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Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Normandie Univ, Dept Metab Biochem, UNIROUEN, INSERM,U1245,CHU Rouen, F-76000 Rouen, France..ORCID iD: 0000-0002-8901-2678
Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden.;Uppsala Univ Hosp, Dept Clin Pathol, Uppsala, Sweden..
Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.ORCID iD: 0000-0001-8800-8469
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2021 (English)In: Acta neuropathologica communications, E-ISSN 2051-5960, Vol. 9, no 1, article id 181Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature , 2021. Vol. 9, no 1, article id 181
Keywords [en]
PitNET, Transcriptomics, RNA-seq, Pituitary adenoma, Pathology, Omics
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:kth:diva-305338DOI: 10.1186/s40478-021-01284-6ISI: 000716931700001PubMedID: 34758873Scopus ID: 2-s2.0-85118861789OAI: oai:DiVA.org:kth-305338DiVA, id: diva2:1614625
Note

QC 20211126

Available from: 2021-11-26 Created: 2021-11-26 Last updated: 2023-12-07Bibliographically approved

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Abdellah, TebaniSivertsson, ÅsaUhlén, Mathias

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