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Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort

Renal cell carcinoma (RCC) is among the 10 most common cancer entities and can be categorised into distinct subtypes by differential expression of Krebs cycle genes. We investigated the predictive value of several targeted metabolites with regards to tumour stages and patient survival in an unselect...

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Autores principales: William, Doreen, Erdmann, Kati, Ottemöller, Jonas, Mangelis, Anastasios, Conrad, Catleen, Peitzsch, Mirko, Schröck, Evelin, Eisenhofer, Graeme, Zacharis, Aristeidis, Füssel, Susanne, Aust, Daniela, Klink, Barbara, Richter, Susan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624007/
https://www.ncbi.nlm.nih.gov/pubmed/34822422
http://dx.doi.org/10.3390/metabo11110764
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author William, Doreen
Erdmann, Kati
Ottemöller, Jonas
Mangelis, Anastasios
Conrad, Catleen
Peitzsch, Mirko
Schröck, Evelin
Eisenhofer, Graeme
Zacharis, Aristeidis
Füssel, Susanne
Aust, Daniela
Klink, Barbara
Richter, Susan
author_facet William, Doreen
Erdmann, Kati
Ottemöller, Jonas
Mangelis, Anastasios
Conrad, Catleen
Peitzsch, Mirko
Schröck, Evelin
Eisenhofer, Graeme
Zacharis, Aristeidis
Füssel, Susanne
Aust, Daniela
Klink, Barbara
Richter, Susan
author_sort William, Doreen
collection PubMed
description Renal cell carcinoma (RCC) is among the 10 most common cancer entities and can be categorised into distinct subtypes by differential expression of Krebs cycle genes. We investigated the predictive value of several targeted metabolites with regards to tumour stages and patient survival in an unselected cohort of 420 RCCs. Unsupervised hierarchical clustering of metabolite ratios identified two main clusters separated by α-ketoglutarate (α-KG) levels and sub-clusters with differential levels of the oncometabolite 2-hydroxyglutarate (2HG). Sub-clusters characterised by high 2HG were enriched in higher tumour stages, suggesting metabolite profiles might be suitable predictors of tumour stage or survival. Bootstrap forest models based on single metabolite signatures showed that lactate, 2HG, citrate, aspartate, asparagine, and glutamine better predicted the cancer-specific survival (CSS) of clear cell RCC patients, whereas succinate and α-ketoglutarate were better CSS predictors for papillary RCC patients. Additionally, this assay identifies rare cases of tumours with SDHx mutations, which are caused predominantly by germline mutations and which predispose to development of different neoplasms. Hence, analysis of selected metabolites should be further evaluated for potential utility in liquid biopsies, which can be obtained using less invasive methods and potentially facilitate disease monitoring for both patients and caregivers.
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spelling pubmed-86240072021-11-27 Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort William, Doreen Erdmann, Kati Ottemöller, Jonas Mangelis, Anastasios Conrad, Catleen Peitzsch, Mirko Schröck, Evelin Eisenhofer, Graeme Zacharis, Aristeidis Füssel, Susanne Aust, Daniela Klink, Barbara Richter, Susan Metabolites Article Renal cell carcinoma (RCC) is among the 10 most common cancer entities and can be categorised into distinct subtypes by differential expression of Krebs cycle genes. We investigated the predictive value of several targeted metabolites with regards to tumour stages and patient survival in an unselected cohort of 420 RCCs. Unsupervised hierarchical clustering of metabolite ratios identified two main clusters separated by α-ketoglutarate (α-KG) levels and sub-clusters with differential levels of the oncometabolite 2-hydroxyglutarate (2HG). Sub-clusters characterised by high 2HG were enriched in higher tumour stages, suggesting metabolite profiles might be suitable predictors of tumour stage or survival. Bootstrap forest models based on single metabolite signatures showed that lactate, 2HG, citrate, aspartate, asparagine, and glutamine better predicted the cancer-specific survival (CSS) of clear cell RCC patients, whereas succinate and α-ketoglutarate were better CSS predictors for papillary RCC patients. Additionally, this assay identifies rare cases of tumours with SDHx mutations, which are caused predominantly by germline mutations and which predispose to development of different neoplasms. Hence, analysis of selected metabolites should be further evaluated for potential utility in liquid biopsies, which can be obtained using less invasive methods and potentially facilitate disease monitoring for both patients and caregivers. MDPI 2021-11-09 /pmc/articles/PMC8624007/ /pubmed/34822422 http://dx.doi.org/10.3390/metabo11110764 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
William, Doreen
Erdmann, Kati
Ottemöller, Jonas
Mangelis, Anastasios
Conrad, Catleen
Peitzsch, Mirko
Schröck, Evelin
Eisenhofer, Graeme
Zacharis, Aristeidis
Füssel, Susanne
Aust, Daniela
Klink, Barbara
Richter, Susan
Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort
title Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort
title_full Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort
title_fullStr Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort
title_full_unstemmed Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort
title_short Targeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort
title_sort targeted quantification of carbon metabolites identifies metabolic progression markers and an undiagnosed case of sdh-deficient clear cell renal cell carcinoma in a german cohort
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624007/
https://www.ncbi.nlm.nih.gov/pubmed/34822422
http://dx.doi.org/10.3390/metabo11110764
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