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Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma
Osteosarcoma has been the most common malignant bone tumor in children and adolescents, while the 5‐y survival of osteosarcoma patients gained no significant improvement over the past decades. This study aimed to explore the role of ferroptosis‐related genes (FRGs) in the development and prognosis o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8586685/ https://www.ncbi.nlm.nih.gov/pubmed/34506683 http://dx.doi.org/10.1111/cas.15131 |
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author | Lei, Ting Qian, Hu Lei, Pengfei Hu, Yihe |
author_facet | Lei, Ting Qian, Hu Lei, Pengfei Hu, Yihe |
author_sort | Lei, Ting |
collection | PubMed |
description | Osteosarcoma has been the most common malignant bone tumor in children and adolescents, while the 5‐y survival of osteosarcoma patients gained no significant improvement over the past decades. This study aimed to explore the role of ferroptosis‐related genes (FRGs) in the development and prognosis of osteosarcoma. The datasets of osteosarcoma patients including RNA sequencing data and clinical information were acquired from the TRGET and Gene Expression Omnibus (GEO) databases. The identification of molecular subgroups with different FRG expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. The prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis. The ESTIMATE algorithm was applied for determining the stromal score, immune score, ESTIMA score, and tumor purity of osteosarcoma patients. Functional analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were conducted to explore the underlying mechanisms in the development and prognosis of osteosarcoma. Two molecular subgroups with different FRGs expression patterns were identified. The molecular subgroups with higher immune score and more active immune status showed better prognostic survival. On the basis of FRGs, a prognostic model and a nomogram integrating clinical characteristics were constructed and their prediction efficiency for osteosarcoma prognosis were well validated. Gene functional enrichment analysis showed that these differentially expressed FRGs were mainly enriched in immunity‐related signaling pathways, indicating that FRGs may affect the development and prognosis of osteosarcoma by regulating the immune microenvironment. The expression profiles of FRGs were closely related to the immunity status and prognostic survival of osteosarcoma patients. The interaction between ferroptosis and immunity in the development of osteosarcoma could provide a new insight into the exploration of molecular mechanisms and targeted therapies of osteosarcoma patients. |
format | Online Article Text |
id | pubmed-8586685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85866852021-11-18 Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma Lei, Ting Qian, Hu Lei, Pengfei Hu, Yihe Cancer Sci Original Articles Osteosarcoma has been the most common malignant bone tumor in children and adolescents, while the 5‐y survival of osteosarcoma patients gained no significant improvement over the past decades. This study aimed to explore the role of ferroptosis‐related genes (FRGs) in the development and prognosis of osteosarcoma. The datasets of osteosarcoma patients including RNA sequencing data and clinical information were acquired from the TRGET and Gene Expression Omnibus (GEO) databases. The identification of molecular subgroups with different FRG expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. The prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis. The ESTIMATE algorithm was applied for determining the stromal score, immune score, ESTIMA score, and tumor purity of osteosarcoma patients. Functional analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were conducted to explore the underlying mechanisms in the development and prognosis of osteosarcoma. Two molecular subgroups with different FRGs expression patterns were identified. The molecular subgroups with higher immune score and more active immune status showed better prognostic survival. On the basis of FRGs, a prognostic model and a nomogram integrating clinical characteristics were constructed and their prediction efficiency for osteosarcoma prognosis were well validated. Gene functional enrichment analysis showed that these differentially expressed FRGs were mainly enriched in immunity‐related signaling pathways, indicating that FRGs may affect the development and prognosis of osteosarcoma by regulating the immune microenvironment. The expression profiles of FRGs were closely related to the immunity status and prognostic survival of osteosarcoma patients. The interaction between ferroptosis and immunity in the development of osteosarcoma could provide a new insight into the exploration of molecular mechanisms and targeted therapies of osteosarcoma patients. John Wiley and Sons Inc. 2021-09-21 2021-11 /pmc/articles/PMC8586685/ /pubmed/34506683 http://dx.doi.org/10.1111/cas.15131 Text en © 2021 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Articles Lei, Ting Qian, Hu Lei, Pengfei Hu, Yihe Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
title | Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
title_full | Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
title_fullStr | Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
title_full_unstemmed | Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
title_short | Ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
title_sort | ferroptosis‐related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8586685/ https://www.ncbi.nlm.nih.gov/pubmed/34506683 http://dx.doi.org/10.1111/cas.15131 |
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