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 [TP53abs]), 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 TP53abs. At the other end of the spectrum, patients with CK and +12,+19 displayed an exceptionally indolent profile. Building upon CK, TP53abs, 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 TP53abs, 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.

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.

Patients with chronic lymphocytic leukemia (CLL) may be more susceptible to Coronavirus disease 2019 (COVID-19) due to age, disease, and treatment-related immunosuppression. We aimed to assess risk factors of outcome and elucidate the impact of CLL-directed treatments on the course of COVID-19. We conducted a retrospective, international study, collectively including 941 patients with CLL and confirmed COVID-19. Data from the beginning of the pandemic until March 16, 2021, were collected from 91 centers. The risk factors of case fatality rate (CFR), disease severity, and overall survival (OS) were investigated. OS analysis was restricted to patients with severe COVID-19 (definition: hospitalization with need of oxygen or admission into an intensive care unit). CFR in patients with severe COVID-19 was 38.4%. OS was inferior for patients in all treatment categories compared to untreated (p < 0.001). Untreated patients had a lower risk of death (HR = 0.54, 95% CI:0.41–0.72). The risk of death was higher for older patients and those suffering from cardiac failure (HR = 1.03, 95% CI:1.02–1.04; HR = 1.79, 95% CI:1.04–3.07, respectively). Age, CLL-directed treatment, and cardiac failure were significant risk factors of OS. Untreated patients had a better chance of survival than those on treatment or recently treated.

Complex karyotype (CK) at chronic lymphocytic leukemia (CLL) diagnosis is a negative biomarker of adverse outcome. Since the impact of CK and its subtypes, namely type-2 CK (CK with major structural abnormalities) or high-CK (CK with ≥5 chromosome abnormalities), on the risk of developing Richter syndrome (RS) is unknown, we carried out a multicenter real-life retrospective study to test its prognostic impact. Among 540 CLL patients, 107 harbored a CK at CLL diagnosis, 78 were classified as CK2 and 52 as high-CK. Twenty-eight patients developed RS during a median follow-up of 6.7 years. At the time of CLL diagnosis, CK2 and high-CK were more common and predicted the highest risk of RS transformation, together with advanced Binet stage, unmutated (U)-IGHV, 11q-, and TP53 abnormalities. We integrated these variables into a hierarchical model: high-CK and/or CK2 patients showed a 10-year time to RS (TTRS) of 31%; U-IGHV/11q- /TP53 abnormalities/Binet stage B-C patients had a 10-year TTRS of 12%; mutated (M)-IGHV without CK and TP53 disruption a 10-year TTRS of 3% (P<0.0001). We herein demonstrate that CK landscape at CLL diagnosis allows the risk of RS transformation to be refined and we recapitulated clinico-biological variables into a prognostic model.