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Competing Interests: Thomas Chatzikonstantinou received honoraria from AbbVie. Lydia Scarfò received honoraria from AbbVie, AstraZeneca, BeiGene, Lilly, Janssen, Octapharma. Gloria Iacoboni received honoraria and travel support from Novartis, Kite/Gilead, Bristol‐Myers Squibb, Abbvie, Autolus, Miltenyi, and AstraZeneca. Rosa Collado received support for attending meetings from Janssen‐Cilag and S.A. Sara Galimberti received honoraria support for attending meetings from AbbVie, AstraZeneca, Jazz, Novartis, and Incyte, honoraria from Roche, Celgene, Pfizer, and Janssen, and support for attending meetings from Jazz, AstraZeneca, and Roche. Romain Guieze received honoraria, consulting fees, and support for attending meetings from AbbVie, Beigene, Roche, Janssen, and AstraZeneca. Eleftheria Hatzimichael received honoraria from AbbVie, Janssen‐Cilag, AstraZeneca, and Roche. Yair Herishanu received honoraria from Janssen, AbbVie, Roche, AstraZeneca, Medion, and Lilly. José‐Ángel Hernández‐Rivas received honoraria as a consultant from Janssen, AbbVie, AstraZeneca, Lilly, and BeiGene and support for attending meetings from Janssen, AbbVie, AstraZeneca, and BeiGene. Ozren Jaksic received honoraria from Johnson and Johnson, AstraZeneca, and Lilly, honoraria from Johnson and Johnson, AbbVie, AstraZeneca, and Lilly, and support for attending meetings from Johnson and Johnson, and AbbVie. Kamel Laribi received consulting fees from AbbVie, AstraZeneca, Janssen, Beigene, Takeda, and Novartis. Maya Koren‐Michowitz received honoraria from Novartis, Pfizer, and Gad Medical LTD. and support for attending meetings from Novartis. Arnon P. Kater received advisory board fees and research money from Janssen, AbbVie, BMS, AstraZeneca, and Roche/Genentech, and support for attending meetings from Janssen and AbbVie. Ioannis Kotsianidis received honoraria and consulting fees from AbbVie and Janssen. Ivana Milosevic received honoraria from AbbVie, Roche, Sandoz, AstraZeneca, and Janssen, and support for attending meetings from AbbVie, Roche, and Takeda. Almudena Navarro‐Bailón received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, Takeda, Janssen, and Beigene. Jacopo Olivieri received honoraria from AbbVie, AstraZeneca, and Janssen. Gianluigi Reda received consulting fees from AbbVie, AstraZeneca, Janssen, and Beigene, and is currently employed by AstraZeneca. Gian M. Rigolin received honoraria for participation in speaker's bureau from AbbVie, Astra Zeneca, Beigene, and Janssen, and support for attending meetings from Janssen. Mattia Schipani received honoraria and support for attending meetings from AstraZeneca, AbbVie, and Janssen‐Cilag and owns shares of stock in AbbVie, AstraZeneca, Merck, Eli Lilly, Sanofi, Johnson and Johnson, Pfizer, Gilead, and GSK. Tereza Shokralla and Stephan Stilgenbauer reports research funding from, consultancy or advisory role for, honoraria from, speakers' bureau participation for, and travel support from AbbVie, Amgen, AstraZeneca, BeiGene, Bristol Myers Squibb, Celgene, Gilead, GlaxoSmithKline, Hoffmann‐La Roche, Incyte, Infinity, Janssen, Novartis, and Sunesis. Eric Tse received support for attending meetings from Takeda. Theodoros Vassilakopoulos received honoraria from Takeda, Roche, Genesis Pharma, Merck, Novartis, Gilead, Sandoz, AstraZeneca, Integris, and Servier, and support for attending meetings from Takeda, Roche, Genesis Pharma, Merck, Pfizer, and Winmedica. Candida Vitale received honoraria from AbbVie, consulting fees from AstraZeneca, and support for attending meetings from AstraZeneca, Takeda, and Janssen. Renata Walewska received honoraria from AbbVie, AstraZeneca, and Beigene, support for attending meetings from Janssen, AbbVie, and AstraZeneca, and advisory board fees from AbbVie, AstraZeneca, Janssen, Beigene, and SecuraBio. Lucrecia Yañez