Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

Chronic Lymphocytic Leukemia (CLL) is the most prevalent leukemia in Western countries and is notable for its variable clinical course. This variability is partly reflected by the mutational status of IGHV genes. Many CLL samples have been studied in recent years by next-generation sequencing. These studies have identified recurrent somatic mutations in NOTCH1, SF3B1, ATM, TP53, BIRC3 and others genes that play roles in cell cycle, DNA repair, RNA metabolism and splicing. In this study, we have taken a deep-targeted massive sequencing approach to analyze the impact of mutations in the most frequently mutated genes in patients with CLL enrolled in the REM (rituximab en mantenimiento) clinical trial. The mutational status of our patients with CLL, except for the TP53 gene, does not seem to affect the good results obtained with maintenance therapy with rituximab after front-line FCR treatment

Clonal dynamics monitoring during clinical evolution in chronic lymphocytic leukaemia

Chronic lymphocytic leukaemia is the most prevalent leukaemia in Western countries. It is an incurable disease characterized by a highly variable clinical course. Chronic lymphocytic leukaemia is an ideal model for studying clonal heterogeneity and dynamics during cancer progression, response to therapy and/or relapse because the disease usually develops over several years. Here we report an analysis by deep sequencing of sequential samples taken at different times from the affected organs of two patients with 12- and 7-year disease courses, respectively. One of the patients followed a linear pattern of clonal evolution, acquiring and selecting new mutations in response to salvage therapy and/or allogeneic transplantation, while the other suffered loss of cellular tumoral clones during progression and histological transformation.This work was supported by the Spanish Ministry of Economy and Competence (MINECO): SAF2013-47416-R; ISCIII-MINECO AES-FEDER (Plan Estatal de I + D + I 2008–2011 and 2013–2016) (PI14/00221 (MSB), PIE14/0064 (MSB), PIE15/0081 (MAP), PI16/01294 (MAP), CIBERONC CB16/12/00291 (MAP)), Madrid Autonomous Community, B2017/BMD3778 (MAP, MSB, FA-S), F Hoffmann-La Roche (JAGM); CNIO Bioinformatics Unit work has been supported by Marie-Curie Career Integration Grant CIG334361. J.G.-R. is a recipient of a i-PFIS predoctoral fellowship (IFI14/00003); NM was supported by AECC Scientific Foundation; S.D. was supported by the Torres Quevedo subprogramme (MICINN) under grant agreement PTQ-12-05391. K.T. and J.P.-P. are supported by Severo Ochoa FPI grant doctoral fellowship by the Spanish MINECO. MSB currently holds a Miguel Servet II contract (CPII16/00024) supported by ISCIII-MINECO AES-FEDER (Plan Estatal I + D + I 2013–2016) and the Fundación de Investigación Biomédica Puerta de Hierro