Identification of DEGs in Regulatory T cells (Treg) with deficiency of IL23R
To identify the effects of IL23R on gastric cancer cells, we analyzed the RNA-seq data of Treg with the knockout of IL23R. A total of 402 genes were identified with a threshold of P < 0.05. The significantly changed genes were shown by the heatmap and volcano plot (Figure 1). The top ten differentially expressed genes (DEGs) were listed in Table 1.
Identification of KEGG and GO in Regulatory T cells (Treg) with deficiency of IL23R
To determine the mechanism of IL23R-regulated Treg, we performed the KEGG and GO enrichment (Figure 2). We identified the top ten KEGG items, including “Autophagy – animal”, “Yersinia infection”, “Neurotrophin signaling pathway”, “Measles”, “Hepatitis B”, “Small cell lung cancer”, “NF−kappa B signaling pathway”, “p53 signaling pathway”, “Prolactin signaling pathway”, and “Pertussis”. We then identified the top ten biological processes, including “autophagy”, “process utilizing autophagic mechanism”, “mRNA processing”, “positive regulation of catabolic process”, “DNA repair”, “RNA splicing”, “macroautophagy”, “DNA replication”, “DNA−dependent DNA replication”, and “autophagosome organization”. We then identified the top ten cellular components, including “nuclear speck”, “spindle”, “vacuolar membrane”, “cytoplasmic ribonucleoprotein granule”, “transferase complex, transferring phosphorus−containing groups”, “spliceosomal complex”, “mitotic spindle”, “lipid droplet”, “autophagosome”, and “aster”. We identified the top ten molecular functions, including “catalytic activity, acting on RNA”, “protein serine/threonine kinase activity”, “ubiquitin protein ligase binding”, “ubiquitin−like protein ligase binding”, “nucleotidyltransferase activity”, “protein serine kinase activity”, “helicase activity”, “protein phosphatase binding”, “phosphoprotein phosphatase activity”, and “protein tyrosine phosphatase activity”.
PPI network and Reactome analyses
To study the potential relationship among the DEGs, we created the PPI network. The combined score > 0.2 was set as a cutoff by using the Cytoscape software. Table 2 indicated the top ten genes with the highest degree scores. The top two significant modules were shown in Figure 3. We further analyzed the PPI and DEGs with a Reactome map (Figure 4) and identified the top ten biological processes including "Interleukin-2 signaling", "Interleukin-7 signaling", "FLT3 Signaling", "Death Receptor Signalling", "Signaling by phosphorylated juxtamembrane, extracellular and kinase domain KIT mutants", "Signaling by KIT in disease", "Ovarian tumor domain proteases", "Cell death signalling via NRAGE, NRIF and NADE", "Growth hormone receptor signaling", and "SHC-related events triggered by IGF1R" (Supplemental Table S1).