received honoraria from AbbVie, AstraZeneca, Novartis, Gilead, Janssen, Jazz, MSD, and Pfizer, support for attending meetings from AbbVie, AstraZeneca, Gilead, Janssen, and Pfizer, and advisory board fees from AbbVie, AstraZeneca, Jazz, Janssen, Beigene, and Celgene. Francesc Bosch received consulting fees, honoraria, and payment for expert testimony from AbbVie, Genentech, Novartis, Takeda, Janssen, Roche, Mundipharma, Celgene/BMS, AstraZeneca, Lilly, Beigene, Gilead and TG Therapeutics, Advantage Allogene, Lava Therapeutics, and Enterome. Stephen Mulligan received advisory board fees from AbbVie, AstraZeneca, Janssen, Roche, and BeiGene. Maria Angelopoulou received consulting fees from AbbVie, Takeda, Janssen, Roche, Genesis, Gilead, and Amgen and honoraria from AbbVie, Takeda, Roche, Genesis, Gilead, and Novartis. Fatih Demirkan received support for attending meetings from Janssen and AbbVie. Tomas Papajík received honoraria and advisory board fees from AbbVie, Janssen‐Cilag, and AstraZeneca, and support for attending meetings from AstraZeneca. Marta Coscia received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, and Janssen. Constantine Tam received honoraria from AbbVie, Beigene, Janssen, and LOXO. Antonio Cuneo received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, Beigene, Janssen, and Lilly. Gianluca Gaidano received honoraria from Abbvie, AstraZeneca, BeiGene, Hikma, Incyte, Janssen, and Lilly. Niki Stavroyianni received honoraria from Janssen, AbbVie, AstraZeneca, and Lilly, and support for attending meetings from Janssen and AstraZeneca. Lukas Smolej received consulting fees, honoraria, and support for attending meetings from AbbVie, AstraZeneca, and Janssen and advisory board fees from AbbVie and AstraZeneca. Martin Spacek received honoraria and consulting and advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, and Janssen. Michael Doubek received research support and honoraria from AbbVie, AstraZeneca, and Janssen. Eugene Nikitin received honoraria from AbbVie. Kostas Stamatopoulos received research support from AbbVie, AstraZeneca, Janssen, Novartis, and Roche; honoraria from AbbVie, AstraZeneca, Bristol Myers Squibb, Lilly, and Janssen. Paolo Ghia received research support from AbbVie, AstraZeneca, BMS, Janssen and honoraria from AbbVie, AstraZeneca, BeiGene, BMS, Galapagos, Genmab, Janssen, Loxo Oncology @Lilly, MSD, Roche, and is an Editor of HemaSphere. Georgios Karakatsoulis, Eva Minga, Dimitra Chamou, Jana Kotaskova, Christos Demosthenous, Elisa Albi, Miguel Alcoceba, Salem Al‐Shemari, Thérèse Aurran‐Schleinitz, Francesca Bacchiarri, Sofia Chatzileontiadou, Zadie Davis, Marcos Daniel de Deus Santos, Maria Dimou, Elena Dmitrieva, David Donaldson, Gimena Dos Santos, Barbara Dreta, Maria Efstathopoulou, Shaimaa El‐Ashwah, Alicia Enrico, Andrzej Frygier, Andrea Galitzia, Eva Gimeno, Valerio Guarente, Sean Harrop, Elżbieta Kalicińska, Volkan Karakus, Bonnie Kho, Maria Kislova, Εliana Konstantinou, Zuzana Kubova, Jorge Labrador, Deepesh Lad, Luca Laurenti, Thomas Longval, Alberto Lopez‐Garcia, Juan Marquet, Stanislava Maslejova, Carlota Mayor‐Bastida, Biljana Mihaljevic, Fatima Miras, Riccardo Moia, Marta Morawska, Uttam K. Nath, Irina Panovska‐Stavridis, Maria Papaioannou, Cheyenne Pierie, Anna Puiggros, Rosa Ruchlemer, Annett Schiwitza, Yandong Shen, Tereza Shokralla, Martin Simkovic, Svetlana Smirnova, Dina S. A. Soliman, Tamar Tadmor, Kristina Tomic, Andrea Visentin, George Vrachiolias, Vojin Vukovic, Zhenshu Xu, Munci Yagci, Mohamed Yassin, Jana Zuchnicka, David Oscier, Alessandro Gozzetti, Panagiotis Panagiotidis, Blanca Espinet, Paolo Sportoletti, Gerassimos A. Pangalis, Viola M. Popov, Bella Biderman, Roberta Murru, Rainer Claus, Livio Trentin, Darko Antic, Olga B. Kalashnikova, Mark Catherwood, Sarka Pospisilova, and Anastasia Chatzidimitriou have no conflict of interest to disclose.

