Pheo-Type: A Diagnostic Gene-expression Assay for the Classification of Pheochromocytoma and Paraganglioma.

Flynn, A; Dwight, T; Harris, J; Benn, D; Zhou, L; Hogg, A; Catchpoole, D; James, P; Duncan, EL; Trainer, A; Gill, AJ; Clifton-Bligh, R; Hicks, RJ; Tothill, RW

Pheo-Type: A Diagnostic Gene-expression Assay for the Classification of Pheochromocytoma and Paraganglioma.

Flynn, A Dwight, T Harris, J Benn, D Zhou, L Hogg, A Catchpoole, D

James, P Duncan, EL Trainer, A Gill, AJ Clifton-Bligh, R Hicks, RJ Tothill, RW

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Publisher:: The Endocrine Society
Publication Type:: Journal Article
Citation:: J Clin Endocrinol Metab, 2016, 101, (3), pp. 1034-1043
Issue Date:: 2016-03

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Field	Value	Language
dc.contributor.author	Flynn, A
dc.contributor.author	Dwight, T
dc.contributor.author	Harris, J
dc.contributor.author	Benn, D
dc.contributor.author	Zhou, L
dc.contributor.author	Hogg, A
dc.contributor.author	Catchpoole, D https://orcid.org/0000-0001-5836-1413
dc.contributor.author	James, P
dc.contributor.author	Duncan, EL
dc.contributor.author	Trainer, A
dc.contributor.author	Gill, AJ
dc.contributor.author	Clifton-Bligh, R
dc.contributor.author	Hicks, RJ
dc.contributor.author	Tothill, RW
dc.date.accessioned	2022-08-11T00:52:59Z
dc.date.available	2022-08-11T00:52:59Z
dc.date.issued	2016-03
dc.identifier.citation	J Clin Endocrinol Metab, 2016, 101, (3), pp. 1034-1043
dc.identifier.issn	0021-972X
dc.identifier.issn	1945-7197
dc.identifier.uri	http://hdl.handle.net/10453/159891
dc.description.abstract	CONTEXT: Pheochromocytomas and paragangliomas (PPGLs) are heritable neoplasms that can be classified into gene-expression subtypes corresponding to their underlying specific genetic drivers. OBJECTIVE: This study aimed to develop a diagnostic and research tool (Pheo-type) capable of classifying PPGL tumors into gene-expression subtypes that could be used to guide and interpret genetic testing, determine surveillance programs, and aid in elucidation of PPGL biology. DESIGN: A compendium of published microarray data representing 205 PPGL tumors was used for the selection of subtype-specific genes that were then translated to the Nanostring gene-expression platform. A support vector machine was trained on the microarray dataset and then tested on an independent Nanostring dataset representing 38 familial and sporadic cases of PPGL of known genotype (RET, NF1, TMEM127, MAX, HRAS, VHL, and SDHx). Different classifier models involving between three and six subtypes were compared for their discrimination potential. RESULTS: A gene set of 46 genes and six endogenous controls was selected representing six known PPGL subtypes; RTK1-3 (RET, NF1, TMEM127, and HRAS), MAX-like, VHL, and SDHx. Of 38 test cases, 34 (90%) were correctly predicted to six subtypes based on the known genotype to gene-expression subtype association. Removal of the RTK2 subtype from training, characterized by an admixture of tumor and normal adrenal cortex, improved the classification accuracy (35/38). Consolidation of RTK and pseudohypoxic PPGL subtypes to four- and then three-class architectures improved the classification accuracy for clinical application. CONCLUSIONS: The Pheo-type gene-expression assay is a reliable method for predicting PPGL genotype using routine diagnostic tumor samples.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	The Endocrine Society
dc.relation.ispartof	J Clin Endocrinol Metab
dc.relation.isbasedon	10.1210/jc.2015-3889
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	1103 Clinical Sciences, 1114 Paediatrics and Reproductive Medicine
dc.subject.classification	Endocrinology & Metabolism
dc.subject.mesh	Adrenal Gland Neoplasms
dc.subject.mesh	Gene Expression
dc.subject.mesh	Genetic Predisposition to Disease
dc.subject.mesh	Genotype
dc.subject.mesh	Humans
dc.subject.mesh	Membrane Proteins
dc.subject.mesh	Mutation
dc.subject.mesh	Neurofibromin 1
dc.subject.mesh	Paraganglioma
dc.subject.mesh	Pheochromocytoma
dc.subject.mesh	Proto-Oncogene Proteins c-ret
dc.subject.mesh	Proto-Oncogene Proteins p21(ras)
dc.subject.mesh	RNA
dc.subject.mesh	Succinate Dehydrogenase
dc.subject.mesh	Von Hippel-Lindau Tumor Suppressor Protein
dc.subject.mesh	Humans
dc.subject.mesh	Paraganglioma
dc.subject.mesh	Pheochromocytoma
dc.subject.mesh	Adrenal Gland Neoplasms
dc.subject.mesh	Genetic Predisposition to Disease
dc.subject.mesh	Succinate Dehydrogenase
dc.subject.mesh	Neurofibromin 1
dc.subject.mesh	Membrane Proteins
dc.subject.mesh	RNA
dc.subject.mesh	Gene Expression
dc.subject.mesh	Genotype
dc.subject.mesh	Mutation
dc.subject.mesh	Proto-Oncogene Proteins p21(ras)
dc.subject.mesh	Proto-Oncogene Proteins c-ret
dc.subject.mesh	Von Hippel-Lindau Tumor Suppressor Protein
dc.title	Pheo-Type: A Diagnostic Gene-expression Assay for the Classification of Pheochromocytoma and Paraganglioma.
dc.type	Journal Article
utslib.citation.volume	101
utslib.location.activity	United States
utslib.for	1103 Clinical Sciences
utslib.for	1114 Paediatrics and Reproductive Medicine
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2022-08-11T00:52:57Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	101
utslib.citation.issue	3

Abstract:

CONTEXT: Pheochromocytomas and paragangliomas (PPGLs) are heritable neoplasms that can be classified into gene-expression subtypes corresponding to their underlying specific genetic drivers. OBJECTIVE: This study aimed to develop a diagnostic and research tool (Pheo-type) capable of classifying PPGL tumors into gene-expression subtypes that could be used to guide and interpret genetic testing, determine surveillance programs, and aid in elucidation of PPGL biology. DESIGN: A compendium of published microarray data representing 205 PPGL tumors was used for the selection of subtype-specific genes that were then translated to the Nanostring gene-expression platform. A support vector machine was trained on the microarray dataset and then tested on an independent Nanostring dataset representing 38 familial and sporadic cases of PPGL of known genotype (RET, NF1, TMEM127, MAX, HRAS, VHL, and SDHx). Different classifier models involving between three and six subtypes were compared for their discrimination potential. RESULTS: A gene set of 46 genes and six endogenous controls was selected representing six known PPGL subtypes; RTK1-3 (RET, NF1, TMEM127, and HRAS), MAX-like, VHL, and SDHx. Of 38 test cases, 34 (90%) were correctly predicted to six subtypes based on the known genotype to gene-expression subtype association. Removal of the RTK2 subtype from training, characterized by an admixture of tumor and normal adrenal cortex, improved the classification accuracy (35/38). Consolidation of RTK and pseudohypoxic PPGL subtypes to four- and then three-class architectures improved the classification accuracy for clinical application. CONCLUSIONS: The Pheo-type gene-expression assay is a reliable method for predicting PPGL genotype using routine diagnostic tumor samples.

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http://hdl.handle.net/10453/159891