Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis

被引:0
作者
Abdellah Tebani
Jelena Jotanovic
Neda Hekmati
Åsa Sivertsson
Olafur Gudjonsson
Britt Edén Engström
Johan Wikström
Mathias Uhlèn
Olivera Casar-Borota
Fredrik Pontén
机构
[1] KTH-Royal Institute of Technology,Science for Life Laboratory, Department of Protein Science
[2] Normandie University,Department of Metabolic Biochemistry, UNIROUEN, INSERM U1245, CHU Rouen
[3] Uppsala University,Department of Immunology, Genetics and Pathology
[4] Uppsala University Hospital,Department of Clinical Pathology
[5] Uppsala University,Department of Neuroscience
[6] Uppsala University,Department of Medical Sciences, Endocrinology and Mineral Metabolism
[7] Uppsala University,Department of Surgical Sciences, Neuroradiology
来源
Acta Neuropathologica Communications | / 9卷
关键词
PitNET; Transcriptomics; RNA-seq; Pituitary adenoma; Pathology; Omics;
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摘要
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.
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