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Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the human urinary system. Macrophage differentiation is associated with tumorigenesis. Therefore, exploring the prognostic value of macrophage differentiation–associated genes (MDGs) may contribute to better clinical managem...

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Autores principales: Liu, Chen, Zhang, Xuhui, Hu, Caoyang, Liang, Xuezhi, Cao, Xiaoming, Wang, Dongwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237391/
https://www.ncbi.nlm.nih.gov/pubmed/35774505
http://dx.doi.org/10.3389/fgene.2022.877656
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author Liu, Chen
Zhang, Xuhui
Hu, Caoyang
Liang, Xuezhi
Cao, Xiaoming
Wang, Dongwen
author_facet Liu, Chen
Zhang, Xuhui
Hu, Caoyang
Liang, Xuezhi
Cao, Xiaoming
Wang, Dongwen
author_sort Liu, Chen
collection PubMed
description Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the human urinary system. Macrophage differentiation is associated with tumorigenesis. Therefore, exploring the prognostic value of macrophage differentiation–associated genes (MDGs) may contribute to better clinical management of ccRCC patients. Methods: The RNA sequence data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed MDGs were unveiled in ccRCC and normal samples. The prognostic model was established according to the univariate and multivariate Cox regression analyses. By combining clinico-pathological features and prognostic genes, a nomogram was established to predict individual survival probability. The Tumor Immune Estimation Resource (TIMER) database was utilized to analyze the correlation between prognostic genes and immune infiltrating cells. Eventually, the mRNA and protein expression levels of prognostic genes were verified. Results: A total of 52 differentially expressed prognosis-related MDGs were identified in ccRCC. Afterward, a six-gene prognostic model (ABCG1, KDF1, KITLG, TGFA, HAVCR2, and CD14) was constructed through the Cox analysis. The overall survival in the high-risk group was relatively poor. Moreover, the risk score was identified as an independent prognostic factor. We constructed a prognostic nomogram with a well-fitted calibration curve based on risk score and clinical data. Furthermore, the prognostic genes were significantly related to the level of immune cell infiltration including B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells. Finally, the mRNA expression of prognostic genes in clinical ccRCC tissues showed that the ABCG1, HAVCR2, CD14, and TGFA mRNA in tumor samples were increased compared with the adjacent control tissue samples, while KDF1 and KITLG were decreased, which was consistent with the verification results in the GSE53757. Conclusion: In conclusion, this study identified and validated a macrophage differentiation–associated prognostic model for ccRCC that could be used to predict the outcomes of the ccRCC patients.
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spelling pubmed-92373912022-06-29 Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma Liu, Chen Zhang, Xuhui Hu, Caoyang Liang, Xuezhi Cao, Xiaoming Wang, Dongwen Front Genet Genetics Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the human urinary system. Macrophage differentiation is associated with tumorigenesis. Therefore, exploring the prognostic value of macrophage differentiation–associated genes (MDGs) may contribute to better clinical management of ccRCC patients. Methods: The RNA sequence data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed MDGs were unveiled in ccRCC and normal samples. The prognostic model was established according to the univariate and multivariate Cox regression analyses. By combining clinico-pathological features and prognostic genes, a nomogram was established to predict individual survival probability. The Tumor Immune Estimation Resource (TIMER) database was utilized to analyze the correlation between prognostic genes and immune infiltrating cells. Eventually, the mRNA and protein expression levels of prognostic genes were verified. Results: A total of 52 differentially expressed prognosis-related MDGs were identified in ccRCC. Afterward, a six-gene prognostic model (ABCG1, KDF1, KITLG, TGFA, HAVCR2, and CD14) was constructed through the Cox analysis. The overall survival in the high-risk group was relatively poor. Moreover, the risk score was identified as an independent prognostic factor. We constructed a prognostic nomogram with a well-fitted calibration curve based on risk score and clinical data. Furthermore, the prognostic genes were significantly related to the level of immune cell infiltration including B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells. Finally, the mRNA expression of prognostic genes in clinical ccRCC tissues showed that the ABCG1, HAVCR2, CD14, and TGFA mRNA in tumor samples were increased compared with the adjacent control tissue samples, while KDF1 and KITLG were decreased, which was consistent with the verification results in the GSE53757. Conclusion: In conclusion, this study identified and validated a macrophage differentiation–associated prognostic model for ccRCC that could be used to predict the outcomes of the ccRCC patients. Frontiers Media S.A. 2022-06-14 /pmc/articles/PMC9237391/ /pubmed/35774505 http://dx.doi.org/10.3389/fgene.2022.877656 Text en Copyright © 2022 Liu, Zhang, Hu, Liang, Cao 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
Liu, Chen
Zhang, Xuhui
Hu, Caoyang
Liang, Xuezhi
Cao, Xiaoming
Wang, Dongwen
Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma
title Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma
title_full Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma
title_fullStr Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma
title_full_unstemmed Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma
title_short Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma
title_sort systematic construction and validation of a novel macrophage differentiation–associated prognostic model for clear cell renal cell carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237391/
https://www.ncbi.nlm.nih.gov/pubmed/35774505
http://dx.doi.org/10.3389/fgene.2022.877656
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