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ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing

BACKGROUND: Osteosarcoma is a common solid malignancy of the bone in children and adolescents, and its metastasis and recurrence are the principal causes of poor treatment outcomes. METHODS: Autophagy-related genes were used to cluster osteosarcoma patients by consensus clustering analysis using the...

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Autores principales: Qin, Zhaojie, Luo, Kai, Liu, Yun, Liao, Shijie, He, Juliang, He, Mingwei, Xie, Tianyu, Jiang, Xiaohong, Li, Boxiang, Liu, Huijiang, Huang, Qian, Tang, Haijun, Feng, Wenyu, Zhan, Xinli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818976/
https://www.ncbi.nlm.nih.gov/pubmed/35140506
http://dx.doi.org/10.2147/IJGM.S341879
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author Qin, Zhaojie
Luo, Kai
Liu, Yun
Liao, Shijie
He, Juliang
He, Mingwei
Xie, Tianyu
Jiang, Xiaohong
Li, Boxiang
Liu, Huijiang
Huang, Qian
Tang, Haijun
Feng, Wenyu
Zhan, Xinli
author_facet Qin, Zhaojie
Luo, Kai
Liu, Yun
Liao, Shijie
He, Juliang
He, Mingwei
Xie, Tianyu
Jiang, Xiaohong
Li, Boxiang
Liu, Huijiang
Huang, Qian
Tang, Haijun
Feng, Wenyu
Zhan, Xinli
author_sort Qin, Zhaojie
collection PubMed
description BACKGROUND: Osteosarcoma is a common solid malignancy of the bone in children and adolescents, and its metastasis and recurrence are the principal causes of poor treatment outcomes. METHODS: Autophagy-related genes were used to cluster osteosarcoma patients by consensus clustering analysis using the GSE21257 database. Differentially expressed genes (DEGs) were identified by limma package. Multiple-gene risk signature was constructed using least absolute shrinkage and selection operator (LASSO) analysis and Cox regression analyses. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to determine gene expression levels. Then, single-cell RNA-sequencing dataset GSE152048 were used to identify the correlation between the DEGs and effector molecules expressed in specific tumor-infiltrating immune cells. RESULTS: Two clusters were identified in the consensus clustering analysis, which were confirmed by principal component analysis. Limma analysis revealed that 15 genes were related, and 9 genes were screened using protein-protein interaction network and LASSO regression analysis. Cox regression analyses identified 5 genes. Combined with survival analysis, only the autophagy related 16 like 1 gene (ATG16L1) was significant. The results of qRT-PCR showed low expression levels of ATG16L1 in tumor cells group. Immune infiltration analysis revealed significantly lower expression of CD8(+) T cells in the high ATG16L1 gene expression group. ScRNA-seq revealed that in the ATG16L1(+)CD8(+) T cell group, the expression of GZMB was lower, whereas the expression of ITGA1 was higher. These results showed that ATG16L1 is an immune-related gene, which is associated with poor prognosis in patients with osteosarcoma. CONCLUSION: ATG16L1 is a potential prognostic biomarker and immune signature and may be a therapeutic target for osteosarcoma.
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spelling pubmed-88189762022-02-08 ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing Qin, Zhaojie Luo, Kai Liu, Yun Liao, Shijie He, Juliang He, Mingwei Xie, Tianyu Jiang, Xiaohong Li, Boxiang Liu, Huijiang Huang, Qian Tang, Haijun Feng, Wenyu Zhan, Xinli Int J Gen Med Original Research BACKGROUND: Osteosarcoma is a common solid malignancy of the bone in children and adolescents, and its metastasis and recurrence are the principal causes of poor treatment outcomes. METHODS: Autophagy-related genes were used to cluster osteosarcoma patients by consensus clustering analysis using the GSE21257 database. Differentially expressed genes (DEGs) were identified by limma package. Multiple-gene risk signature was constructed using least absolute shrinkage and selection operator (LASSO) analysis and Cox regression analyses. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to determine gene expression levels. Then, single-cell RNA-sequencing dataset GSE152048 were used to identify the correlation between the DEGs and effector molecules expressed in specific tumor-infiltrating immune cells. RESULTS: Two clusters were identified in the consensus clustering analysis, which were confirmed by principal component analysis. Limma analysis revealed that 15 genes were related, and 9 genes were screened using protein-protein interaction network and LASSO regression analysis. Cox regression analyses identified 5 genes. Combined with survival analysis, only the autophagy related 16 like 1 gene (ATG16L1) was significant. The results of qRT-PCR showed low expression levels of ATG16L1 in tumor cells group. Immune infiltration analysis revealed significantly lower expression of CD8(+) T cells in the high ATG16L1 gene expression group. ScRNA-seq revealed that in the ATG16L1(+)CD8(+) T cell group, the expression of GZMB was lower, whereas the expression of ITGA1 was higher. These results showed that ATG16L1 is an immune-related gene, which is associated with poor prognosis in patients with osteosarcoma. CONCLUSION: ATG16L1 is a potential prognostic biomarker and immune signature and may be a therapeutic target for osteosarcoma. Dove 2022-02-02 /pmc/articles/PMC8818976/ /pubmed/35140506 http://dx.doi.org/10.2147/IJGM.S341879 Text en © 2022 Qin et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Qin, Zhaojie
Luo, Kai
Liu, Yun
Liao, Shijie
He, Juliang
He, Mingwei
Xie, Tianyu
Jiang, Xiaohong
Li, Boxiang
Liu, Huijiang
Huang, Qian
Tang, Haijun
Feng, Wenyu
Zhan, Xinli
ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing
title ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing
title_full ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing
title_fullStr ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing
title_full_unstemmed ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing
title_short ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing
title_sort atg16l1 is a potential prognostic biomarker and immune signature for osteosarcoma: a study based on bulk rna and single-cell rna-sequencing
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818976/
https://www.ncbi.nlm.nih.gov/pubmed/35140506
http://dx.doi.org/10.2147/IJGM.S341879
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