Cargando…
Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets
BACKGROUND: Generally, cancer cells undergo metabolic reprogramming to adapt to energetic and biosynthetic requirements that support their uncontrolled proliferation. However, the mutual relationship between two critical metabolic pathways, glycolysis and oxidative phosphorylation (OXPHOS), remains...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142489/ https://www.ncbi.nlm.nih.gov/pubmed/34030708 http://dx.doi.org/10.1186/s12967-021-02889-0 |
_version_ | 1783696563091013632 |
---|---|
author | Bi, Guoshu Bian, Yunyi Liang, Jiaqi Yin, Jiacheng Li, Runmei Zhao, Mengnan Huang, Yiwei Lu, Tao Zhan, Cheng Fan, Hong Wang, Qun |
author_facet | Bi, Guoshu Bian, Yunyi Liang, Jiaqi Yin, Jiacheng Li, Runmei Zhao, Mengnan Huang, Yiwei Lu, Tao Zhan, Cheng Fan, Hong Wang, Qun |
author_sort | Bi, Guoshu |
collection | PubMed |
description | BACKGROUND: Generally, cancer cells undergo metabolic reprogramming to adapt to energetic and biosynthetic requirements that support their uncontrolled proliferation. However, the mutual relationship between two critical metabolic pathways, glycolysis and oxidative phosphorylation (OXPHOS), remains poorly defined. METHODS: We developed a “double-score” system to quantify glycolysis and OXPHOS in 9668 patients across 33 tumor types from The Cancer Genome Atlas and classified them into four metabolic subtypes. Multi-omics bioinformatical analyses was conducted to detect metabolism-related molecular features. RESULTS: Compared with patients with low glycolysis and high OXPHOS (LGHO), those with high glycolysis and low OXPHOS (HGLO) were consistently associated with worse prognosis. We identified common dysregulated molecular features between different metabolic subgroups across multiple cancers, including gene, miRNA, transcription factor, methylation, and somatic alteration, as well as investigated their mutual interfering relationships. CONCLUSION: Overall, this work provides a comprehensive atlas of metabolic heterogeneity on a pan-cancer scale and identified several potential drivers of metabolic rewiring, suggesting corresponding prognostic and therapeutic utility. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-02889-0. |
format | Online Article Text |
id | pubmed-8142489 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81424892021-05-25 Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets Bi, Guoshu Bian, Yunyi Liang, Jiaqi Yin, Jiacheng Li, Runmei Zhao, Mengnan Huang, Yiwei Lu, Tao Zhan, Cheng Fan, Hong Wang, Qun J Transl Med Research BACKGROUND: Generally, cancer cells undergo metabolic reprogramming to adapt to energetic and biosynthetic requirements that support their uncontrolled proliferation. However, the mutual relationship between two critical metabolic pathways, glycolysis and oxidative phosphorylation (OXPHOS), remains poorly defined. METHODS: We developed a “double-score” system to quantify glycolysis and OXPHOS in 9668 patients across 33 tumor types from The Cancer Genome Atlas and classified them into four metabolic subtypes. Multi-omics bioinformatical analyses was conducted to detect metabolism-related molecular features. RESULTS: Compared with patients with low glycolysis and high OXPHOS (LGHO), those with high glycolysis and low OXPHOS (HGLO) were consistently associated with worse prognosis. We identified common dysregulated molecular features between different metabolic subgroups across multiple cancers, including gene, miRNA, transcription factor, methylation, and somatic alteration, as well as investigated their mutual interfering relationships. CONCLUSION: Overall, this work provides a comprehensive atlas of metabolic heterogeneity on a pan-cancer scale and identified several potential drivers of metabolic rewiring, suggesting corresponding prognostic and therapeutic utility. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-02889-0. BioMed Central 2021-05-24 /pmc/articles/PMC8142489/ /pubmed/34030708 http://dx.doi.org/10.1186/s12967-021-02889-0 Text en © The Author(s) 2021 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 Bi, Guoshu Bian, Yunyi Liang, Jiaqi Yin, Jiacheng Li, Runmei Zhao, Mengnan Huang, Yiwei Lu, Tao Zhan, Cheng Fan, Hong Wang, Qun Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
title | Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
title_full | Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
title_fullStr | Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
title_full_unstemmed | Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
title_short | Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
title_sort | pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142489/ https://www.ncbi.nlm.nih.gov/pubmed/34030708 http://dx.doi.org/10.1186/s12967-021-02889-0 |
work_keys_str_mv | AT biguoshu pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT bianyunyi pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT liangjiaqi pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT yinjiacheng pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT lirunmei pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT zhaomengnan pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT huangyiwei pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT lutao pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT zhancheng pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT fanhong pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets AT wangqun pancancercharacterizationofmetabolismrelatedbiomarkersidentifiespotentialtherapeutictargets |