Somatostatin receptor tissue distribution in lung neuroendocrine tumours: A clinicopathologic and immunohistochemical study of 218 'clinically aggressive' cases

143Citations
Citations of this article
57Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: The management of pulmonary neuroendocrine tumours (NETs), with special reference to clinically aggressive carcinoids and large-cell neuroendocrine carcinomas (LCNECs), is poorly standardised and data about somatostatin receptor (SSTR) expression or therapeutic guidelines for somatostatin analogue administration are still debated. Materials and methods: A series of 218 lung NETs [24 metastatic typical carcinoids (TCs), 73 atypical carcinoids (ACs), 60 LCNECs and 61 surgically resected small-cell lung carcinomas] were investigated for SSTR types 2A and 3 tissue distribution using immunohistochemistry, in correlation with clinicopathologic parameters, outcome, scintigraphy and treatment. Results: SSTRs were heterogeneously distributed with a significant progressive decrease from low- to high-grade forms. SSTR type 2A was strikingly overexpressed in metastatic TCs as compared with ACs and clinically benign TCs. SSTR tissue immunolocalization correlated with octreotide scintigraphy in 20 of 28 cases. Conclusion: The immunohistochemical determination of SSTRs, with special reference to low-grade/intermediate-grade tumours, may assist the clinical approach with somatostatin analogue-based diagnostic and therapeutic procedures in clinically aggressive pulmonary NETs. © The Author 2009. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

Cite

CITATION STYLE

APA

Righi, L., Volante, M., Tavaglione, V., Billè, A., Daniele, L., Angusti, T., … Papotti, M. (2009). Somatostatin receptor tissue distribution in lung neuroendocrine tumours: A clinicopathologic and immunohistochemical study of 218 “clinically aggressive” cases. Annals of Oncology, 21(3), 548–555. https://doi.org/10.1093/annonc/mdp334

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free