Characterization of Glycometabolism and Tumor Immune Microenvironment for Predicting Clinical Outcomes and Therapeutic Responses in Gastric Cancer

Abstract

Background: The role of reprogramming of energy metabolism in the progression of gastric cancer remains largely uncharacterized. In this study, multi-omics data of 2471 gastric cancer sample were used to identify tumor glycometabolism and its correlation with tumor immune microenvironment.

Method: Multi-omics data of gastric cancer were used to identify tumor glycometabolism and its correlation with tumor immune microenvironment. A series of bioinformatic approaches were performed to establish a scoring system to predict survival and response of chemotherapy and immunotherapy.

Findings: Three glycometabolic subtypes and two immune clustering subgroups of gastric cancer were determined. Activated metabolism of glucose was correlated with high infiltration of anti-tumor effector cells. Patients in the activated subtype of glycometabolism and immune activated clustering subgroup exhibited superior prognosis. However, patients with poor infiltration of anti-tumor effector cells showed better treatment response for adjuvant chemotherapy. We further established a Gluco-Immune Scoring system to quantify the cancer glycometabolic status and immune infiltration of individual patients. We found Gluco-Immune Score was an independent prognostic factor. Patients with low Gluco-Immune Score were sensitive to adjuvant chemotherapy, while patients with high Gluco-Immune Score may benefit from immunotherapy.

Interpretation: In conclusion, our results indicate that in gastric cancer, the assessment of tumor glucose metabolism and immune microenvironment has application value for the prediction of curative effect and the formulation of combined treatment strategies.

Funding Information: This study was funded by the joint fund for key projects of National Natural Science Foundation of China (U20A20371), the National High Technology Research and Development Program of China (863 Program, No. 2014AA020603), “Double First Class” disciplinary development Foundation of Peking University (BMU2019LCKXJ011), the National Natural Science Foundation of China (Nos. 81872502, 81802471, 81972758), the Science Foundation of Peking University Cancer Hospital (2020-6, 2020-22).

Declaration of Interests: The authors declare that they have no competing interests.

Ethics Approval Statement: The gene expression microarray data of four gastric cancer cohorts were obtained from the Gene Expression Omnibus (GEO) database (https://www.ncbi.n lm.nih.gov/geo/) under accession numbers GSE15459, GSE34942, GSE57303 and GSE62254/ACRG. The transcriptomic data of Samsung Medical Center cohort were downloaded from the European Nucleotide Archive under accession number PRJEB25780 (https://www.ebi.ac.uk/ena/browser/view/PRJEB25780). The RNA sequencing data and detailed clinicopathologic information of IMvigor210 cohort were downloaded based on the Creative Commons 3.0 license from http://research-pub.gene.com/IMvigor210CoreBiologies.

Keywords: Glucose metabolism, Tumor microenvironment, Gastric cancer, Chemotherapy, Immunotherapy