis showed that patients with high ssGSEA scores of glycolysis exhibited worse OS ( HR=1.9,P= 0.001).Adjusted for stage,age,gender, our signature was an independent risk factor for overall survival in TCGA cohorts (HR=1.67[1.19-2.30],P= 0.003). We then apply the glycolysis -related gene signature to classify patients into the high risk group and the low risk group with the cutoff of median. In external independent cohorts, similar results were observed. In the validation cohort GEO31210, the multivariate Cox regression analysis showed that glycolysis -related gene signature exhibited an independent risk prediction for overall survival in 226 patients with stage I-II LUAD (HR=2.5 [1.11-5.5], P =0.025). Conclusions: By analyzing the gene-expression data with bioinformation approach, we developed and validated a risk prediction model with glycolysis -related expression scores in early stage LUAD, which have the potential to identify patients who could have better overall survival. Furthmore, our study confirmed that tumor glycolysis has wide-ranging effects, would become an attractive therapeutic target. Citation Format: Shengguang Wang, Zhang Bei. Development and validation of a glycolysis-related gene signature to predict overall survival in lung adenocarcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 664.