Details

Autor(en) / Beteiligte

• Mozas, Pablo
• López, Cristina
• Grau, Marta
• Nadeu, Ferran
• Clot, Guillem
• Valle, Sara
• Kulis, Marta
• Navarro, Alba
• Ramis-Zaldivar, Joan Enric
• González-Farré, Blanca
• Rivas-Delgado, Alfredo
• Rivero, Andrea
• Frigola, Gerard
• Balagué, Olga
• Giné, Eva
• Delgado, Julio
• Villamor, Neus
• Matutes, Estella
• Magnano, Laura
• García-Sanz, Ramón
• Huet, Sarah
• Russell, Robert B
• Campo, Elías
• López-Guillermo, Armando
• Beà, Sílvia

Titel

Genomic landscape of follicular lymphoma across a wide spectrum of clinical behaviors

Ist Teil von

• Hematological oncology, 2023-10, Vol.41 (4), p.631-643

Ort / Verlag

England: Wiley Subscription Services, Inc

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Wiley Online Library - AutoHoldings Journals

Beschreibungen/Notizen

• 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.