Year: 2025
Type: article
Abstract: Introduction: The integration of laboratory and clinical technologies and knowledge is key to an accurate diagnosis of hematologic neoplasms.Over the past decade, next-generation sequencing (NGS) has enabled the molecular characterization of these diseases, identifying mutations, copy number variations, and recurrent fusion genes.This advancement has driven the update of recommendations for the diagnosis and management of patients with hematologic neoplasms.Recent classifications by the World Health Organization (WHO), the International Consensus Classification (ICC), and the European LeukemiaNet (ELN) highlight the relevance of genetic data, incorporating them into their diagnostic and risk stratification algorithms.In this context, the implementation of targeted NGS panels is recommended for their ability to simultaneously analyze multiple genetic alterations.Objective: Although NGS is available in many laboratories, its use is not yet standardized, and there is no clear consensus on the methodology or the genes to be evaluated for each pathology.Material and method: The Molecular Biology Group in Hematology (GBMH), in collaboration with a panel of experts, developed this consensus guide.Results: Genes of interest were compiled based on their clinical relevance and scientific evidence.Conclusions: This guide aims to assist professionals in the use of targeted NGS panels in lymphoplasmacytic lymphoma.
Source: Revista Sangre (ENG)
Institutions: Universidad de Salamanca, Instituto de Investigación Biomédica de Salamanca, Centro de Investigación del Cáncer, Centro de Investigación Biomédica en Red de Cáncer, Hospital General Universitario Gregorio Marañón, Complejo Hospitalario de Salamanca, Hospital Universitario 12 De Octubre, Hospital Universitari i Politècnic La Fe, Hospital Universitario de Gran Canaria Doctor Negrín, Hospital Clínic de Barcelona
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4417015286
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