Background: Patients with chronic lymphocytic leukemia (CLL) have a higher risk of developing other malignancies (OMs) compared to the general population. However, the impact of CLL-related risk factors and CLL-directed treatment is still unclear and represents the focus of this work., Methods: We conducted a retrospective international multicenter study to assess the incidence of OMs and detect potential risk factors in 19,705 patients with CLL, small lymphocytic lymphoma, or high-count CLL-like monoclonal B-cell lymphocytosis, diagnosed between 2000 and 2016. Data collection took place between October 2020 and March 2022., Findings: In 129,254 years of follow-up after CLL diagnosis, 3513 OMs were diagnosed (27.2 OMs/1000 person-years). The most common hematological OMs were Richter transformation, myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Non-melanoma skin (NMSC) and prostate cancers were the most common solid tumors (STs).The only predictor for MDS and AML development was treatment with fludarabine and cyclophosphamide with/without rituximab (FC ± R) (OR = 3.7; 95% CI = 2.79-4.91; p < 0.001). STs were more frequent in males and patients with unmutated immunoglobulin heavy variable genes (OR = 1.77; 95% CI = 1.49-2.11; p < 0.001/OR = 1.89; 95% CI = 1.6-2.24; p < 0.001).CLL-directed treatment was associated with non-melanoma skin and prostate cancers (OR = 1.8; 95% CI = 1.36-2.41; p < 0.001/OR = 2.11; 95% CI = 1.12-3.97; p = 0.021). In contrast, breast cancers were more frequent in untreated patients (OR = 0.17; 95% CI = 0.08-0.33; p < 0.001).Patients with CLL and an OM had inferior overall survival (OS) than those without. AML and MDS conferred the worst OS (p < 0.001)., Interpretation: OMs in CLL impact on OS. Treatment for CLL increased the risk for AML/MDS, prostate cancer, and NMSC. FCR was associated with increased risk for AML/MDS., Funding: AbbVie, and EU/EFPIAInnovative Medicines Initiative Joint Undertaking HARMONY grant n° 116026., Competing Interests: TC received honoraria from AbbVie. LS received consulting fees from AbbVie, BeiGene, AstraZeneca, Lilly, and Janssen, honoraria from Janssen and Octapharma, support for attending meetings from BeiGene and Janssen and advisory board fees from Merck. SMu received advisory board fees from AbbVie, AstraZeneca, Janssen, Roche and BeiGene. JAHR received honoraria as a consultant from Janssen, AbbVie, AstraZeneca, Lilly, and BeiGene and support for attending meetings from Janssen, AbbVie, AstraZeneca, and BeiGene. LI received honoraria from AbbVie, Roche, and Janssen-Cilag. APK received advisory board fees and research money from Janssen, AbbVie, BMS, AstraZeneca, Roche/Genentech, support for attending meetings from Janssen and AbbVie. M-DL received travel expenses from Janssen and AbbVie. GMR received honoraria for participation to speaker's bureau from AbbVie, Astra Zeneca, Beigene, and Janssen, and support for attending meetings from Janssen. JVT received consulting fees from AbbVie, AstraZeneca, BeiGene, and Janssen, honoraria for scientific talks from AbbVie, AstraZeneca, BeiGene, Janssen, Lilly, and Roche, travel support from AbbVie, AstraZeneca, BeiGene, Janssen, Roche, and Lilly, and advisory boards fees for AbbVie, Amgen, AstraZeneca, BeiGene. GI received honoraria from Novartis, BMS, Sandoz, AstraZeneca, Janssen, Kite/Gilead, and Miltenyi, support for attending meetings from Kite/Gilead, AstraZeneca, and AbbVie and advisory board fees from Kite/Gilead, Novartis, BMS, and Autolus. FBi received support for attending meetings from AbbVie. RCo received support for attending meetings from Janssen-Cilag and S.A. SG received honoraria support for attending meetings from