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Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma

BACKGROUND: In recent years, the relationship between tumor-associated macrophages (TAMs) and solid tumors has become a research hotspot. This study aims to explore the close relationship of TAMs with metabolic reprogramming genes in hepatocellular carcinoma (HCC) to provide new methods of treatment...

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Autores principales: Huo, Junyu, Wu, Liqun, Zang, Yunjin, Dong, Hongjing, Liu, Xiaoqiang, He, Fu, Zhang, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789516/
https://www.ncbi.nlm.nih.gov/pubmed/33413205
http://dx.doi.org/10.1186/s12885-020-07734-z
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author Huo, Junyu
Wu, Liqun
Zang, Yunjin
Dong, Hongjing
Liu, Xiaoqiang
He, Fu
Zhang, Xiao
author_facet Huo, Junyu
Wu, Liqun
Zang, Yunjin
Dong, Hongjing
Liu, Xiaoqiang
He, Fu
Zhang, Xiao
author_sort Huo, Junyu
collection PubMed
description BACKGROUND: In recent years, the relationship between tumor-associated macrophages (TAMs) and solid tumors has become a research hotspot. This study aims to explore the close relationship of TAMs with metabolic reprogramming genes in hepatocellular carcinoma (HCC) to provide new methods of treatment for HCC. METHODS: The study selected 343 HCC patients with complete survival information (survival time > = 1 month) in the Cancer Genome Atlas (TCGA) as study subjects. Kaplan-Meier survival analysis assisted in determining the relationship between macrophage infiltration and overall survival (OS), and Pearson correlation tests were used to identify metabolic reprogramming genes (MRGs) associated with tumor macrophage abundance. Lasso regression algorithms were used on prognosis-related MRGs identified by Kaplan-Meier survival analysis and univariate Cox regression analysis to construct a risk score; another independent cohort (including 228 HCC patients) from the International Cancer Genome Consortium (ICGC) was used to verify prognostic signature externally. RESULTS: A risk score composed of 8 metabolic genes could accurately predict the OS of a training cohort (TCGA) and a testing cohort (ICGC). The risk score could be widely used for people with different clinical characteristics, and it is a predictor that is independent of other clinical factors that affect prognosis. As expected, compared with the low-risk group, the high-risk group exhibited an obviously higher macrophage abundance, together with a positive correlation between the risk score and the expression levels of three commonly used immune checkpoints (PD1, PDL1, and CTLA4). CONCLUSION: Our study constructed and validated a novel eight-gene signature for predicting HCC patient OS, which may contribute to clinical treatment decisions.
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spelling pubmed-77895162021-01-07 Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma Huo, Junyu Wu, Liqun Zang, Yunjin Dong, Hongjing Liu, Xiaoqiang He, Fu Zhang, Xiao BMC Cancer Research Article BACKGROUND: In recent years, the relationship between tumor-associated macrophages (TAMs) and solid tumors has become a research hotspot. This study aims to explore the close relationship of TAMs with metabolic reprogramming genes in hepatocellular carcinoma (HCC) to provide new methods of treatment for HCC. METHODS: The study selected 343 HCC patients with complete survival information (survival time > = 1 month) in the Cancer Genome Atlas (TCGA) as study subjects. Kaplan-Meier survival analysis assisted in determining the relationship between macrophage infiltration and overall survival (OS), and Pearson correlation tests were used to identify metabolic reprogramming genes (MRGs) associated with tumor macrophage abundance. Lasso regression algorithms were used on prognosis-related MRGs identified by Kaplan-Meier survival analysis and univariate Cox regression analysis to construct a risk score; another independent cohort (including 228 HCC patients) from the International Cancer Genome Consortium (ICGC) was used to verify prognostic signature externally. RESULTS: A risk score composed of 8 metabolic genes could accurately predict the OS of a training cohort (TCGA) and a testing cohort (ICGC). The risk score could be widely used for people with different clinical characteristics, and it is a predictor that is independent of other clinical factors that affect prognosis. As expected, compared with the low-risk group, the high-risk group exhibited an obviously higher macrophage abundance, together with a positive correlation between the risk score and the expression levels of three commonly used immune checkpoints (PD1, PDL1, and CTLA4). CONCLUSION: Our study constructed and validated a novel eight-gene signature for predicting HCC patient OS, which may contribute to clinical treatment decisions. BioMed Central 2021-01-07 /pmc/articles/PMC7789516/ /pubmed/33413205 http://dx.doi.org/10.1186/s12885-020-07734-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Huo, Junyu
Wu, Liqun
Zang, Yunjin
Dong, Hongjing
Liu, Xiaoqiang
He, Fu
Zhang, Xiao
Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
title Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
title_full Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
title_fullStr Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
title_full_unstemmed Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
title_short Eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
title_sort eight-gene metabolic signature related with tumor-associated macrophages predicting overall survival for hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789516/
https://www.ncbi.nlm.nih.gov/pubmed/33413205
http://dx.doi.org/10.1186/s12885-020-07734-z
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