Journal
PEERJ
Volume 8, Issue -, Pages -Publisher
PEERJ INC
DOI: 10.7717/peerj.10142
Keywords
Colon cancer; Stromal; Immune; TCGA; GEO; Prognosis
Categories
Funding
- Health and Family planning Commission of Zhejiang Province [2020KY1045]
- Taizhou Science and Technology Bureau in Zhejiang Province [1901ky62]
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Background. Colon cancer is one of the deadliest tumors worldwide. Stromal cells and immune cells play important roles in cancer biology and microenvironment across different types of cancer. This study aimed to identify the prognostic value of stromal/immune cell-associated genes for colon cancer in The Cancer Genome Atlas (TCGA) database using bioinformatic technology. Methods. The gene expression data and corresponding clinical information of colon cancer were downloaded from TCGA database. Stromal and immune scores were estimated based on the ESTIMATE algorithm. Sanger software was used to identify the differentially expressed genes (DEGs) and prognostic DEGs based on stromal and immune scores. External validation of prognostic biomarkers was conducted in Gene Expression Omnibus (GEO) database. Gene ontology (GO) analysis, pathway enrichment analysis, and gene set enrichment analysis (GSEA) were used for functional analysis. STRING and Cytoscape were used to assess the protein-protein interaction (PPI) network and screen hub genes. Quantitative real-time PCR (qRT-PCR) was used to validate the expression of hub genes in clinical tissues. Synaptosomal-associated protein 25 (SNAP25) was selected for analyzing its correlations with tumor-immune system in the TISIDB database. Results. Worse overall survivals of colon cancer patients were found in high stromal score group (2963 vs. 1930 days, log-rank test P D0:038) and high immune score group (2894 vs. 2230 days, log-rank test P D0:076). 563 up-regulated and 9 down-regulated genes were identified as stromal-immune score-related DEGs. 70 up-regulated DEGs associated with poor outcomes were identified by COX proportional hazard regression model, and 15 hub genes were selected later. Then, we verified aquaporin 4 (AQP4) and SNAP25 as prognostic biomarkers in GEO database. qRT-PCR results revealed that AQP4 and SNAP25 were significantly elevated in colon cancer tissues compared with adjacent normal tissues (P D0:003, 0.001). GSEA and TISIDB suggested that SNAP25 involved in cancer-related signaling pathway, immunity and metabolism progresses. Conclusion. SNAP25 is a microenvironment-related and immune-related gene that can predict poor outcomes in colon cancer.
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