A Novel Strategy for the Diagnosis of Pulmonary High-Grade Neuroendocrine Tumor.
high-grade neuroendocrine tumor
immunostaining
large cell neuroendocrine tumor
small cell lung cancer
stathmin-1
Journal
Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402
Informations de publication
Date de publication:
20 Oct 2021
20 Oct 2021
Historique:
received:
23
08
2021
revised:
05
10
2021
accepted:
15
10
2021
entrez:
27
11
2021
pubmed:
28
11
2021
medline:
28
11
2021
Statut:
epublish
Résumé
Correctly diagnosing a histologic type of lung cancer is important for selecting the appropriate treatment because the aggressiveness, chemotherapy regimen, surgical approach, and prognosis vary significantly among histologic types. Pulmonary NETs, which are characterized by neuroendocrine morphologies, represent approximately 20% of all lung cancers. In particular, high-grade neuroendocrine tumors (small cell lung cancer and large cell neuroendocrine tumor) are highly proliferative cancers that have a poorer prognosis than other non-small cell lung cancers. The combination of hematoxylin and eosin staining, Ki-67, and immunostaining of classic neuroendocrine markers, such as chromogranin A, CD56, and synaptophysin, are normally used to diagnose high-grade neuroendocrine tumors; however, they are frequently heterogeneous. This article reviews the diagnostic methods of lung cancer diagnosis focused on immunostaining. In particular, we describe the usefulness of immunostaining by Stathmin-1, which is a cytosolic phosphoprotein and a key regulator of cell division due to its microtubule depolymerization in a phosphorylation-dependent manner, for the diagnosis of high-grade neuroendocrine tumors.
Identifiants
pubmed: 34829292
pii: diagnostics11111945
doi: 10.3390/diagnostics11111945
pmc: PMC8625242
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Subventions
Organisme : Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (JSPS)
ID : 19K07726
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