AbbVie, AstraZeneca, Jazz, Novartis, and Incyte, honoraria from Roche, Celgene, Pfizer, and Janssen, and support for attending meetings from Jazz, AstraZeneca, and Roche. RGS received support for attending meetings from AbbVie and S.L.U. RG received honoraria, consulting fees, and support for attending meetings from AbbVie, Beigene, Roche, Janssen, AstraZeneca. YH received honoraria from Janssen, AbbVie, Roche, AstraZeneca, Medion, and Lilly. OJ received honoraria from Johnson and Johnson, AstraZeneca, and Lilly, honoraria from Johnson and Johnson, AbbVie, AstraZeneca, and Lilly, and support for attending meetings from Johnson and Johnson, and AbbVie. LK received consulting fees from AbbVie, AstraZeneca, Janssen, Beigene, Takeda, and Novartis. MKM received honoraria from Novartis, Pfizer, and Gad Medical LTD and support for attending meetings from Novartis. IKo received honoraria and consulting fees from AbbVie and Janssen. IM received honoraria from AbbVie, Roche, Sandoz, AstraZeneca, and Janssen, and support for attending meetings from AbbVie, Roche, and Takeda. ANB received honoraria, advisory board fees and support for attending meetings from AbbVie, AstraZeneca, Takeda, Janssen, and Beigene. JO received honoraria from AbbVie, AstraZeneca, and Janssen. GR received consulting fees from AbbVie, AstraZeneca, Janssen, and Beigene, and is currently employed by AstraZeneca. TP received honoraria and advisory board fees from AbbVie, Janssen-Cilag, and AstraZeneca and support for attending meeting from AstraZeneca. MS received honoraria and support for attending meeting from AstraZeneca, AbbVie, and Janssen-Cilag and owns shares of stock in AbbVie, AstraZeneca, Merck, Eli Lilly, Sanofi, Johnson and Johnson, Pfizer, Gilead, and GSK. MSp received honoraria and consulting and advisory board fees, and support for attending meeting from AbbVie, AstraZeneca, and Janssen. ET received support for attending meetings from Takeda. TV received honoraria from Takeda, Roche, Genesis Pharma, Merck, Novartis, Gilead, Sandoz, AstraZeneca, Integris, and Servier and support for attending meetings from Takeda, Roche, Genesis Pharma, Merck, Pfizer, and Winmedica. CV received honoraria from AbbVie, consulting fees from AstraZeneca and support for attending meeting from AstraZeneca, Takeda, and Janssen. RW received honoraria from AbbVie, AstraZeneca, and Beigene, support for attending meetings from Janssen, AbbVie, and AstraZeneca and advisory board fees from AbbVie, AstraZeneca, Janssen, Beigene, and SecuraBio. EWS received honoraria from AbbVie, Roche, and Janssen-Cilag and support for attending meetings from AbbVie. LY received honoraria from AbbVie, AstraZeneca, Novartis, Gilead, Janssen, Jazz, MSD, and Pfizer, support for attending meetings from AbbVie, AstraZeneca, Gilead, Janssen, and Pfizer, and advisory board fees from AbbVie, AstraZeneca, Jazz, Janssen, Beigene, and Celgene. MAn received consulting fees from AbbVie, Takeda, Janssen, Roche, Genesis, Gilead, and Amgen and honoraria from AbbVie, Takeda, Roche, Genesis, Gilead, and Novartis. MC received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, and Janssen. ACu received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, Beigene, Janssen, and Lilly. FD support for attending meetings from Janssen and AbbVie. GG received honoraria, and advisory board fees from AbbVie, AstraZeneca, Beigene, Janssen and advisory board fees from Lilly. EN received honoraria from AbbVie. LSm received consulting fees, honoraria and support for attending meetings from AbbVie, AstraZeneca, and Janssen and advisory board fees from AbbVie and AstraZeneca. NS received honoraria from Janssen, AbbVie, AstraZeneca, and Lilly, and support for attending meetings