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Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score

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 i...

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Autores principales: Zou, Jinyan, Duan, Darong, Yu, Changfa, Pan, Jie, Xia, Jinwei, Yang, Zaixing, Cai, Shasha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583623/
https://www.ncbi.nlm.nih.gov/pubmed/33150073
http://dx.doi.org/10.7717/peerj.10142
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author Zou, Jinyan
Duan, Darong
Yu, Changfa
Pan, Jie
Xia, Jinwei
Yang, Zaixing
Cai, Shasha
author_facet Zou, Jinyan
Duan, Darong
Yu, Changfa
Pan, Jie
Xia, Jinwei
Yang, Zaixing
Cai, Shasha
author_sort Zou, Jinyan
collection PubMed
description 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 = 0.038) and high immune score group (2894 vs. 2230 days, log-rank test P = 0.076). 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 = 0.003, 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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spelling pubmed-75836232020-11-03 Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score Zou, Jinyan Duan, Darong Yu, Changfa Pan, Jie Xia, Jinwei Yang, Zaixing Cai, Shasha PeerJ Bioinformatics 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 = 0.038) and high immune score group (2894 vs. 2230 days, log-rank test P = 0.076). 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 = 0.003, 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. PeerJ Inc. 2020-10-20 /pmc/articles/PMC7583623/ /pubmed/33150073 http://dx.doi.org/10.7717/peerj.10142 Text en ©2020 Zou et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Zou, Jinyan
Duan, Darong
Yu, Changfa
Pan, Jie
Xia, Jinwei
Yang, Zaixing
Cai, Shasha
Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score
title Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score
title_full Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score
title_fullStr Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score
title_full_unstemmed Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score
title_short Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score
title_sort mining the potential prognostic value of synaptosomal-associated protein 25 (snap25) in colon cancer based on stromal-immune score
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583623/
https://www.ncbi.nlm.nih.gov/pubmed/33150073
http://dx.doi.org/10.7717/peerj.10142
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