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S. Ramos-Campoy et al.
2.74; P<0.001). Our findings suggest that both methods are useful but not equivalent for risk stratifica- tion of CLL patients. Validation studies are needed to establish the prognostic value of genome com- plexity based on GM data in future prospective studies.
Introduction
Deletions of 17p13 region and/or mutations in TP53 as well as the mutational status of the variable region of the immunoglobulin heavy chain (IGHV) gene constitute the most important prognostic and predictive factors in chronic lymphocytic leukemia (CLL) in the era of chemoimmunotherapy.1 However, several studies have highlighted the independent clinical significance of genomic complexity, mainly defined by the detection of complex karyotypes (CK) by chromosome banding analysis (CBA), due to its association with an unfavorable clinical outcome. This has been demonstrated in patients treated not only with standard chemoimmunotherapy regimes2-5 but also in the initial clinical trials with the novel mechanism-based therapeutic agents such as ibru- tinib or venetoclax.6-8
Early studies in CLL defined CK as the presence of at least three numerical and/or structural chromosomal abnormalities in the same cell clone detected by CBA.9,10 Of note, the increasing number of chromosomal abnor- malities in the karyotype has been correlated with the worsening of clinical evolution of CLL patients.11,12 In this context, a large retrospective study from the European Research Initiative on CLL (ERIC) has reported that patients with five or more abnormalities (the so-called high-CK) display an adverse outcome independently of other known biomarkers such as TP53 abnormalities or the IGHV mutational status.5 On the other hand, it has been demonstrated that CK might have a different clinical impact in CLL patients according to not only the number, but also the type of aberrations detected in the karyotype. In this regard, it has been described that patients with CK carrying +12, +19 display a particularly favorable out- come while the presence of unbalanced rearrangements define a subset with very aggressive disease.13-15
Even though CBA has been the gold standard method to identify CK, in the last decade genomic microarrays (GM) have emerged as a valuable tool for genome-wide screening in CLL.16-20 Indeed, some studies have correlated the genomic complexity detected by GM to progressive disease and poorer response rates to treatment.21-23 Nonetheless, although some European countries have replaced conventional techniques by GM, standard crite- ria to analyze and define genomic complexity by GM are still needed. According to the published guidelines for GM analysis in acquired hematologic neoplasms, recur- rent aberrations with known clinical relevance in the dis- ease irrespective of their size as well as other copy num- ber abnormalities (CNA) ≥5 Mb should be considered in order to reduce the detection of benign constitutional variants and avoid the reporting of anomalies with uncer- tain clinical significance.24 However, it remains unclear whether this threshold is the optimal to analyze CLL patients or whether potentially relevant chromosomal imbalances are disregarded by applying this highly con- servative size cut-off. Besides, another multicenter study conducted by ERIC suggested that CLL patients could be divided into three distinct prognostic subgroups based on the number of CNA.25 According to Leeksma et al., the so-
called high genomic complexity (high-GC) subgroup, which is defined by carrying ≥5 CNA, emerged as prog- nostically adverse, independently of other biomarkers. Nevertheless, to the best of our knowledge, the compari- son of genomic complexity for risk stratification using CBA and GM in parallel has not been performed in a large CLL cohort.
In the present multicenter retrospective study we aimed to compare the usefulness of CBA and GM tech- niques in a series of 340 CLL patients with and without CK to determine both their concordance and their equiv- alence in the prognostic stratification of CLL patients with CK. Moreover, we have analyzed the detected aber- rations using different counting strategies to ascertain whether other parameters, such as the type of the aberra- tions or their size, might have an influence on the risk stratification of CLL patients.
Methods
Patient cohort
A total of 340 previously untreated CLL (n=327; 96.2%) and monoclonal B-cell lymphocytosis (n=13; 3.8%) patients from 18 European institutions were included. All had CBA results at diagnosis or before treatment. GM data were already available or obtained from DNA extracted within 1 year. Analyses were performed on peripheral blood (PB) (n=286) or bone marrow (BM) (n=54). Due to the purpose of the study, this cohort was enriched in patients with CK (n=158; 46.5%). Demographic, clinical and biological characteristics are summarized in Table 1. The study was carried out in accordance with national and inter- national guidelines (Professional Code of Conduct, Declaration of Helsinki) and approved by the Hospital del Mar Ethics Committee (2017/7565/I).
Chromosome banding analyses
CBA was performed on G- or R-banded chromosomes. Karyotypes were described according to the International System for Human Cytogenetic Nomenclature (ISCN 2016).26 A complex karyotype was defined as the presence of three or more numerical and/or structural chromosomal abnormalities (abn.) detected in the same cell clone. Patients were stratified in three categories: non-CK (0-2 abn.), low/intermediate-CK (3-4 abn.) and high-CK (≥5 abn.)5
Genomic microarray analyses
Microarray platforms used are summarized in the Online Supplementary Table S1. All aberrations found irrespective of size were collected, although non-classical CLL abnormalities (other than gain of chromosome 12 and losses of 11q, 13q and 17p) were filtered in the CNA count for prognostic stratification fol- lowing the 5 Mb cut-off size recommended.24 Three subgroups were defined according to genomic complexity (GC): low-GC (0-2 CNA), intermediate-GC (3-4 CNA) and high-GC (≥5 CNA).25 This strategy was compared with other CNA counting methodologies, such as the inclusion of smaller abnormalities (no size filter or 1 Mb as cut-off) or counting as a unique CNA small contiguous abnormalities (with a distance ≤1 Mb between them) or those included in a chromothripsis event.
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