from Janssen and AstraZeneca. CT received honoraria from AbbVie, Beigene, Janssen, and LOXO. FB received consulting fees, honoraria and payment for expert testimony from AbbVie, Genentech, Novartis, Takeda, Janssen, Roche, Mundipharma, Celgene/BMS, AstraZeneca, Lilly, Beigene, Gilead and TG Therapeutics, Advantage Allogene, Lava Therapeutics, and Enterome. MDo received honoraria and advisory board fees from AbbVie, AstraZeneca and Janssen, advisory board fees from Swixx, and support for attending meetings from Janssen. PG received honoraria and consulting fees from AbbVie, AstraZeneca, BMS, Janssen, Lilly/Loxo Oncology, MSD, and Roche; grant support from AbbVie, AstraZeneca, BMS, Janssen. KS received honoraria from Janssen, AbbVie, Lilly and AstraZeneca, consulting fees and support for attending meetings from Janssen and AstraZeneca. GK, EM, DC, JK, CD, MA, SA, TAS, FBa, MB, ACa, AM, AKM, RC, SC, ACh, ZD, MDi, DD, GDS, BD, ME, SEA, AE, AF, AG, EG, IGGM, AGo, AjG, RGu, SH, EH, SJ, EKa, VK, BK, MK, EK, RJK, JL, DL, IL, TL, ALG, JM, LMR, MMa, SM, CMB, BM, FM, RM, MMo, RMu, UKN, ACO, DO, IPS, MP, ZK, PP, CP, AP, LR, RR, MDDS, AS, YS, MSi, SS, DSAS, TT, KT, AV, GV, VV, ZX, MYa, MY, JZ, DA, BB, MCa, RCl, BE, OBK, LL, GP, PPa, VMP, SP, PS, LT, AC, have no conflict of interest to disclose., (© 2023 Published by Elsevier Ltd.)

Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B-cell receptor (BcR) immunoglobulins. Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR immunoglobulin stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR immunoglobulin stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. To address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29 856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed "satellites," were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL., (© 2021 by The American Society of Hematology.)

Recent evidence suggests that complex karyotype (CK) defined by the presence of ≥3 chromosomal aberrations (structural and/or numerical) identified by using chromosome-banding analysis (CBA) may be relevant for treatment decision-making in chronic lymphocytic leukemia (CLL). However, many challenges toward the routine clinical application of CBA remain. In a retrospective study of 5290 patients with available CBA data, we explored both clinicobiological associations and the clinical impact of CK in CLL. We found that patients with ≥5 abnormalities, defined as high-CK, exhibit uniformly dismal clinical outcomes, independently of clinical stage, TP53 aberrations (deletion of chromosome 17p and/or TP53 mutations [ TP53 abs]), and the expression of somatically hypermutated (M-CLL) or unmutated immunoglobulin heavy variable genes. Thus, they contrasted with CK cases with 3 or 4 aberrations (low-CK and intermediate-CK, respectively) who followed aggressive disease courses only in the presence of TP53 abs. At the other end of the spectrum, patients with CK and +12,+19 displayed an exceptionally indolent profile. Building upon CK, TP53 abs, and immunoglobulin heavy variable gene somatic hypermutation status, we propose a novel hierarchical model in which patients with high-CK exhibit the worst prognosis, whereas those with mutated CLL lacking CK or TP53 abs, as well as CK with +12,+19, show the longest overall survival. Thus, CK should not be axiomatically considered unfavorable in CLL, representing a heterogeneous group with variable clinical behavior. High-CK with ≥5 chromosomal aberrations emerges as prognostically adverse, independent of other biomarkers. Prospective clinical validation is warranted before ultimately incorporating high-CK in risk stratification of CLL., (© 2019 by The American Society of Hematology.)

