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Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations
Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DN...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393968/ https://www.ncbi.nlm.nih.gov/pubmed/37394583 http://dx.doi.org/10.1038/s12276-023-01011-2 |
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author | Xu, Zhiyang Zhou, Kaixiang Wang, Zhenni Liu, Yang Wang, Xingguo Gao, Tian Xie, Fanfan Yuan, Qing Gu, Xiwen Liu, Shujuan Xing, Jinliang |
author_facet | Xu, Zhiyang Zhou, Kaixiang Wang, Zhenni Liu, Yang Wang, Xingguo Gao, Tian Xie, Fanfan Yuan, Qing Gu, Xiwen Liu, Shujuan Xing, Jinliang |
author_sort | Xu, Zhiyang |
collection | PubMed |
description | Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients. |
format | Online Article Text |
id | pubmed-10393968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103939682023-08-03 Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations Xu, Zhiyang Zhou, Kaixiang Wang, Zhenni Liu, Yang Wang, Xingguo Gao, Tian Xie, Fanfan Yuan, Qing Gu, Xiwen Liu, Shujuan Xing, Jinliang Exp Mol Med Article Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients. Nature Publishing Group UK 2023-07-03 /pmc/articles/PMC10393968/ /pubmed/37394583 http://dx.doi.org/10.1038/s12276-023-01011-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Xu, Zhiyang Zhou, Kaixiang Wang, Zhenni Liu, Yang Wang, Xingguo Gao, Tian Xie, Fanfan Yuan, Qing Gu, Xiwen Liu, Shujuan Xing, Jinliang Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
title | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
title_full | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
title_fullStr | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
title_full_unstemmed | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
title_short | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
title_sort | metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial dna mutations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393968/ https://www.ncbi.nlm.nih.gov/pubmed/37394583 http://dx.doi.org/10.1038/s12276-023-01011-2 |
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