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Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes

Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly...

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Autores principales: Wang, Qian, Sun, Na, Meixner, Raphael, Le Gleut, Ronan, Kunzke, Thomas, Feuchtinger, Annette, Wang, Jun, Shen, Jian, Kircher, Stefan, Dischinger, Ulrich, Weigand, Isabel, Beuschlein, Felix, Fassnacht, Martin, Kroiss, Matthias, Walch, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Clinical Investigation 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543722/
https://www.ncbi.nlm.nih.gov/pubmed/37606037
http://dx.doi.org/10.1172/jci.insight.167007
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author Wang, Qian
Sun, Na
Meixner, Raphael
Le Gleut, Ronan
Kunzke, Thomas
Feuchtinger, Annette
Wang, Jun
Shen, Jian
Kircher, Stefan
Dischinger, Ulrich
Weigand, Isabel
Beuschlein, Felix
Fassnacht, Martin
Kroiss, Matthias
Walch, Axel
author_facet Wang, Qian
Sun, Na
Meixner, Raphael
Le Gleut, Ronan
Kunzke, Thomas
Feuchtinger, Annette
Wang, Jun
Shen, Jian
Kircher, Stefan
Dischinger, Ulrich
Weigand, Isabel
Beuschlein, Felix
Fassnacht, Martin
Kroiss, Matthias
Walch, Axel
author_sort Wang, Qian
collection PubMed
description Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly variable, but the contributions of tumor metabolic heterogeneity have not been investigated thus far to our knowledge. An in-depth understanding of tumor heterogeneity requires molecular feature-based identification of tumor subpopulations associated with tumor aggressiveness. Here, using spatial metabolomics by high–mass resolution MALDI Fourier transform ion cyclotron resonance mass spectrometry imaging, we assessed metabolic heterogeneity by de novo discovery of metabolic subpopulations and Simpson’s diversity index. After identification of tumor subpopulations in 72 patients with ACC, we additionally performed a comparison with 25 tissue sections of normal adrenal cortex to identify their common and unique metabolic subpopulations. We observed variability of ACC tumor heterogeneity and correlation of high metabolic heterogeneity with worse clinical outcome. Moreover, we identified tumor subpopulations that served as independent prognostic factors and, furthermore, discovered 4 associated anticancer drug action pathways. Our research may facilitate comprehensive understanding of the biological implications of tumor subpopulations in ACC and showed that metabolic heterogeneity might impact chemotherapy.
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spelling pubmed-105437222023-10-03 Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes Wang, Qian Sun, Na Meixner, Raphael Le Gleut, Ronan Kunzke, Thomas Feuchtinger, Annette Wang, Jun Shen, Jian Kircher, Stefan Dischinger, Ulrich Weigand, Isabel Beuschlein, Felix Fassnacht, Martin Kroiss, Matthias Walch, Axel JCI Insight Research Article Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly variable, but the contributions of tumor metabolic heterogeneity have not been investigated thus far to our knowledge. An in-depth understanding of tumor heterogeneity requires molecular feature-based identification of tumor subpopulations associated with tumor aggressiveness. Here, using spatial metabolomics by high–mass resolution MALDI Fourier transform ion cyclotron resonance mass spectrometry imaging, we assessed metabolic heterogeneity by de novo discovery of metabolic subpopulations and Simpson’s diversity index. After identification of tumor subpopulations in 72 patients with ACC, we additionally performed a comparison with 25 tissue sections of normal adrenal cortex to identify their common and unique metabolic subpopulations. We observed variability of ACC tumor heterogeneity and correlation of high metabolic heterogeneity with worse clinical outcome. Moreover, we identified tumor subpopulations that served as independent prognostic factors and, furthermore, discovered 4 associated anticancer drug action pathways. Our research may facilitate comprehensive understanding of the biological implications of tumor subpopulations in ACC and showed that metabolic heterogeneity might impact chemotherapy. American Society for Clinical Investigation 2023-08-22 /pmc/articles/PMC10543722/ /pubmed/37606037 http://dx.doi.org/10.1172/jci.insight.167007 Text en © 2023 Wang et al. https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Wang, Qian
Sun, Na
Meixner, Raphael
Le Gleut, Ronan
Kunzke, Thomas
Feuchtinger, Annette
Wang, Jun
Shen, Jian
Kircher, Stefan
Dischinger, Ulrich
Weigand, Isabel
Beuschlein, Felix
Fassnacht, Martin
Kroiss, Matthias
Walch, Axel
Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
title Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
title_full Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
title_fullStr Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
title_full_unstemmed Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
title_short Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
title_sort metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543722/
https://www.ncbi.nlm.nih.gov/pubmed/37606037
http://dx.doi.org/10.1172/jci.insight.167007
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