Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/219869
Title: Genomic landscape of follicular lymphoma across a wide spectrum of clinical behaviors.
Author: Mozas, Pablo
López González, Cristina
Grau Cuesta, Marta
Nadeu Prat, Ferran
Clot Razquin, Guillem
Valle, Sara
Kulis, Marta
Navarro López, Alba
Ramis Zaldivar, Joan Enric
González Farré. Blanca
Rivas Delgado, Alfredo
Rivero, Andrea
Frigola, Gerard
Balagué Ponz, Olga
Giné Soca, Eva
Delgado, Julio
Villamor i Casas, Neus
Matutes, Estella
Magnano, Laura
García Sanz, Ramón
Huet, Sarah
Russell. Robert B.
Campo Güerri, Elias
López Guillermo, Armando
Beà Bobet, Sílvia M.
Keywords: Limfomes
Genòmica
Pronòstic mèdic
Lymphomas
Genomics
Prognosis
Issue Date: 30-Mar-2023
Publisher: John Wiley & Sons
Abstract: While some follicular lymphoma (FL) patients do not require treatment or experience prolonged responses, others relapse early, and little is known about genetic alterations specific to patients with a particular clinical behavior. We selected 56 grade 1-3A FL patients according to their need of treatment or timing of relapse: never treated (n = 7), non-relapsed (19), late relapse (14), early relapse or POD24 (11), and primary refractory (5). We analyzed 56 diagnostic and 12 paired relapse lymphoid tissue biopsies and performed copy number alteration (CNA) analysis and next generation sequencing (NGS). We identified six focal driver losses (1p36.32, 6p21.32, 6q14.1, 6q23.3, 9p21.3, 10q23.33) and 1p36.33 copy-neutral loss of heterozygosity (CN-LOH). By integrating CNA and NGS results, the most frequently altered genes/regions were KMT2D (79%), CREBBP (67%), TNFRSF14 (46%) and BCL2 (40%). Although we found that mutations in PIM1, FOXO1 and TMEM30A were associated with an adverse clinical behavior, definitive conclusions cannot be drawn, due to the small sample size. We identified common precursor cells harboring early oncogenic alterations of the KMT2D, CREBBP, TNFRSF14 and EP300 genes and 16p13.3-p13.2 CN-LOH. Finally, we established the functional consequences of mutations by means of protein modeling (CD79B, PLCG2, PIM1, MCL1 and IRF8). These data expand the knowledge on the genomics behind the heterogeneous FL population and, upon replication in larger cohorts, could contribute to risk stratification and the development of targeted therapies.
Note: Reproducció del document publicat a: https://doi.org/10.1002/hon.3132
It is part of: Hematological Oncology, 2023, vol. 41, num.4, p. 631-643
URI: https://hdl.handle.net/2445/219869
Related resource: https://doi.org/10.1002/hon.3132
ISSN: 0278-0232
Appears in Collections:Articles publicats en revistes (Fonaments Clínics)
Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)

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