Immunohistochemical Profile of p62/SQSTM1/Sequestosome-1 in Human Low- and High-Grade Intracranial Meningiomas.
Antonio IeniCristina PizzimentiVincenzo FiorentinoMariausilia FranchinaAntonino GermanòGiovanni RaffaMaurizio MartiniGuido FaddaGiovanni TuccariPublished in: Analytical cellular pathology (Amsterdam) (2024)
Among autophagic-related proteins, p62/SQSTM1/Sequestosome-1 represents a relevant actor in cellular proliferation and neoplastic growth. Although, recently, p62 expression has been analyzed in different neurodegenerative and glial neoplastic diseases, no available information have been reported in meningiomas, which have an high epidemiological relevance being the second most common category of intracranial tumors after gliomas. Generally meningiomas have a benign behavior, but their recurrence is not uncommon mainly when atypical or anaplastic varieties occur. However, intranuclear vacuoles have been ultrastructurally observed in meningiomas, and they were labelled by p62 antibodies. Therefore, in the present study, we have investigated p62 immunohistochemical pattern in a cohort of 133 cases representative of low- and high-grade meningiomas, to verify if p62 expression may be related to clinicopathological data, thus achieving a potential prognostic role. The p62 immunoexpression was frequently found in the nucleus and cytoplasm of neoplastic elements, and utilizing an intensity-distribution score, 55 (41.3%) cases were considered as high expressors while 78 (58.7%) cases were instead recorded as low expressors. Fifteen cases exhibited recurrences of the disease, 14 of which were codified as high expressors. Moreover, a direct relationship between p62 and Mib-1 immunoexpression as well as between p62 and neoplastic grade have been documented. Finally, we suggest that impaired autophagic flux with an increase in p62 expression may be involved in the activation of NRF2 also contributing in the development of recurrence in meningioma patients.
Keyphrases
- high grade
- poor prognosis
- low grade
- end stage renal disease
- cell death
- endothelial cells
- binding protein
- newly diagnosed
- oxidative stress
- chronic kidney disease
- ejection fraction
- optic nerve
- peritoneal dialysis
- signaling pathway
- long non coding rna
- electronic health record
- risk assessment
- machine learning
- mass spectrometry
- health information
- patient reported outcomes
- optical coherence tomography
- artificial intelligence