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Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients

BACKGROUND: Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to for...

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Autores principales: Dai, Siqi, Xu, Shuang, Ye, Yao, Ding, Kefeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746810/
https://www.ncbi.nlm.nih.gov/pubmed/33343640
http://dx.doi.org/10.3389/fgene.2020.607009
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author Dai, Siqi
Xu, Shuang
Ye, Yao
Ding, Kefeng
author_facet Dai, Siqi
Xu, Shuang
Ye, Yao
Ding, Kefeng
author_sort Dai, Siqi
collection PubMed
description BACKGROUND: Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient’s prognosis. METHODS: IRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another two CRC datasets from the Gene Expression Omnibus (GEO). Gene function enrichment analysis was conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors. RESULTS: The three datasets had 487, 579, and 224 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B, and IL20RB) was developed through feature selection that showed good differentiation between the low- and high-risk groups in the training set (p < 0.001), which was later confirmed in the two validation groups (log-rank p < 0.05). The signature outperformed tumor TNM staging for survival prediction. GO and KEGG functional annotation analysis suggested that the signature was significantly enriched in metabolic processes and regulation of immunity (p < 0.05). When combined with clinical risk factors, the model showed robust prediction capability. CONCLUSION: The immune-related six-gene signature is a reliable prognostic indicator for CRC patients and could provide insight for personalized cancer management.
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spelling pubmed-77468102020-12-19 Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients Dai, Siqi Xu, Shuang Ye, Yao Ding, Kefeng Front Genet Genetics BACKGROUND: Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient’s prognosis. METHODS: IRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another two CRC datasets from the Gene Expression Omnibus (GEO). Gene function enrichment analysis was conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors. RESULTS: The three datasets had 487, 579, and 224 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B, and IL20RB) was developed through feature selection that showed good differentiation between the low- and high-risk groups in the training set (p < 0.001), which was later confirmed in the two validation groups (log-rank p < 0.05). The signature outperformed tumor TNM staging for survival prediction. GO and KEGG functional annotation analysis suggested that the signature was significantly enriched in metabolic processes and regulation of immunity (p < 0.05). When combined with clinical risk factors, the model showed robust prediction capability. CONCLUSION: The immune-related six-gene signature is a reliable prognostic indicator for CRC patients and could provide insight for personalized cancer management. Frontiers Media S.A. 2020-12-04 /pmc/articles/PMC7746810/ /pubmed/33343640 http://dx.doi.org/10.3389/fgene.2020.607009 Text en Copyright © 2020 Dai, Xu, Ye and Ding. http://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
Dai, Siqi
Xu, Shuang
Ye, Yao
Ding, Kefeng
Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients
title Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients
title_full Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients
title_fullStr Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients
title_full_unstemmed Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients
title_short Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients
title_sort identification of an immune-related gene signature to improve prognosis prediction in colorectal cancer patients
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746810/
https://www.ncbi.nlm.nih.gov/pubmed/33343640
http://dx.doi.org/10.3389/fgene.2020.607009
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