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Identification of metabolism‐associated molecular subtype in ovarian cancer
Ovarian cancer (OC) is the most lethal gynaecological cancer with genomic complexity and extensive heterogeneity. This study aimed to characterize the molecular features of OC based on the gene expression profile of 2752 previously characterized metabolism‐relevant genes and provide new strategies t...
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/PMC8505839/ https://www.ncbi.nlm.nih.gov/pubmed/34523782 http://dx.doi.org/10.1111/jcmm.16907 |
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author | Liu, Xiaona Wu, Aoshen Wang, Xing Liu, Yunhe Xu, Yiang Liu, Gang Liu, Lei |
author_facet | Liu, Xiaona Wu, Aoshen Wang, Xing Liu, Yunhe Xu, Yiang Liu, Gang Liu, Lei |
author_sort | Liu, Xiaona |
collection | PubMed |
description | Ovarian cancer (OC) is the most lethal gynaecological cancer with genomic complexity and extensive heterogeneity. This study aimed to characterize the molecular features of OC based on the gene expression profile of 2752 previously characterized metabolism‐relevant genes and provide new strategies to improve the clinical status of patients with OC. Finally, three molecular subtypes (C1, C2 and C3) were identified. The C2 subtype displayed the worst prognosis, upregulated immune‐cell infiltration status and expression level of immune checkpoint genes, lower burden of copy number gains and losses and suboptimal response to targeted drug bevacizumab. The C1 subtype showed downregulated immune‐cell infiltration status and expression level of immune checkpoint genes, the lowest incidence of BRCA mutation and optimal response to targeted drug bevacizumab. The C3 subtype had an intermediate immune status, the highest incidence of BRCA mutation and a secondary optimal response to bevacizumab. Gene signatures of C1 and C2 subtypes with an opposite expression level were mainly enriched in proteolysis and immune‐related biological process. The C3 subtype was mainly enriched in the T cell‐related biological process. The prognostic and immune status of subtypes were validated in the Gene Expression Omnibus (GEO) dataset, which was predicted with a 45‐gene classifier. These findings might improve the understanding of the diversity and therapeutic strategies for OC. |
format | Online Article Text |
id | pubmed-8505839 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85058392021-10-18 Identification of metabolism‐associated molecular subtype in ovarian cancer Liu, Xiaona Wu, Aoshen Wang, Xing Liu, Yunhe Xu, Yiang Liu, Gang Liu, Lei J Cell Mol Med Original Articles Ovarian cancer (OC) is the most lethal gynaecological cancer with genomic complexity and extensive heterogeneity. This study aimed to characterize the molecular features of OC based on the gene expression profile of 2752 previously characterized metabolism‐relevant genes and provide new strategies to improve the clinical status of patients with OC. Finally, three molecular subtypes (C1, C2 and C3) were identified. The C2 subtype displayed the worst prognosis, upregulated immune‐cell infiltration status and expression level of immune checkpoint genes, lower burden of copy number gains and losses and suboptimal response to targeted drug bevacizumab. The C1 subtype showed downregulated immune‐cell infiltration status and expression level of immune checkpoint genes, the lowest incidence of BRCA mutation and optimal response to targeted drug bevacizumab. The C3 subtype had an intermediate immune status, the highest incidence of BRCA mutation and a secondary optimal response to bevacizumab. Gene signatures of C1 and C2 subtypes with an opposite expression level were mainly enriched in proteolysis and immune‐related biological process. The C3 subtype was mainly enriched in the T cell‐related biological process. The prognostic and immune status of subtypes were validated in the Gene Expression Omnibus (GEO) dataset, which was predicted with a 45‐gene classifier. These findings might improve the understanding of the diversity and therapeutic strategies for OC. John Wiley and Sons Inc. 2021-09-15 2021-10 /pmc/articles/PMC8505839/ /pubmed/34523782 http://dx.doi.org/10.1111/jcmm.16907 Text en © 2021 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Liu, Xiaona Wu, Aoshen Wang, Xing Liu, Yunhe Xu, Yiang Liu, Gang Liu, Lei Identification of metabolism‐associated molecular subtype in ovarian cancer |
title | Identification of metabolism‐associated molecular subtype in ovarian cancer |
title_full | Identification of metabolism‐associated molecular subtype in ovarian cancer |
title_fullStr | Identification of metabolism‐associated molecular subtype in ovarian cancer |
title_full_unstemmed | Identification of metabolism‐associated molecular subtype in ovarian cancer |
title_short | Identification of metabolism‐associated molecular subtype in ovarian cancer |
title_sort | identification of metabolism‐associated molecular subtype in ovarian cancer |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505839/ https://www.ncbi.nlm.nih.gov/pubmed/34523782 http://dx.doi.org/10.1111/jcmm.16907 |
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