Literature DB >> 32621052

Cyclin A in nonfunctioning pituitary adenomas.

Elisa B Lamback1, Alexandro Guterres2, Monique Alvares Barbosa3, Carlos Henrique de Azeredo Lima2, Debora Aparecida Silva2, Aline Helen da Silva Camacho2,4, Leila Chimelli2, Leandro Kasuki1,5,6, Mônica R Gadelha7,8,9.   

Abstract

PURPOSE: Assess cyclin A in nonfunctioning pituitary adenomas (NFPA) and compare its expression in non-invasive and non-proliferative tumors with invasive and proliferative tumors (12× higher risk of recurrence).
METHODS: Quantitative real time polymerase chain reaction to analyze cyclin A using normal pituitary gland as reference. Fold change (FC) > 1 was considered as increased. Tumor invasion was based on Knosp criteria (grades 3-4 considered invasive) and proliferation on the presence of at least two of three criteria: Ki-67 ≥ 3%; mitoses > 2/10; positive p53. Both groups were compared with Mann-Whitney test considering p value < 0.05 as statistically significant.
RESULTS: Thirty-one patients with NFPA were included. Tumors were mainly of gonadotrophic origin (74.2%), followed by corticotrophic (19.4%) and lactotrophic (3.2%) origins and null-cell adenomas (3.2%). Median tumor diameter was 3.5 cm (1.8-8.0) and Ki-67 was 3.0% (0.3-11%). Sixteen patients had tumors classified as non-invasive and non-proliferative and 15 as invasive and proliferative. Median FC was 0.31 in all tumors (0.13-1.94). Cyclin A was not related to invasion or proliferation (FC 0.41 in non-invasive and non-proliferative tumors and FC 0.30 in invasive and proliferative tumors; p = 0.968). Four (12.9%) patients had tumors that exhibited increased cyclin A [median FC of 1.04 (1.02-1.94)]-three of gonadotrophic origin and one null-cell adenoma, with two tumors classified as non-invasive and non-proliferative and two tumors classified as invasive and proliferative. Median tumor diameter in these samples was 3.4 cm (2.4-3.6) and Ki-67 was 5.1% (2-11%).
CONCLUSIONS: Cyclin A was increased in a minority of NFPA and does not seem to be related to invasion or proliferation.

Entities:  

Keywords:  Cyclin A; Invasion; Nonfunctioning pituitary adenomas; Proliferation; Tumorigenesis

Mesh:

Substances:

Year:  2020        PMID: 32621052     DOI: 10.1007/s12020-020-02402-5

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


  38 in total

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Authors:  Yong Chen; Cheng De Wang; Zhi Peng Su; Yun Xiang Chen; Lin Cai; Qi Chuan Zhuge; Zhe Bao Wu
Journal:  Neuroendocrinology       Date:  2012-08-28       Impact factor: 4.914

2.  Pathology of invasive pituitary tumors with special reference to functional classification.

Authors:  B W Scheithauer; K T Kovacs; E R Laws; R V Randall
Journal:  J Neurosurg       Date:  1986-12       Impact factor: 5.115

Review 3.  Genetics of pituitary adenomas.

Authors:  Monica R Gadelha; Giampaolo Trivellin; Laura Cristina Hernández Ramírez; Márta Korbonits
Journal:  Front Horm Res       Date:  2013-03-19       Impact factor: 2.606

4.  Hypopituitarism-needs modern individualized treatment.

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Journal:  Endocrine       Date:  2016-12-21       Impact factor: 3.633

5.  Subclinical adenomas in postmortem pituitaries: classification and correlations to clinical data.

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Review 6.  The 2017 World Health Organization classification of tumors of the pituitary gland: a summary.

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Journal:  Acta Neuropathol       Date:  2017-08-18       Impact factor: 17.088

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Journal:  Best Pract Res Clin Endocrinol Metab       Date:  2009-10       Impact factor: 4.690

Review 9.  Pathohistological classification of pituitary tumors: 10 years of experience with the German Pituitary Tumor Registry.

Authors:  Wolfgang Saeger; Dieter K Lüdecke; Michael Buchfelder; Rudolf Fahlbusch; Hans-Jürgen Quabbe; Stephan Petersenn
Journal:  Eur J Endocrinol       Date:  2007-02       Impact factor: 6.664

Review 10.  Apoplexy in nonfunctioning pituitary adenomas.

Authors:  Luiz Eduardo Wildemberg; Andrea Glezer; Marcello D Bronstein; Mônica R Gadelha
Journal:  Pituitary       Date:  2018-04       Impact factor: 4.107

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Journal:  Pituitary       Date:  2021-01-25       Impact factor: 4.107

2.  Prediction of high infiltration levels in pituitary adenoma using MRI-based radiomics and machine learning.

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