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Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer

BACKGROUND: As the most common gastrointestinal malignancy worldwide, liver metastases occur in half colorectal cancer (CRC) patients. Early detection can help treat them early and reduce mortality in patients with colorectal cancer liver metastases (CRLM). Finding useful biomarkers for CRLM is thus...

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Autores principales: Liu, Chang, Lu, Zhihua, Yan, Jun, Xue, Dong, He, Xiaoyu, Huang, Wenbo, Sun, Qi, Zhao, Wei, Li, Fanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411999/
https://www.ncbi.nlm.nih.gov/pubmed/37564935
http://dx.doi.org/10.3389/fonc.2023.1234045
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author Liu, Chang
Lu, Zhihua
Yan, Jun
Xue, Dong
He, Xiaoyu
Huang, Wenbo
Sun, Qi
Zhao, Wei
Li, Fanni
author_facet Liu, Chang
Lu, Zhihua
Yan, Jun
Xue, Dong
He, Xiaoyu
Huang, Wenbo
Sun, Qi
Zhao, Wei
Li, Fanni
author_sort Liu, Chang
collection PubMed
description BACKGROUND: As the most common gastrointestinal malignancy worldwide, liver metastases occur in half colorectal cancer (CRC) patients. Early detection can help treat them early and reduce mortality in patients with colorectal cancer liver metastases (CRLM). Finding useful biomarkers for CRLM is thus essential. METHODS: The TCGA and GEO databases were used to download the expression profiles and clinical data of the patients. Differential analysis screened for genes associated with CRLM, and univariate Cox regression analysis identified genes associated with prognosis. The least absolute shrinkage and selection operator (LASSO) method further preferred genes to construct a prognostic signature. Kaplan-Meier survival curves were used to show patients’ overall survival (OS). Receiver operating characteristic (ROC) curves showed the accuracy of the model. Risk scores and clinical characteristics of patients were included in multivariate Cox regression analysis to identify independent risk factors, and a nomogram was constructed. The proportion of immune cells and infiltration were assessed using the ‘CIBERSORT’ package and the ‘ESTIMATE’ package. RESULTS: We constructed a signature consisting of seven CRLM-associated genes, and signature-based risk scores have great potential in estimating the prognosis of CRC patients. Moreover, the poor response to immunotherapy in high-risk patients might contribute to the poor prognosis of individuals. Furthermore, we found that overexpression of Hepcidin antimicrobial peptide (HAMP), the only gene highly expressed in CRC and liver metastatic tissues, promoted CRC development and that it was associated with tumor mutation burden (TMB), DNA mismatch repair (MMR) genes, and microsatellite instability (MSI) in various tumors. Finally, we found that in CRC patients, low expression of HAMP also represented a better immunotherapeutic outcome, reflecting the critical role of HAMP in guiding immunotherapy. CONCLUSION: We identified a prognostic signature containing 7 CRLM-associated genes, and the signature was specified as an independent predictor and a nomogram containing the risk score was built accordingly. In addition, the derived gene HAMP could help guide the exploration of profitable immunotherapeutic strategies.
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spelling pubmed-104119992023-08-10 Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer Liu, Chang Lu, Zhihua Yan, Jun Xue, Dong He, Xiaoyu Huang, Wenbo Sun, Qi Zhao, Wei Li, Fanni Front Oncol Oncology BACKGROUND: As the most common gastrointestinal malignancy worldwide, liver metastases occur in half colorectal cancer (CRC) patients. Early detection can help treat them early and reduce mortality in patients with colorectal cancer liver metastases (CRLM). Finding useful biomarkers for CRLM is thus essential. METHODS: The TCGA and GEO databases were used to download the expression profiles and clinical data of the patients. Differential analysis screened for genes associated with CRLM, and univariate Cox regression analysis identified genes associated with prognosis. The least absolute shrinkage and selection operator (LASSO) method further preferred genes to construct a prognostic signature. Kaplan-Meier survival curves were used to show patients’ overall survival (OS). Receiver operating characteristic (ROC) curves showed the accuracy of the model. Risk scores and clinical characteristics of patients were included in multivariate Cox regression analysis to identify independent risk factors, and a nomogram was constructed. The proportion of immune cells and infiltration were assessed using the ‘CIBERSORT’ package and the ‘ESTIMATE’ package. RESULTS: We constructed a signature consisting of seven CRLM-associated genes, and signature-based risk scores have great potential in estimating the prognosis of CRC patients. Moreover, the poor response to immunotherapy in high-risk patients might contribute to the poor prognosis of individuals. Furthermore, we found that overexpression of Hepcidin antimicrobial peptide (HAMP), the only gene highly expressed in CRC and liver metastatic tissues, promoted CRC development and that it was associated with tumor mutation burden (TMB), DNA mismatch repair (MMR) genes, and microsatellite instability (MSI) in various tumors. Finally, we found that in CRC patients, low expression of HAMP also represented a better immunotherapeutic outcome, reflecting the critical role of HAMP in guiding immunotherapy. CONCLUSION: We identified a prognostic signature containing 7 CRLM-associated genes, and the signature was specified as an independent predictor and a nomogram containing the risk score was built accordingly. In addition, the derived gene HAMP could help guide the exploration of profitable immunotherapeutic strategies. Frontiers Media S.A. 2023-07-26 /pmc/articles/PMC10411999/ /pubmed/37564935 http://dx.doi.org/10.3389/fonc.2023.1234045 Text en Copyright © 2023 Liu, Lu, Yan, Xue, He, Huang, Sun, Zhao and Li 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 Oncology
Liu, Chang
Lu, Zhihua
Yan, Jun
Xue, Dong
He, Xiaoyu
Huang, Wenbo
Sun, Qi
Zhao, Wei
Li, Fanni
Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
title Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
title_full Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
title_fullStr Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
title_full_unstemmed Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
title_short Construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
title_sort construction of a prognostic signature associated with liver metastases for prognosis and immune response prediction in colorectal cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411999/
https://www.ncbi.nlm.nih.gov/pubmed/37564935
http://dx.doi.org/10.3389/fonc.2023.1234045
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