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Refining prognosis in early-stage CLL
Introduction
Despite mounting evidence for the existence of distinct biological variants of chronic lymphocytic leukemia (CLL), the 2016 update of the World Health Organization (WHO) classification still considers CLL as a single, homo- geneous entity, in contrast to other hematologic malignan- cies (e.g. diffuse large B-cell lymphoma, DLBCL) which are segregated in different subgroups, based on the inte- gration of genetic, morphological, immunophenotypic and clinical features.1
Since the introduction of the Rai and Binet clinical stag- ing systems in the 1970s,2,3 it has become increasingly evi- dent that the clinical heterogeneity in CLL is linked to and reflects the underlying biological heterogeneity. Hence, several initiatives have focused on identifying biomarkers that would refine prognostication, especially for cases who present with early stage disease, who nowadays rep- resent the great majority of patients (80-85%).4-12 Consequently, numerous prognostic indices have been proposed; however, none has been adopted in every-day clinical practice.13 This is partly due to the fact that differ- ent variables have been assessed in each evaluated cohort while the actual routine diagnostic and monitoring prac- tice varies between different institutions. Moreover, most reported cohorts were rather small, thus inherently limit- ed in their capacity to both encompass the remarkable clinico-biological heterogeneity of CLL and reveal possible interactions and interdependencies among the evaluated prognosticators.
The clonotypic B-cell receptor immunoglobulin (BcR IG) is a unique molecular signature for every CLL clone, pres- ent from its genesis and remaining unaltered throughout the course of the disease, thus sharply contrasting other tumor-derived biomarkers.14-19 Seminal studies from the late 1990s have established that the somatic hypermuta- tion (SHM) status of the immunoglobulin heavy variable (IGHV) gene expressed by the clonotypic BcR IG is a robust prognostic and predictive biomarker for CLL, stratifying patients into two non-interchangeable cate- gories with different clinical behavior.20,21 More specifical- ly, CLL with a significant SHM load (“mutated” CLL, M- CLL) generally follow an indolent clinical course, whereas CLL carrying no or few mutations (“unmutated” CLL, U- CLL) generally have an aggressive disease and an overall inferior response to chemoimmunotherapy.22-24
This subclassification into M-CLL and U-CLL reflects fundamental clinico-biological differences extending from the genomic and epigenomic to the transcriptomic and proteomic levels, alluding to distinct ontogeny and evolu- tion patterns, including response to treatment, for the two patient categories.14,24-27 That said, within both M-CLL and U-CLL, a sizeable proportion of cases exhibit a clinico-bio- logical behavior pattern that deviates from the expected, thus highlighting that the heterogeneity of CLL persists even within a given SHM category.28-31 The paradigmatic example is offered by CLL subset #2, defined by the expression of stereotyped IGHV3-21/IGLV3-21 BcR IG, within which M-CLL cases follow an aggressive clinical course similar to U-CLL.30,32,33
Notably, other established prognosticators such as cyto- genetic aberrations or recurrent gene mutations are asym- metrically distributed within M-CLL or U-CLL.10,34-36 On these grounds, it is not unreasonable to think that defini- tive conclusions about the precise clinical implications of
any given biomarker should be drawn only after consider- ing the SHM status of the clonotypic BcR IG.
In this study, we followed a compartmentalized approach where we assessed the prognostic impact of tra- ditional and novel prognostic parameters separately with- in M-CLL and U-CLL in a large multi-institutional cohort of well characterized CLL patients, based on the hypoth- esis that not all variables would carry equal weight within the two SHM categories. Considering that the key chal- lenge at the time of diagnosis is determining if, and conse- quently when, early stage/asymptomatic patients will require treatment, we focused on identifying a robust prognostication scheme for time-to-first-treatment (TTFT) in these separate disease categories.
Methods
Patients’ characteristics
Overall, 2366 general practice patients with CLL diagnosed fol- lowing the 2008 International Workshop on CLL (IWCLL) diag- nostic criteria37 from 10 European institutions were included in this multicenter retrospective study (Online Supplementary Table S1). The external validation cohort comprised of 649 Binet A cases evaluated at the Munich Leukemia Laboratory (n=508) and from a Scandinavian population-based study (n=141) (Online Supplementary Table S2). Ethical approval was granted by the local review committees and informed consent was collected according to the Declaration of Helsinki.
Methodologies
Detailed information about the methodologies used to analyze the prognostic markers and definitions about stereotyped subsets and the criteria for subset assignment are provided in the Online Supplementary Appendix. Briefly: i) mutational screening was per- formed for the following genes: NOTCH1, entire exon 34 or tar- geted analysis for del7544-45/p.P2514Rfs*4; TP53, exons 4–8 but also exons 9–10 for some centers; SF3B1, exons 14–16; BIRC3, exons 6–9 and MYD88, exons 3 and 5 or targeted analysis for p.L265P. The great majority (80%) of cases included in this study were screened for the aforementioned recurrent mutations by Sanger sequencing. In the remaining cases (20%), next generation sequencing (NGS) was applied and only those clones with higher than 10% variant allele frequency (VAF >10%) were considered; ii) fluorescence in situ hybridization (FISH) was performed in 1825 (77%) cases using probes for the 13q14, 11q22, 17p13 regions and trisomy 12 (cut off: 5%) while results were interpreted following Döhner’s hierarchical model;38 and iii) sequence analysis and inter- pretation of IGHV-IGHD–IGHJ rearrangements (including BcR IG stereotypy) was performed as described previously.39
Statistical analysis
We assessed the prognostic impact on TTFT of the following variables: age at the time of diagnosis; sex; CD38 expression; cyto- genetic aberrations [del(17p), del(11q), del(13q) and trisomy 12 (+12)]; mutations within the TP53, SF3B1, NOTCH1, BIRC3 and MYD88 genes; and immunogenetic features, including borderline germline identity (GI: 97-97.99%) and assignment to stereotyped subsets #1, #2 and #4.
The following methodology was applied separately for M-CLL and U-CLL patients. The χ2 test was used to assess the homogene- ity of all categorical prognostic variables within the different Binet stages (A, B and C). In order to evaluate homogeneity and detect significant differences within each categorical variable, the Bonferroni correction was applied to adjust for multiple compari-
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