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Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration
BACKGROUND: p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differentia...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185979/ https://www.ncbi.nlm.nih.gov/pubmed/35689249 http://dx.doi.org/10.1186/s13018-022-03193-3 |
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author | Cai, Dechao Ma, Xiao Guo, Huihui Zhang, Haotian Bian, Ashuai Yu, Haoran Cheng, Wendan |
author_facet | Cai, Dechao Ma, Xiao Guo, Huihui Zhang, Haotian Bian, Ashuai Yu, Haoran Cheng, Wendan |
author_sort | Cai, Dechao |
collection | PubMed |
description | BACKGROUND: p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported. METHODS: The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan–Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER). RESULTS: p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma. CONCLUSIONS: The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma. |
format | Online Article Text |
id | pubmed-9185979 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91859792022-06-11 Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration Cai, Dechao Ma, Xiao Guo, Huihui Zhang, Haotian Bian, Ashuai Yu, Haoran Cheng, Wendan J Orthop Surg Res Research BACKGROUND: p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported. METHODS: The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan–Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER). RESULTS: p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma. CONCLUSIONS: The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma. BioMed Central 2022-06-10 /pmc/articles/PMC9185979/ /pubmed/35689249 http://dx.doi.org/10.1186/s13018-022-03193-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Cai, Dechao Ma, Xiao Guo, Huihui Zhang, Haotian Bian, Ashuai Yu, Haoran Cheng, Wendan Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
title | Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
title_full | Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
title_fullStr | Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
title_full_unstemmed | Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
title_short | Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
title_sort | prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185979/ https://www.ncbi.nlm.nih.gov/pubmed/35689249 http://dx.doi.org/10.1186/s13018-022-03193-3 |
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