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A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction

Sarcomas are a group of malignant tumors derived from mesenchymal tissues that display complex and variable pathological types. The impact of the immune properties of the tumor microenvironment (TME) on the prognosis, treatment, and management of sarcomas has attracted attention, requiring the explo...

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Autores principales: Zhang, Guanran, Jian, Aiwen, Zhang, Yundi, Zhang, Xiaoli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918054/
https://www.ncbi.nlm.nih.gov/pubmed/36769292
http://dx.doi.org/10.3390/ijms24032961
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author Zhang, Guanran
Jian, Aiwen
Zhang, Yundi
Zhang, Xiaoli
author_facet Zhang, Guanran
Jian, Aiwen
Zhang, Yundi
Zhang, Xiaoli
author_sort Zhang, Guanran
collection PubMed
description Sarcomas are a group of malignant tumors derived from mesenchymal tissues that display complex and variable pathological types. The impact of the immune properties of the tumor microenvironment (TME) on the prognosis, treatment, and management of sarcomas has attracted attention, requiring the exploration of sensitive and accurate signatures. In this study, The Cancer Genome Atlas (TCGA) database was searched to screen for an RNA sequencing dataset, retrieving 263 sarcoma and 2 normal samples with survival data. Genes associated with immune regulation in sarcomas were retrieved from the Tumor Immune Estimation Resource database to estimate tumor purity and immune cell infiltration levels. The samples were then divided into the immune-high and immune-low groups. Then, we screened for differentially expressed genes (DEGs) between the two groups. The intersection between immune-related genes and DEGs was then determined. Univariate Cox and least absolute shrinkage and selection operator analyses were used to select ideal genes for prognostic prediction and subsequent construction of a risk signature. A survival analysis was performed to reveal the dissimilarity in survival between the high- and low-score groups. Finally, a nomogram was generated to verify the accuracy and reliability of the signature. Through Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression (ESTIMATE) analysis, high ESTIMATE, and low tumor purity were significantly associated with a favorable prognosis. Moreover, a total of 5259 DEGs were retrieved, the majority of which were downregulated. In total, 590 immune-associated genes overlapped with the DEGs, among which nine hub genes were identified. Finally, two candidate genes, ACVR2B and NFYA, were identified, based on which a risk signature was constructed. The risk signature constructed in this study is accurate and reliable for the prognostic prediction and phenotyping of sarcomas.
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spelling pubmed-99180542023-02-11 A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction Zhang, Guanran Jian, Aiwen Zhang, Yundi Zhang, Xiaoli Int J Mol Sci Article Sarcomas are a group of malignant tumors derived from mesenchymal tissues that display complex and variable pathological types. The impact of the immune properties of the tumor microenvironment (TME) on the prognosis, treatment, and management of sarcomas has attracted attention, requiring the exploration of sensitive and accurate signatures. In this study, The Cancer Genome Atlas (TCGA) database was searched to screen for an RNA sequencing dataset, retrieving 263 sarcoma and 2 normal samples with survival data. Genes associated with immune regulation in sarcomas were retrieved from the Tumor Immune Estimation Resource database to estimate tumor purity and immune cell infiltration levels. The samples were then divided into the immune-high and immune-low groups. Then, we screened for differentially expressed genes (DEGs) between the two groups. The intersection between immune-related genes and DEGs was then determined. Univariate Cox and least absolute shrinkage and selection operator analyses were used to select ideal genes for prognostic prediction and subsequent construction of a risk signature. A survival analysis was performed to reveal the dissimilarity in survival between the high- and low-score groups. Finally, a nomogram was generated to verify the accuracy and reliability of the signature. Through Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression (ESTIMATE) analysis, high ESTIMATE, and low tumor purity were significantly associated with a favorable prognosis. Moreover, a total of 5259 DEGs were retrieved, the majority of which were downregulated. In total, 590 immune-associated genes overlapped with the DEGs, among which nine hub genes were identified. Finally, two candidate genes, ACVR2B and NFYA, were identified, based on which a risk signature was constructed. The risk signature constructed in this study is accurate and reliable for the prognostic prediction and phenotyping of sarcomas. MDPI 2023-02-03 /pmc/articles/PMC9918054/ /pubmed/36769292 http://dx.doi.org/10.3390/ijms24032961 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Guanran
Jian, Aiwen
Zhang, Yundi
Zhang, Xiaoli
A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction
title A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction
title_full A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction
title_fullStr A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction
title_full_unstemmed A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction
title_short A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction
title_sort new signature of sarcoma based on the tumor microenvironment benefits prognostic prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918054/
https://www.ncbi.nlm.nih.gov/pubmed/36769292
http://dx.doi.org/10.3390/ijms24032961
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