DataSheet1.xlsx

Abstract

Background Esophageal cancer is one of the most leading and lethal malignancies. Glycolysis and 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 TME between the two groups. Prognostic genes signature for overall survival (OS) was established through cox 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, GEO database was employed to validate the impact of glycolysis on TME in EAC patients with EAC. Results Seventy-eight EAC patients with gene expression profiles and clinical information were included for analysis. Functional enrichment results showed 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 mutation mutant genes were TP53, TTN, and the most frequent mutation type was missense mutation. Glycolysis significantly influenced the drug sensitivity, and high tumor mutation burden (TMB) was associated with better immunotherapeutic response. GEO results confirmed the glycolysis had significant impacts on immune cells contents in TME. Conclusions We performed a comprehensive study of glycolysis and TME, and demonstrated glycolysis could influence microenvironment and drug therapeutic response in EAC. Evaluation of glycolysis pattern could help to identify individualized therapeutic regime.