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Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer
BACKGROUND: Ovarian cancer (OC) is the most malignant tumor in the female reproductive system. About 75% of OC in complete remission of clinical symptoms still develop a recurrence. Therefore, searching for new treatment methods plays an important role in improving the prognosis of OC. METHODS: We d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405355/ https://www.ncbi.nlm.nih.gov/pubmed/32774167 http://dx.doi.org/10.1186/s12935-020-01472-9 |
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author | Bi, Fangfang Chen, Ying Yang, Qing |
author_facet | Bi, Fangfang Chen, Ying Yang, Qing |
author_sort | Bi, Fangfang |
collection | PubMed |
description | BACKGROUND: Ovarian cancer (OC) is the most malignant tumor in the female reproductive system. About 75% of OC in complete remission of clinical symptoms still develop a recurrence. Therefore, searching for new treatment methods plays an important role in improving the prognosis of OC. METHODS: We downloaded the MAF files, RNA-seq data and clinical information from the TCGA database. The “maftools” package in R software was used to visualize the OC mutation data. We calculated the tumor mutation burden (TMB) of OC and analyzed its correlation with clinicopathological parameters and prognostic value. Tumor mutation burden related signature model was constructed to predict the overall survival (OS) of OC. RESULTS: The results revealed that there was a statistical correlation between TMB and FIGO stage, grade and tumor residual size of ovarian cancer patients. The Kaplan–Meier curve indicated that a high TMB is associated with better clinical outcomes of OC. The difference analysis indicated 24 upregulated genes and 619 downregulated genes in the high-TMB group compared with the low-TMB group. Besides, the TMBRS model based on five hub genes (RBMS3, PLA2G5, CDH2, AMHR2 and ADAMTS8) was constructed to predict the OS of OC. The ROC curve and validation data sets all revealed that the TMBRS model was reliable in predicting recurrence risk. Immune microenvironment analysis indicated the correlations between TMB and infiltrating immune cells. CONCLUSIONS: Our results suggest that TMB plays an important role in the prognosis and guiding immunotherapy of OC. By detecting the TMB of OC, clinicians can more accurately treat patients with immunotherapy, thereby improving their survival rate. |
format | Online Article Text |
id | pubmed-7405355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-74053552020-08-07 Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer Bi, Fangfang Chen, Ying Yang, Qing Cancer Cell Int Primary Research BACKGROUND: Ovarian cancer (OC) is the most malignant tumor in the female reproductive system. About 75% of OC in complete remission of clinical symptoms still develop a recurrence. Therefore, searching for new treatment methods plays an important role in improving the prognosis of OC. METHODS: We downloaded the MAF files, RNA-seq data and clinical information from the TCGA database. The “maftools” package in R software was used to visualize the OC mutation data. We calculated the tumor mutation burden (TMB) of OC and analyzed its correlation with clinicopathological parameters and prognostic value. Tumor mutation burden related signature model was constructed to predict the overall survival (OS) of OC. RESULTS: The results revealed that there was a statistical correlation between TMB and FIGO stage, grade and tumor residual size of ovarian cancer patients. The Kaplan–Meier curve indicated that a high TMB is associated with better clinical outcomes of OC. The difference analysis indicated 24 upregulated genes and 619 downregulated genes in the high-TMB group compared with the low-TMB group. Besides, the TMBRS model based on five hub genes (RBMS3, PLA2G5, CDH2, AMHR2 and ADAMTS8) was constructed to predict the OS of OC. The ROC curve and validation data sets all revealed that the TMBRS model was reliable in predicting recurrence risk. Immune microenvironment analysis indicated the correlations between TMB and infiltrating immune cells. CONCLUSIONS: Our results suggest that TMB plays an important role in the prognosis and guiding immunotherapy of OC. By detecting the TMB of OC, clinicians can more accurately treat patients with immunotherapy, thereby improving their survival rate. BioMed Central 2020-08-05 /pmc/articles/PMC7405355/ /pubmed/32774167 http://dx.doi.org/10.1186/s12935-020-01472-9 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 | Primary Research Bi, Fangfang Chen, Ying Yang, Qing Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
title | Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
title_full | Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
title_fullStr | Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
title_full_unstemmed | Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
title_short | Significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
title_sort | significance of tumor mutation burden combined with immune infiltrates in the progression and prognosis of ovarian cancer |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405355/ https://www.ncbi.nlm.nih.gov/pubmed/32774167 http://dx.doi.org/10.1186/s12935-020-01472-9 |
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