SF3B1 , SRSF2 , and U2AF1 are the most frequently mutated splicing factor genes in the myelodysplastic syndromes (MDS). We have performed a comprehensive and systematic analysis to determine the effect of these commonly mutated splicing factors on pre-mRNA splicing in the bone marrow stem/progenitor cells and in the erythroid and myeloid precursors in splicing factor mutant MDS. Using RNA-seq, we determined the aberrantly spliced genes and dysregulated pathways in CD34 + cells of 84 patients with MDS. Splicing factor mutations result in different alterations in splicing and largely affect different genes, but these converge in common dysregulated pathways and cellular processes, focused on RNA splicing, protein synthesis, and mitochondrial dysfunction, suggesting common mechanisms of action in MDS. Many of these dysregulated pathways and cellular processes can be linked to the known disease pathophysiology associated with splicing factor mutations in MDS, whereas several others have not been previously associated with MDS, such as sirtuin signaling. We identified aberrantly spliced events associated with clinical variables, and isoforms that independently predict survival in MDS and implicate dysregulation of focal adhesion and extracellular exosomes as drivers of poor survival. Aberrantly spliced genes and dysregulated pathways were identified in the MDS-affected lineages in splicing factor mutant MDS. Functional studies demonstrated that knockdown of the mitosis regulators SEPT2 and AKAP8, aberrantly spliced target genes of SF3B1 and SRSF2 mutations, respectively, led to impaired erythroid cell growth and differentiation. This study illuminates the effect of the common spliceosome mutations on the MDS phenotype and provides novel insights into disease pathophysiology., (© 2018 by The American Society of Hematology.)

Purpose: We sought to investigate whether B cell receptor immunoglobulin (BcR IG) stereotypy is associated with particular clinicobiological features among chronic lymphocytic leukemia (CLL) patients expressing mutated BcR IG (M-CLL) encoded by the IGHV4-34 gene, and also ascertain whether these associations could refine prognostication. Experimental Design: In a series of 19,907 CLL cases with available immunogenetic information, we identified 339 IGHV4-34-expressing cases assigned to one of the four largest stereotyped M-CLL subsets, namely subsets #4, #16, #29 and #201, and investigated in detail their clinicobiological characteristics and disease outcomes. Results: We identified shared and subset-specific patterns of somatic hypermutation (SHM) among patients assigned to these subsets. The greatest similarity was observed between subsets #4 and #16, both including IgG-switched cases (IgG-CLL). In contrast, the least similarity was detected between subsets #16 and #201, the latter concerning IgM/D-expressing CLL. Significant differences between subsets also involved disease stage at diagnosis and the presence of specific genomic aberrations. IgG subsets #4 and #16 emerged as particularly indolent with a significantly ( P < 0.05) longer time-to-first-treatment (TTFT; median TTFT: not yet reached) compared with the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). Conclusions: Our findings support the notion that BcR IG stereotypy further refines prognostication in CLL, superseding the immunogenetic distinction based solely on SHM load. In addition, the observed distinct genetic aberration landscapes and clinical heterogeneity suggest that not all M-CLL cases are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Clin Cancer Res; 23(17); 5292-301. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Purpose: Prompted by the extensive biases in the immunoglobulin (IG) gene repertoire of splenic marginal-zone lymphoma (SMZL), supporting antigen selection in SMZL ontogeny, we sought to investigate whether antigen involvement is also relevant post-transformation., Experimental Design: We conducted a large-scale subcloning study of the IG rearrangements of 40 SMZL cases aimed at assessing intraclonal diversification (ID) due to ongoing somatic hypermutation (SHM)., Results: ID was identified in 17 of 21 (81%) rearrangements using the immunoglobulin heavy variable (IGHV)1-2*04 gene versus 8 of 19 (40%) rearrangements utilizing other IGHV genes (P= 0.001). ID was also evident in most analyzed IG light chain gene rearrangements, albeit was more limited compared with IG heavy chains. Identical sequence changes were shared by subclones from different patients utilizing the IGHV1-2*04 gene, confirming restricted ongoing SHM profiles. Non-IGHV1-2*04 cases displayed both a lower number of ongoing SHMs and a lack of shared mutations (per group of cases utilizing the same IGHV gene)., Conclusions: These findings support ongoing antigen involvement in a sizable portion of SMZL and further argue that IGHV1-2*04 SMZL may represent a distinct molecular subtype of the disease., (©2015 American Association for Cancer Research.)

