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Hematological oncology · 2023

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

СтатьяНазвание и аннотация: Перевод пока не подготовлен
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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

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты