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Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma
Background: The immune system plays a crucial role in rectal adenocarcinoma (READ). Immune-related genes may help predict READ prognoses. Methods: The Cancer Genome Atlas dataset and GSE56699 were used as the training and validation datasets, respectively, and differentially expressed genes (DEGs) w...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159392/ https://www.ncbi.nlm.nih.gov/pubmed/35664306 http://dx.doi.org/10.3389/fgene.2022.880945 |
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author | Jiang, Linlin Wang, Peng Su, Mu Yang, Lili Wang, Qingbo |
author_facet | Jiang, Linlin Wang, Peng Su, Mu Yang, Lili Wang, Qingbo |
author_sort | Jiang, Linlin |
collection | PubMed |
description | Background: The immune system plays a crucial role in rectal adenocarcinoma (READ). Immune-related genes may help predict READ prognoses. Methods: The Cancer Genome Atlas dataset and GSE56699 were used as the training and validation datasets, respectively, and differentially expressed genes (DEGs) were identified. The optimal DEG combination was determined, and the prognostic risk model was constructed. The correlation between optimal DEGs and immune infiltrating cells was evaluated. Results: Nine DEGs were selected for analysis. Moreover, ADAMDEC1 showed a positive correlation with six immune infiltrates, most notably with B cells and dendritic cells. F13A1 was also positively correlated with six immune infiltrates, particularly macrophage and dendritic cells, whereas LGALS9C was negatively correlated with all immune infiltrates except B cells. Additionally, the prognostic risk model was strongly correlated with the actual situation. We retained only three prognosis risk factors: age, pathologic stage, and prognostic risk model. The stratified analysis revealed that lower ages and pathologic stages have a better prognosis with READ. Age and mRNA prognostic factors were the most important factors in determining the possibility of 3- and 5-year survival. Conclusion: In summary, we identified a nine-gene prognosis risk model that is applicable to the treatment of READ. Altogether, characteristics such as the gene signature and age have a strong predictive value for prognosis risk. |
format | Online Article Text |
id | pubmed-9159392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91593922022-06-02 Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma Jiang, Linlin Wang, Peng Su, Mu Yang, Lili Wang, Qingbo Front Genet Genetics Background: The immune system plays a crucial role in rectal adenocarcinoma (READ). Immune-related genes may help predict READ prognoses. Methods: The Cancer Genome Atlas dataset and GSE56699 were used as the training and validation datasets, respectively, and differentially expressed genes (DEGs) were identified. The optimal DEG combination was determined, and the prognostic risk model was constructed. The correlation between optimal DEGs and immune infiltrating cells was evaluated. Results: Nine DEGs were selected for analysis. Moreover, ADAMDEC1 showed a positive correlation with six immune infiltrates, most notably with B cells and dendritic cells. F13A1 was also positively correlated with six immune infiltrates, particularly macrophage and dendritic cells, whereas LGALS9C was negatively correlated with all immune infiltrates except B cells. Additionally, the prognostic risk model was strongly correlated with the actual situation. We retained only three prognosis risk factors: age, pathologic stage, and prognostic risk model. The stratified analysis revealed that lower ages and pathologic stages have a better prognosis with READ. Age and mRNA prognostic factors were the most important factors in determining the possibility of 3- and 5-year survival. Conclusion: In summary, we identified a nine-gene prognosis risk model that is applicable to the treatment of READ. Altogether, characteristics such as the gene signature and age have a strong predictive value for prognosis risk. Frontiers Media S.A. 2022-05-18 /pmc/articles/PMC9159392/ /pubmed/35664306 http://dx.doi.org/10.3389/fgene.2022.880945 Text en Copyright © 2022 Jiang, Wang, Su, Yang and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Jiang, Linlin Wang, Peng Su, Mu Yang, Lili Wang, Qingbo Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma |
title | Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma |
title_full | Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma |
title_fullStr | Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma |
title_full_unstemmed | Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma |
title_short | Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma |
title_sort | identification of mrna signature for predicting prognosis risk of rectal adenocarcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159392/ https://www.ncbi.nlm.nih.gov/pubmed/35664306 http://dx.doi.org/10.3389/fgene.2022.880945 |
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