Fludarabine, cyclophosphamide, and rituximab (FCR) is first-line treatment of medically fit chronic lymphocytic leukemia (CLL) patients; however, despite good response rates, many patients eventually relapse. Although recent high-throughput studies have identified novel recurrent genetic lesions in adverse prognostic CLL, the mechanisms leading to relapse after FCR therapy are not completely understood. To gain insight into this issue, we performed whole-exome sequencing of sequential samples from 41 CLL patients who were uniformly treated with FCR but relapsed after a median of 2 years. In addition to mutations with known adverse-prognostic impact (TP53, NOTCH1, ATM, SF3B1, NFKBIE, and BIRC3), a large proportion of cases (19.5%) harbored mutations in RPS15, a gene encoding a component of the 40S ribosomal subunit. Extended screening, totaling 1119 patients, supported a role for RPS15 mutations in aggressive CLL, with one-third of RPS15-mutant cases also carrying TP53 aberrations. In most cases, selection of dominant, relapse-specific subclones was observed over time. However, RPS15 mutations were clonal before treatment and remained stable at relapse. Notably, all RPS15 mutations represented somatic missense variants and resided within a 7 amino-acid, evolutionarily conserved region. We confirmed the recently postulated direct interaction between RPS15 and MDM2/MDMX and transient expression of mutant RPS15 revealed defective regulation of endogenous p53 compared with wild-type RPS15. In summary, we provide novel insights into the heterogeneous genetic landscape of CLL relapsing after FCR treatment and highlight a novel mechanism underlying clinical aggressiveness involving a mutated ribosomal protein, potentially representing an early genetic lesion in CLL pathobiology., (© 2016 by The American Society of Hematology.)

An unresolved issue in chronic lymphocytic leukemia (CLL) is whether IGHV3-21 gene usage, in general, or the expression of stereotyped B-cell receptor immunoglobulin defining subset #2 (IGHV3-21/IGLV3-21), in particular, determines outcome for IGHV3-21-utilizing cases. We reappraised this issue in 8593 CLL patients of whom 437 (5%) used the IGHV3-21 gene with 254/437 (58%) classified as subset #2. Within subset #2, immunoglobulin heavy variable (IGHV)-mutated cases predominated, whereas non-subset #2/IGHV3-21 was enriched for IGHV-unmutated cases (P = .002). Subset #2 exhibited significantly shorter time-to-first-treatment (TTFT) compared with non-subset #2/IGHV3-21 (22 vs 60 months, P = .001). No such difference was observed between non-subset #2/IGHV3-21 vs the remaining CLL with similar IGHV mutational status. In conclusion, IGHV3-21 CLL should not be axiomatically considered a homogeneous entity with adverse prognosis, given that only subset #2 emerges as uniformly aggressive, contrasting non-subset #2/IGVH3-21 patients whose prognosis depends on IGHV mutational status as the remaining CLL., (© 2015 by The American Society of Hematology.)

This study evaluates the prognostic significance of genetic abnormalities (detected at or shortly after presentation), clinical stage, lymphocyte morphology, CD38 expression, and IGVH gene status in 205 patients with chronic lymphocytic leukemia (B-CLL). Deletion of chromosome 11q23, absence of a deletion of chromosome 13q14, atypical lymphocyte morphology, and more than 30% CD38 expression are significantly associated with the presence of unmutated IGVH genes. Advanced stage, male sex, atypical morphology, more than 30% CD38 expression, trisomy 12, deletion of chromosome 11q23, loss or mutation of the p53 gene, and unmutated IGVH genes are all poor prognostic factors in a univariate analysis. However, only 98% or more homology of IGVH genes to the germline sequence, loss or mutation of the p53 gene, and clinical stage retain prognostic significance in a multivariate analysis. The median survival of patients with mutated IGVH genes, unmutated IGVH genes, and loss or mutation of the p53 gene regardless of IGVH gene status is 310, 119, and 47 months, respectively. These data should facilitate the design of new trials for the management of patients presenting with advanced disease or poor prognosis early stage disease.