CXCR4 negatively correlates with NKT cell infiltration during gastric precancerous lesions progression to early gastric cancer
Authors: Jiang Xiaotao , Zhuang Kunhai , Jiang Kailin , Wen Yi , Xie Linling , Senhui Weng , Xu Chen , Nie Kechao , Zheng Zhihua , Pan Jinglin , Yan Yanhua , Liu Peng , Zheng Junhui , Huang Yuancheng , Liu Yufeng , Li Peiwu , Liu Fengbin 
Published: September 2020

Background: With the coming of immunotherapy era, immunotherapy is gradually playing a vital role in the treatment of gastric cancer (GC). However, immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. Methods: From the Gene Expression Omnibus (GEO), data of three GPL-related gene expression profiles (GSE55696, GSE87666 and GSE130823) and three GC data sets with clinical information (GSE66229, GSE15459 and GSE34942) were downloaded. Three GC data were consolidated as a GC meta-GEO cohort. RNA sequencing data of 375 stomach adenocarcinoma (STAD) samples with clinical information from The Cancer Genome Atlas (TCGA) and 175 stomach normal controls (NC) from Genotype-Tissue Expression (GTEx) datasets were obtained from the UCSC Xena browser, which were merged as a STAD TCGA-GTEx cohort. The abundance of immune cells in above datasets were estimated using Immune Cell Abundance Identifier (ImmuCellAI) algorithm. Firstly, key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test as well as Spearman’s correlation test in two GPL and EGC related datasets (GSE55696 and GSE87666). Then, weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network. Candidate hub genes were identified based on network parameters. Combining expression comparison and prognosis analysis in STAD TCGA-GTEx and GC meta-GEO cohort, Genes with significant difference between GC and NC and prognostic significance were identified as real hub genes. Correlation between real hub genes and key immune cells was evaluated using Pearson’s correlation test. The pattern of key immune cells infiltration and hub genes expression as well as their correlation during GPL progression to EGC were validated in an independent cohort GSE130823. The correlation was also verified in the GC datasets (STAD TCGA-GTEx and GC meta-GEO cohort).Results: Combining with GSE55696 and GSE87666 cohorts, NKT cell was found gradually decreased with GPL progression and negatively correlated with tumorigenesis significantly. It was identified as the key immune cell associated with GPL progression to EGC based on one-way ANOVA test and Spearman’s correlation test. Further verification indicated that it was significantly downregulated in GC in meta-GEO cohort and STAD TCGA-GTEx cohort. According to the results of WGCNA and KEGG pathway enrichment, green modules in GSE55696 and GSE87666 cohorts were considered as hub modules as they were negatively associated with NKT cell infiltration at a significant level and their overlapping genes were significantly enriched in immune-related pathways. In further screening, CXCR4 was found to be significantly upregulated in GC and had a poor prognosis, which was determined as the real hub gene. CXCR4 expression was found increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly. The pattern of NKT cell infiltration and CXCR4 expression as well as their relationship stay consistent in the independent GPL cohort GSE130823. The negative correlation of CXCR4 with NKT cell infiltration was also confirmed in GC datasets (GC meta-GEO cohort and STAD TCGA-GTEx cohort).Conclusion: CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.