: More than 90% of patients affected by mastocytosis are characterized by a somatic point mutation of KIT, which induces ligand-independent activation of the receptor and downstream signal triggering, ultimately leading to mast cell accumulation and survival. The most frequent mutation is KIT p.D816V, but other rarer mutations can also be found. These mutations often have a very low variant allele frequency (VAF), well below the sensitivity of common next-generation sequencing (NGS) methods used in routine diagnostic panels. Highly sensitive methods are developing for detecting mutations. This review summarizes the current indications on the recommended methods and on how to manage and interpret molecular data for the diagnosis and follow-up of patients with mastocytosis.

Detection of KIT Mutations in Systemic Mastocytosis: How, When, and Why

Cilloni, Daniela
;
Maffeo, Beatrice;Savi, Arianna;Danzero, Alice Costanza;Bonuomo, Valentina;Fava, Carmen
2024-01-01

Abstract

: More than 90% of patients affected by mastocytosis are characterized by a somatic point mutation of KIT, which induces ligand-independent activation of the receptor and downstream signal triggering, ultimately leading to mast cell accumulation and survival. The most frequent mutation is KIT p.D816V, but other rarer mutations can also be found. These mutations often have a very low variant allele frequency (VAF), well below the sensitivity of common next-generation sequencing (NGS) methods used in routine diagnostic panels. Highly sensitive methods are developing for detecting mutations. This review summarizes the current indications on the recommended methods and on how to manage and interpret molecular data for the diagnosis and follow-up of patients with mastocytosis.
2024
Inglese
Esperti anonimi
25
20
1
16
16
KIT; digital PCR; gene mutations; systemic mastocytosis
no
4 – prodotto già presente in altro archivio Open Access (arXiv, REPEC…)
6
03-CONTRIBUTO IN RIVISTA::03B-Review in Rivista / Rassegna della Lett. in Riv. / Nota Critica
open
262
info:eu-repo/semantics/article
Cilloni, Daniela; Maffeo, Beatrice; Savi, Arianna; Danzero, Alice Costanza; Bonuomo, Valentina; Fava, Carmen
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2028877
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