Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization

Summary: Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and genomics data in supervised machine-lear...

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Autores principales:	Tuyana Boldanova, Geoffrey Fucile, Jan Vosshenrich, Aleksei Suslov, Caner Ercan, Mairene Coto-Llerena, Luigi M. Terracciano, Christoph J. Zech, Daniel T. Boll, Stefan Wieland, Markus H. Heim
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	liver cancer locoregional treatment hepatocellular carcinoma transarterial chemoembolisation biomarker Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/24d4d9cd9de347eb9e55f10515c24c82
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spelling	oai:doaj.org-article:24d4d9cd9de347eb9e55f10515c24c822021-11-18T04:52:12ZSupervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization2666-379110.1016/j.xcrm.2021.100444https://doaj.org/article/24d4d9cd9de347eb9e55f10515c24c822021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666379121003128https://doaj.org/toc/2666-3791Summary: Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and genomics data in supervised machine-learning models toward the development of a clinically applicable predictive classifier of response to TACE in HCC patients. Our study consists of a discovery cohort of 33 tumors through which we identify predictive biomarkers, which are confirmed in a validation cohort. We find that radiological assessment of tumor area and several transcriptomic signatures, primarily the expression of FAM111B and HPRT1, are most predictive of response to TACE. Logistic regression decision support models consisting of tumor area and RNA-seq gene expression estimates for FAM111B and HPRT1 yield a predictive accuracy of ∼90%. Reverse transcription droplet digital PCR (RT-ddPCR) confirms these genes in combination with tumor area as a predictive classifier for response to TACE.Tuyana BoldanovaGeoffrey FucileJan VosshenrichAleksei SuslovCaner ErcanMairene Coto-LlerenaLuigi M. TerraccianoChristoph J. ZechDaniel T. BollStefan WielandMarkus H. HeimElsevierarticleliver cancerlocoregional treatmenthepatocellular carcinomatransarterial chemoembolisationbiomarkerMedicine (General)R5-920ENCell Reports Medicine, Vol 2, Iss 11, Pp 100444- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	liver cancer locoregional treatment hepatocellular carcinoma transarterial chemoembolisation biomarker Medicine (General) R5-920
spellingShingle	liver cancer locoregional treatment hepatocellular carcinoma transarterial chemoembolisation biomarker Medicine (General) R5-920 Tuyana Boldanova Geoffrey Fucile Jan Vosshenrich Aleksei Suslov Caner Ercan Mairene Coto-Llerena Luigi M. Terracciano Christoph J. Zech Daniel T. Boll Stefan Wieland Markus H. Heim Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
description	Summary: Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and genomics data in supervised machine-learning models toward the development of a clinically applicable predictive classifier of response to TACE in HCC patients. Our study consists of a discovery cohort of 33 tumors through which we identify predictive biomarkers, which are confirmed in a validation cohort. We find that radiological assessment of tumor area and several transcriptomic signatures, primarily the expression of FAM111B and HPRT1, are most predictive of response to TACE. Logistic regression decision support models consisting of tumor area and RNA-seq gene expression estimates for FAM111B and HPRT1 yield a predictive accuracy of ∼90%. Reverse transcription droplet digital PCR (RT-ddPCR) confirms these genes in combination with tumor area as a predictive classifier for response to TACE.
format	article
author	Tuyana Boldanova Geoffrey Fucile Jan Vosshenrich Aleksei Suslov Caner Ercan Mairene Coto-Llerena Luigi M. Terracciano Christoph J. Zech Daniel T. Boll Stefan Wieland Markus H. Heim
author_facet	Tuyana Boldanova Geoffrey Fucile Jan Vosshenrich Aleksei Suslov Caner Ercan Mairene Coto-Llerena Luigi M. Terracciano Christoph J. Zech Daniel T. Boll Stefan Wieland Markus H. Heim
author_sort	Tuyana Boldanova
title	Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
title_short	Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
title_full	Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
title_fullStr	Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
title_full_unstemmed	Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
title_sort	supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/24d4d9cd9de347eb9e55f10515c24c82
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Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization

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