Objective: Increasing evidence has indicated an association between gut microbiota in gastrointestinal cancer and clinical outcome. Herein, we aim to develop a prognosis-prediction tool based on an immune-lipid metabolism signature, tumor cell-associated immune microenvironment, and lipid metabolism proteins inferred from the function of gut microbiota.
Methods: 16S gene ribosomal RNA sequencing was performed on 10 fecal samples obtained after tumor resection but before chemotherapy (EBVaGC = 4 and EBVnGC = 6). Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to screening for highly accurate marker proteins. A compound score based on the fraction of screened markers was then constructed using a LASSO logistic regression model.
Results: The Tax4Fun analysis based on Kyoto Encyclopedia of Genes and Genomes data indicated differentially expressed tumor pathway between EBVnGC and EBVaGC. Using the LASSO logistic model, a compound score was established consisting of 14 types of immune microenvironment and lipid metabolism proteins. In the training set (378 patients), significant differences were found between high- and low-compound score groups in overall survival across and within subpopulations with an identical EBV. Multivariable analysis revealed that the compound score was an independent prognostic factor (hazard ratio, 2.26; 95% confidence interval = 2.28-3.36). The prognostic value ;of the compound score was also confirmed in the validation (162 patients) and entire (540 patients) sets.
Discussion: The proposed compound score is a promising signature for estimating overall survival in patients with gastric cancer having EBVaGCs or EBVnGCs.