Abstract
Background: Esophageal cancer is one of the most leading and lethal malignancies. Glycolysis and the tumor microenvironment (TME) are responsible for cancer progressions. We aimed to study the relationships between glycolysis, TME, and therapeutic response in esophageal adenocarcinoma (EAC). Materials and Methods: We used the ESTIMATE algorithm to divide EAC patients into ESTIMATE (high) and ESTIMATE (low) groups based on the gene expression data downloaded from TCGA. Weighted gene co-expression network analysis (WGCNA) and Gene Set Enrichment Analysis (GSEA) were performed to identify different glycolytic genes in the TME between the two groups. The prognostic gene signature for overall survival (OS) was established through Cox regression analysis. Impacts of glycolytic genes on immune cells were assessed and validated. Next, we conducted the glycolytic gene mutation analysis and drug therapeutic response analysis between the two groups. Finally, the GEO database was employed to validate the impact of glycolysis on TME in patients with EAC. Results: A total of 78 EAC patients with gene expression profiles and clinical information were included for analysis. Functional enrichment results showed that the genes between ESTIMATE (high) and ESTIMATE (low) groups (N = 39, respectively) were strongly related with glycolytic and ATP/ADP metabolic pathways. Patients in the low-risk group had probabilities to survive longer than those in the high-risk group (p < 0.001). Glycolytic genes had significant impacts on the components of immune cells in TME, especially on the T-cells and dendritic cells. In the high-risk group, the most common mutant genes were TP53 and TTN, and the most frequent mutation type was missense mutation. Glycolysis significantly influenced drug sensitivity, and high tumor mutation burden (TMB) was associated with better immunotherapeutic response. GEO results confirmed that glycolysis had significant impacts on immune cell contents in TME. Conclusion: We performed a comprehensive study of glycolysis and TME and demonstrated that glycolysis could influence the microenvironment and drug therapeutic response in EAC. Evaluation of the glycolysis pattern could help identify the individualized therapeutic regime.