Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis

Abstract Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main tra...

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Autores principales:	Abdellah Tebani, Jelena Jotanovic, Neda Hekmati, Åsa Sivertsson, Olafur Gudjonsson, Britt Edén Engström, Johan Wikström, Mathias Uhlèn, Olivera Casar-Borota, Fredrik Pontén
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	PitNET Transcriptomics RNA-seq Pituitary adenoma Pathology Omics Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/9310c583b1f143c397522ca78e786048
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spelling	oai:doaj.org-article:9310c583b1f143c397522ca78e7860482021-11-14T12:11:12ZAnnotation of pituitary neuroendocrine tumors with genome-wide expression analysis10.1186/s40478-021-01284-62051-5960https://doaj.org/article/9310c583b1f143c397522ca78e7860482021-11-01T00:00:00Zhttps://doi.org/10.1186/s40478-021-01284-6https://doaj.org/toc/2051-5960Abstract Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.Abdellah TebaniJelena JotanovicNeda HekmatiÅsa SivertssonOlafur GudjonssonBritt Edén EngströmJohan WikströmMathias UhlènOlivera Casar-BorotaFredrik PonténBMCarticlePitNETTranscriptomicsRNA-seqPituitary adenomaPathologyOmicsNeurology. Diseases of the nervous systemRC346-429ENActa Neuropathologica Communications, Vol 9, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	PitNET Transcriptomics RNA-seq Pituitary adenoma Pathology Omics Neurology. Diseases of the nervous system RC346-429
spellingShingle	PitNET Transcriptomics RNA-seq Pituitary adenoma Pathology Omics Neurology. Diseases of the nervous system RC346-429 Abdellah Tebani Jelena Jotanovic Neda Hekmati Åsa Sivertsson Olafur Gudjonsson Britt Edén Engström Johan Wikström Mathias Uhlèn Olivera Casar-Borota Fredrik Pontén Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
description	Abstract Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.
format	article
author	Abdellah Tebani Jelena Jotanovic Neda Hekmati Åsa Sivertsson Olafur Gudjonsson Britt Edén Engström Johan Wikström Mathias Uhlèn Olivera Casar-Borota Fredrik Pontén
author_facet	Abdellah Tebani Jelena Jotanovic Neda Hekmati Åsa Sivertsson Olafur Gudjonsson Britt Edén Engström Johan Wikström Mathias Uhlèn Olivera Casar-Borota Fredrik Pontén
author_sort	Abdellah Tebani
title	Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
title_short	Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
title_full	Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
title_fullStr	Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
title_full_unstemmed	Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
title_sort	annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
publisher	BMC
publishDate	2021
url	https://doaj.org/article/9310c583b1f143c397522ca78e786048
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Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis

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