Identification of novel neuroblastoma biomarkers in urine samples

Abstract Urine is a complex liquid containing numerous small molecular metabolites. The ability to non-invasively test for cancer biomarkers in urine is especially beneficial for screening child patients. This study attempted to identify neuroblastoma biomarkers by comprehensively analysing urinary...

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Autores principales:	Kazuki Yokota, Hiroo Uchida, Minoru Sakairi, Mayumi Abe, Yujiro Tanaka, Takahisa Tainaka, Chiyoe Shirota, Wataru Sumida, Kazuo Oshima, Satoshi Makita, Hizuru Amano, Akinari Hinoki
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c32edc81ed5a4d7c98de512961cdbfdc
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spelling	oai:doaj.org-article:c32edc81ed5a4d7c98de512961cdbfdc2021-12-02T12:11:50ZIdentification of novel neuroblastoma biomarkers in urine samples10.1038/s41598-021-83619-w2045-2322https://doaj.org/article/c32edc81ed5a4d7c98de512961cdbfdc2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83619-whttps://doaj.org/toc/2045-2322Abstract Urine is a complex liquid containing numerous small molecular metabolites. The ability to non-invasively test for cancer biomarkers in urine is especially beneficial for screening child patients. This study attempted to identify neuroblastoma biomarkers by comprehensively analysing urinary metabolite samples from children. A total of 87 urine samples were collected from 54 participants (15 children with neuroblastoma and 39 without cancer) and used to perform a comprehensive analysis. Urine metabolites were extracted using liquid chromatography/mass spectrometry and analysed by Metabolon, Inc. Biomarker candidates were extracted using the Wilcoxon rank sum test, random forest method (RF), and orthogonal partial least squares discriminant analysis (OPLS-DA). RF identified three important metabolic pathways in 15 samples from children with neuroblastoma. One metabolite was selected from each of the three identified pathways and combined to create a biomarker candidate (3-MTS, CTN, and COR) that represented each of the three pathways; using this candidate, all 15 cases were accurately distinguishable from the control group. Two cases in which known biomarkers were negative tested positive using this new biomarker. Furthermore, the predictive value did not decrease in cases with a low therapeutic effect. This approach could be effectively applied to identify biomarkers for other cancer types.Kazuki YokotaHiroo UchidaMinoru SakairiMayumi AbeYujiro TanakaTakahisa TainakaChiyoe ShirotaWataru SumidaKazuo OshimaSatoshi MakitaHizuru AmanoAkinari HinokiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kazuki Yokota Hiroo Uchida Minoru Sakairi Mayumi Abe Yujiro Tanaka Takahisa Tainaka Chiyoe Shirota Wataru Sumida Kazuo Oshima Satoshi Makita Hizuru Amano Akinari Hinoki Identification of novel neuroblastoma biomarkers in urine samples
description	Abstract Urine is a complex liquid containing numerous small molecular metabolites. The ability to non-invasively test for cancer biomarkers in urine is especially beneficial for screening child patients. This study attempted to identify neuroblastoma biomarkers by comprehensively analysing urinary metabolite samples from children. A total of 87 urine samples were collected from 54 participants (15 children with neuroblastoma and 39 without cancer) and used to perform a comprehensive analysis. Urine metabolites were extracted using liquid chromatography/mass spectrometry and analysed by Metabolon, Inc. Biomarker candidates were extracted using the Wilcoxon rank sum test, random forest method (RF), and orthogonal partial least squares discriminant analysis (OPLS-DA). RF identified three important metabolic pathways in 15 samples from children with neuroblastoma. One metabolite was selected from each of the three identified pathways and combined to create a biomarker candidate (3-MTS, CTN, and COR) that represented each of the three pathways; using this candidate, all 15 cases were accurately distinguishable from the control group. Two cases in which known biomarkers were negative tested positive using this new biomarker. Furthermore, the predictive value did not decrease in cases with a low therapeutic effect. This approach could be effectively applied to identify biomarkers for other cancer types.
format	article
author	Kazuki Yokota Hiroo Uchida Minoru Sakairi Mayumi Abe Yujiro Tanaka Takahisa Tainaka Chiyoe Shirota Wataru Sumida Kazuo Oshima Satoshi Makita Hizuru Amano Akinari Hinoki
author_facet	Kazuki Yokota Hiroo Uchida Minoru Sakairi Mayumi Abe Yujiro Tanaka Takahisa Tainaka Chiyoe Shirota Wataru Sumida Kazuo Oshima Satoshi Makita Hizuru Amano Akinari Hinoki
author_sort	Kazuki Yokota
title	Identification of novel neuroblastoma biomarkers in urine samples
title_short	Identification of novel neuroblastoma biomarkers in urine samples
title_full	Identification of novel neuroblastoma biomarkers in urine samples
title_fullStr	Identification of novel neuroblastoma biomarkers in urine samples
title_full_unstemmed	Identification of novel neuroblastoma biomarkers in urine samples
title_sort	identification of novel neuroblastoma biomarkers in urine samples
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c32edc81ed5a4d7c98de512961cdbfdc
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Identification of novel neuroblastoma biomarkers in urine samples

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