Gut Microbiota Functional Biomakers For Prognostic Compound Score In Epstein-barr Virus Associated Gastric Adenocarcinoma

Epstein-Barr virus-associated gastric cancer(EBVaGC)is a common subtype of gastric cancer,and the composition of EBVaGC in gastric cancer patients is about 10%.There is increasing evidence that the gut microbiota of patients with digestive tract tumors is closely related to the prognosis of patients.Our goal is to establish a gut microbial-tumor cell based on patients with gastric adenocarcinoma classified as EBV infection.Functional-Clinical Prognosis is characterized by a prognostic model for the expression of tumor cell-associated immune microenvironment and lipid metabolism function markers from the gut microbiota function.We collected 10 cases(EBVaGC=4,EBVnGC=6)of fresh fecal samples between tumor resection and chemotherapy interval and analyzed their intestinal flora by 16 S rRNA sequencing.Formalin fixed paraffin-embedded(FFPE)tissue microarray was collected from540 patients with gastric adenocarcinoma.Immunohistochemistry was used to detect the expression of marker proteins in the above-mentioned flora affecting host differential function.The machine learning model was established to screen highly accurate marker proteins using the LASSO(Least absolute shrinkage and selection operator)-Cox regression.The results of the screening were used to construct a predictive score for the prognosis of patients using LASSO-Logistic regression.A model of composite scoring.The EBV-infected gastric cancer cell line was constructed,and the differentially expressed genes of EBV-positive gastric cancer cell line and EBV-negative gastric cancer cell line were analyzed by RNA-seq sequencing,and the gene function of EBV-positive gastric cancer cell line was predicted and enriched.Western blotting was used to detect the expression of related proteins in EBV positive gastric cancer cell lines and EBV negative gastric cancer cell lines.The cell migration function of gastric cancer cell lines was detected by scratch test.16S RNA sequencing revealed an increase in Bacteroides in the intestinal flora of patients with EBVaGC,a decrease in Prevotella 9 genus.In level of family with increase in Lachnospiraceae,Bacteroidaceae and Ruminococcaceae,and a decrease in the family of Prevotellaceae.The Tax4 Fun analysis based on the Kyoto Encyclopedia of Genes and Genomes(KEGG)data indicates that there are differentially expressed tumor pathways between EBVnGC and EBVaGC,including lipid metabolism,environmental information processing,cellular processes,and biological systems.In the transcriptome analysis of gastric cancer cell lines,the cytokine signaling pathway was activated in EBV-positive gastric cancer cell lines,and CXCL12 was up-regulated.Western blotting of cell lines and immunohistochemistry of tissue microarrays suggest that CXCL12 has the same relationship with ACOT1 and GLI3 protein expression,CXCL12 may have Hedgehog signaling pathway,and gastricadenocarcinoma with high expression of ACOT1 and GLI3 may indicate prognosis.worse.The LASSO-Cox model screened the significant markers of 14 immune microenvironments and lipid metabolism proteins.A composite scoring model consisting of 8 marker proteins was established using the LASSO-Logistic model.There were significant differences in survival rates between the high and low compound score in the full-case,EBVaGC subgroup and EBVnGC subgroups in the training set(378 patients).multivariate regression analysis showed that composite score was an independent prognostic factor(OR=2.26,95% CI2.28-3.36).The prognostic value of the composite score was also confirmed in the validation(162 patients)and the entire(540 patients)group.Our study shows that composite scoring is a biomarker that is important for assessing the survival rate of patients with gastric cancer with EBVaGC and EBVnGC.Our study indicates that differences in gut microbial expression between EBVaGC and EBVnGC patients,and the biological effects of immune and lipid metabolism in host patients are factors that influence patient prognosis.Prognostic models based on immunological and lipid metabolism biomarkers play an important role in prognosis prediction...