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:	Doreen William, Kati Erdmann, Jonas Ottemöller, Anastasios Mangelis, Catleen Conrad, Mirko Peitzsch, Evelin Schröck, Graeme Eisenhofer, Aristeidis Zacharis, Susanne Füssel, Daniela Aust, Barbara Klink, Susan Richter
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Krebs cycle metabolic profiling renal cell carcinoma subtypes survival analysis succinate dehydrogenase mutations Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/737c8718eab247f0abc5488e82bb525a
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spelling	oai:doaj.org-article:737c8718eab247f0abc5488e82bb525a2021-11-25T18:20:45ZTargeted Quantification of Carbon Metabolites Identifies Metabolic Progression Markers and an Undiagnosed Case of SDH-Deficient Clear Cell Renal Cell Carcinoma in a German Cohort10.3390/metabo111107642218-1989https://doaj.org/article/737c8718eab247f0abc5488e82bb525a2021-11-01T00:00:00Zhttps://www.mdpi.com/2218-1989/11/11/764https://doaj.org/toc/2218-1989Renal 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 <i>SDHx</i> 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.Doreen WilliamKati ErdmannJonas OttemöllerAnastasios MangelisCatleen ConradMirko PeitzschEvelin SchröckGraeme EisenhoferAristeidis ZacharisSusanne FüsselDaniela AustBarbara KlinkSusan RichterMDPI AGarticleKrebs cyclemetabolic profilingrenal cell carcinomasubtypessurvival analysissuccinate dehydrogenase mutationsMicrobiologyQR1-502ENMetabolites, Vol 11, Iss 764, p 764 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Krebs cycle metabolic profiling renal cell carcinoma subtypes survival analysis succinate dehydrogenase mutations Microbiology QR1-502
spellingShingle	Krebs cycle metabolic profiling renal cell carcinoma subtypes survival analysis succinate dehydrogenase mutations Microbiology QR1-502 Doreen William Kati Erdmann Jonas Ottemöller Anastasios Mangelis Catleen Conrad Mirko Peitzsch Evelin Schröck Graeme Eisenhofer Aristeidis Zacharis Susanne Füssel Daniela Aust Barbara Klink Susan Richter 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
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 <i>SDHx</i> 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.
format	article
author	Doreen William Kati Erdmann Jonas Ottemöller Anastasios Mangelis Catleen Conrad Mirko Peitzsch Evelin Schröck Graeme Eisenhofer Aristeidis Zacharis Susanne Füssel Daniela Aust Barbara Klink Susan Richter
author_facet	Doreen William Kati Erdmann Jonas Ottemöller Anastasios Mangelis Catleen Conrad Mirko Peitzsch Evelin Schröck Graeme Eisenhofer Aristeidis Zacharis Susanne Füssel Daniela Aust Barbara Klink Susan Richter
author_sort	Doreen William
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_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_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_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
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/737c8718eab247f0abc5488e82bb525a
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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

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