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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...

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Autores principales: Liu, Xiaona, Wu, Aoshen, Wang, Xing, Liu, Yunhe, Xu, Yiang, Liu, Gang, Liu, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
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.
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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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