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Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes
BACKGROUND: Accumulating evidence suggests that microRNA-target genes are closely related to tumorigenesis and progression. This study aims to screen the intersection of differentially expressed mRNAs (DEmRNAs) and the target genes of differentially expressed microRNAs (DEmiRNAs), and to construct a...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248560/ https://www.ncbi.nlm.nih.gov/pubmed/37304542 http://dx.doi.org/10.21037/tcr-22-2588 |
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author | Gu, Bingbing Zhang, Shuai Fan, Zhe Che, Jiajing Li, Shuting Li, Yunfei Pan, Keyu Lv, Jiali Wang, Cheng Zhang, Tao Wang, Jialin |
author_facet | Gu, Bingbing Zhang, Shuai Fan, Zhe Che, Jiajing Li, Shuting Li, Yunfei Pan, Keyu Lv, Jiali Wang, Cheng Zhang, Tao Wang, Jialin |
author_sort | Gu, Bingbing |
collection | PubMed |
description | BACKGROUND: Accumulating evidence suggests that microRNA-target genes are closely related to tumorigenesis and progression. This study aims to screen the intersection of differentially expressed mRNAs (DEmRNAs) and the target genes of differentially expressed microRNAs (DEmiRNAs), and to construct a prognostic gene model of esophageal cancer (EC). METHODS: Gene expression, microRNA expression, somatic mutation, and clinical information data of EC from The Cancer Genome Atlas (TCGA) database were used. The intersection of DEmRNAs and the target genes of DEmiRNAs predicted by the Targetscan database and microRNA Data Integration Portal (mirDIP) database were screened. The screened genes were used to construct a prognostic model of EC. Then, the molecular and immune signatures of these genes were explored. Finally, the GSE53625 dataset from the Gene Expression Omnibus (GEO) database was further used as a validation cohort to confirm the prognostic value of the genes. RESULTS: Six genes on the grounds of the intersection of DEmiRNAs target genes and DEmRNAs were identified as prognostic genes, including ARHGAP11A, H1.4, HMGB3, LRIG1, PRR11, and COL4A1. Based on the median risk score calculated for these genes, EC patients were divided into a high-risk group (n=72) and a low-risk group (n=72). Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001). The nomogram evaluation showed high reliability in predicting the 1-year, 2-year, and 3-year survival probability of EC patients. Compared to low-risk group, higher expression level of M2 macrophages was found in high-risk group of EC patient (P<0.05), while STAT3 checkpoints showed attenuated expression level in high-risk group. CONCLUSIONS: A panel of differential genes was identified as potential EC prognostic biomarkers and showed great clinical significance in EC prognosis. |
format | Online Article Text |
id | pubmed-10248560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-102485602023-06-09 Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes Gu, Bingbing Zhang, Shuai Fan, Zhe Che, Jiajing Li, Shuting Li, Yunfei Pan, Keyu Lv, Jiali Wang, Cheng Zhang, Tao Wang, Jialin Transl Cancer Res Original Article BACKGROUND: Accumulating evidence suggests that microRNA-target genes are closely related to tumorigenesis and progression. This study aims to screen the intersection of differentially expressed mRNAs (DEmRNAs) and the target genes of differentially expressed microRNAs (DEmiRNAs), and to construct a prognostic gene model of esophageal cancer (EC). METHODS: Gene expression, microRNA expression, somatic mutation, and clinical information data of EC from The Cancer Genome Atlas (TCGA) database were used. The intersection of DEmRNAs and the target genes of DEmiRNAs predicted by the Targetscan database and microRNA Data Integration Portal (mirDIP) database were screened. The screened genes were used to construct a prognostic model of EC. Then, the molecular and immune signatures of these genes were explored. Finally, the GSE53625 dataset from the Gene Expression Omnibus (GEO) database was further used as a validation cohort to confirm the prognostic value of the genes. RESULTS: Six genes on the grounds of the intersection of DEmiRNAs target genes and DEmRNAs were identified as prognostic genes, including ARHGAP11A, H1.4, HMGB3, LRIG1, PRR11, and COL4A1. Based on the median risk score calculated for these genes, EC patients were divided into a high-risk group (n=72) and a low-risk group (n=72). Survival analysis showed that the high-risk group had a significantly shorter survival time than the low-risk group (TCGA and GEO, P<0.001). The nomogram evaluation showed high reliability in predicting the 1-year, 2-year, and 3-year survival probability of EC patients. Compared to low-risk group, higher expression level of M2 macrophages was found in high-risk group of EC patient (P<0.05), while STAT3 checkpoints showed attenuated expression level in high-risk group. CONCLUSIONS: A panel of differential genes was identified as potential EC prognostic biomarkers and showed great clinical significance in EC prognosis. AME Publishing Company 2023-04-13 2023-05-31 /pmc/articles/PMC10248560/ /pubmed/37304542 http://dx.doi.org/10.21037/tcr-22-2588 Text en 2023 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Gu, Bingbing Zhang, Shuai Fan, Zhe Che, Jiajing Li, Shuting Li, Yunfei Pan, Keyu Lv, Jiali Wang, Cheng Zhang, Tao Wang, Jialin Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes |
title | Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes |
title_full | Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes |
title_fullStr | Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes |
title_full_unstemmed | Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes |
title_short | Prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microRNA target genes |
title_sort | prognostic model construction and immune microenvironment analysis of esophageal cancer based on gene expression data and microrna target genes |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248560/ https://www.ncbi.nlm.nih.gov/pubmed/37304542 http://dx.doi.org/10.21037/tcr-22-2588 |
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