Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores

Background Colorectal cancer (CRC) is one of the most common malignancies.An early diagnosis and an accurate prognosis are major focuses of CRC research. Tumor microenvironment cells and the extent of infiltrating immune and stromal cells contribute significantly to the tumor prognosis. Methods Immu...

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Autores principales:	Yi Zhu, Yuan Zhou, HongGang Jiang, ZhiHeng Chen, BoHao Lu
Formato:	article
Lenguaje:	EN
Publicado:	PeerJ Inc. 2021
Materias:	Prognosis Tumor micro-environment Immune scores Colorectal cancer Medicine R
Acceso en línea:	https://doaj.org/article/ae91c41497024c86aafa3e0b2722a114
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spelling	oai:doaj.org-article:ae91c41497024c86aafa3e0b2722a1142021-11-21T15:05:17ZAnalysis of core genes for colorectal cancer prognosis based on immune and stromal scores10.7717/peerj.124522167-8359https://doaj.org/article/ae91c41497024c86aafa3e0b2722a1142021-11-01T00:00:00Zhttps://peerj.com/articles/12452.pdfhttps://peerj.com/articles/12452/https://doaj.org/toc/2167-8359Background Colorectal cancer (CRC) is one of the most common malignancies.An early diagnosis and an accurate prognosis are major focuses of CRC research. Tumor microenvironment cells and the extent of infiltrating immune and stromal cells contribute significantly to the tumor prognosis. Methods Immune and stromal scores were calculated based on the ESTIMATE algorithm using the sample expression profile of the The Cancer Genome Atlas (TCGA) database. GSE102479 was used as the validation database. Differentially expressed genes whose expression was significantly associated with the prognosis of CRC patients were identified based on the immune matrix score. Survival analysis was conducted on the union of the differentially expressed genes. A protein–protein interaction (PPI) network was constructed using the STRING database to identify the closely connected modules. To conduct functional enrichment analysis of the relevant genes, GO and KEGG pathway analyses were performed with Cluster Profiler. Pivot analysis of the ncRNAs and TFs was performed by using the RAID2.0 database and TRRUST v2 database. TF-mRNA regulatory relationships were analyzed in the TRRUST V2 database. Hubgene targeting relationships were screened in the TargetScan, miRTarBase and miRDB databases. The SNV data of the hub genes were analyzed by using the R maftools package. A ROC curve was drawn based on the TCGA database. The proportion of immune cells was estimated using CIBERSORT and the LM22 feature matrix. Results The results showed that the matrix score was significantly correlated with colorectal cancer stage T. A total of 789 differentially expressed genes and 121 survival-related prognostic genes were identified. The PPI network showed that 22 core genes were related to the CRC prognosis. Furthermore, four ncRNAs that regulated the core prognosis genes, 11 TFs with regulatory effects on the core prognosis genes, and two drugs, quercetin and pseudoephedrine, that have regulatory effects on colorectal cancer were also identified. Conclusions We obtained a list of tumor microenvironment-related genes for CRC patients. These genes could be useful for determining the prognosis of CRC patients. To confirm the function of these genes, additional experiments are necessary.Yi ZhuYuan ZhouHongGang JiangZhiHeng ChenBoHao LuPeerJ Inc.articlePrognosisTumor micro-environmentImmune scoresColorectal cancerMedicineRENPeerJ, Vol 9, p e12452 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Prognosis Tumor micro-environment Immune scores Colorectal cancer Medicine R
spellingShingle	Prognosis Tumor micro-environment Immune scores Colorectal cancer Medicine R Yi Zhu Yuan Zhou HongGang Jiang ZhiHeng Chen BoHao Lu Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
description	Background Colorectal cancer (CRC) is one of the most common malignancies.An early diagnosis and an accurate prognosis are major focuses of CRC research. Tumor microenvironment cells and the extent of infiltrating immune and stromal cells contribute significantly to the tumor prognosis. Methods Immune and stromal scores were calculated based on the ESTIMATE algorithm using the sample expression profile of the The Cancer Genome Atlas (TCGA) database. GSE102479 was used as the validation database. Differentially expressed genes whose expression was significantly associated with the prognosis of CRC patients were identified based on the immune matrix score. Survival analysis was conducted on the union of the differentially expressed genes. A protein–protein interaction (PPI) network was constructed using the STRING database to identify the closely connected modules. To conduct functional enrichment analysis of the relevant genes, GO and KEGG pathway analyses were performed with Cluster Profiler. Pivot analysis of the ncRNAs and TFs was performed by using the RAID2.0 database and TRRUST v2 database. TF-mRNA regulatory relationships were analyzed in the TRRUST V2 database. Hubgene targeting relationships were screened in the TargetScan, miRTarBase and miRDB databases. The SNV data of the hub genes were analyzed by using the R maftools package. A ROC curve was drawn based on the TCGA database. The proportion of immune cells was estimated using CIBERSORT and the LM22 feature matrix. Results The results showed that the matrix score was significantly correlated with colorectal cancer stage T. A total of 789 differentially expressed genes and 121 survival-related prognostic genes were identified. The PPI network showed that 22 core genes were related to the CRC prognosis. Furthermore, four ncRNAs that regulated the core prognosis genes, 11 TFs with regulatory effects on the core prognosis genes, and two drugs, quercetin and pseudoephedrine, that have regulatory effects on colorectal cancer were also identified. Conclusions We obtained a list of tumor microenvironment-related genes for CRC patients. These genes could be useful for determining the prognosis of CRC patients. To confirm the function of these genes, additional experiments are necessary.
format	article
author	Yi Zhu Yuan Zhou HongGang Jiang ZhiHeng Chen BoHao Lu
author_facet	Yi Zhu Yuan Zhou HongGang Jiang ZhiHeng Chen BoHao Lu
author_sort	Yi Zhu
title	Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
title_short	Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
title_full	Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
title_fullStr	Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
title_full_unstemmed	Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
title_sort	analysis of core genes for colorectal cancer prognosis based on immune and stromal scores
publisher	PeerJ Inc.
publishDate	2021
url	https://doaj.org/article/ae91c41497024c86aafa3e0b2722a114
work_keys_str_mv	AT yizhu analysisofcoregenesforcolorectalcancerprognosisbasedonimmuneandstromalscores AT yuanzhou analysisofcoregenesforcolorectalcancerprognosisbasedonimmuneandstromalscores AT honggangjiang analysisofcoregenesforcolorectalcancerprognosisbasedonimmuneandstromalscores AT zhihengchen analysisofcoregenesforcolorectalcancerprognosisbasedonimmuneandstromalscores AT bohaolu analysisofcoregenesforcolorectalcancerprognosisbasedonimmuneandstromalscores
_version_	1718418846556094464

Analysis of core genes for colorectal cancer prognosis based on immune and stromal scores

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