IGHV Mutational Status and BCR Stereotypy in Chronic Lymphocytic Leukemia: A Turkish Cohort Analysis

IGHV Mutational Status and BCR Stereotypy in Chronic Lymphocytic Leukemia: A Turkish Cohort Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article IGHV Mutational Status and BCR Stereotypy in Chronic Lymphocytic Leukemia: A Turkish Cohort Analysis Seher YÜKSEL, Rahmi Şinasi, Merve YÜKSEL, Mehmet Berk ÖRÜNCÜ, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9375280/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 7 You are reading this latest preprint version Abstract Objective: Immunoglobulin heavy chain variable region (IGHV) mutational status and B-cell receptor (BCR) stereotypy are established prognostic markers in chronic lymphocytic leukemia (CLL). However, immunogenetic data from Türkiye and surrounding regions are scarce. We evaluated IGHV mutational status, BCR stereotypy including nearest subset assignment, and their clinical and cytogenetic correlates in a real-world Turkish CLL cohort. Methods: We retrospectively analyzed 145 patients with CLL at a tertiary referral center in Türkiye. IGHV mutational status was determined by next-generation sequencing (98% germline homology cutoff). BCR stereotypy was assigned using ARResT/AssignSubsets. Cytogenetic abnormalities were assessed by fluorescence in situ hybridization (FISH). Time-to-first treatment (TTFT), progression-free survival (PFS), and overall survival (OS) were analyzed by Kaplan–Meier method, with multivariate Cox regression for TTFT. Results: Unmutated IGHV was detected in 55.2% of patients, higher than Western reports but consistent with Mediterranean and Middle Eastern cohorts. Unmutated cases showed adverse cytogenetics—del(11q) and higher genomic complexity—whereas del(13q) predominated in mutated cases. TTFT was significantly shorter in U-CLL when compared to M-CLL (17.0 vs. 70.0 months; p < 0.0001). PFS and OS did not differ statistically. Major stereotyped subsets were present in 15.9% of patients; subset #2 was absent, while subset #1 was predominant (39.1%). Subsets #1 and #64B were overrepresented among relapsed cases. Nearest subset #77 showed rapid progression despite mutated IGHV. Conclusion: CLL in Türkiye demonstrates region-specific immunogenetic features while preserving established clinico-biological correlations. Integration of IGHV status, cytogenetics, and BCR stereotypy may improve risk stratification in underrepresented populations. Chronic lymphocytic leukemia IGHV mutational status BCR stereotypy major stereotyped subsets real-world cohort Figures Figure 1 Figure 2 Figure 3 Introduction Chronic lymphocytic leukemia (CLL) is an indolent B-cell malignancy accounting for approximately 30–40% of adult leukemias, yet its clinical course is remarkably heterogeneous [ 1 ]. While many patients remain stable for years without requiring therapy, others progress rapidly, highlighting the importance of reliable biological markers for prognostic stratification and treatment planning. Contemporary risk assessment integrates the Rai and Binet staging systems with FISH-detected cytogenetic abnormalities—del(17p), del(11q), trisomy 12, and del(13q)—and recurrent gene mutations [ 2 ]. The prognostic significance of somatic hypermutation (SHM) within the immunoglobulin heavy chain variable region (IGHV) gene was established in 1999 [ 3 , 4 ]; patients with unmutated IGHV (U-CLL; ≥ 98% germline homology) experience more aggressive disease and shorter TTFT, while mutated IGHV (M-CLL; < 98% homology) confers a more indolent trajectory [ 5 , 6 ]—distinctions formalized in the CLL-IPI [ 7 ]. Immunogenetic studies have shown that approximately 40% of CLL patients express quasi-identical BCR immunoglobulins—a phenomenon termed BCR stereotypy [ 8 , 9 ]. Subsets sharing VH CDR3 characteristics are classified as major (≥ 20 cases, reproducible clinical behavior) or minor [ 1 , 8 ]. Despite extensive investigation in Western populations, real-world immunogenetic data from Türkiye remain scarce. We therefore analyzed a Turkish CLL cohort to characterize IGHV mutational status, IGHV gene repertoire, BCR stereotypy, and their clinical and cytogenetic correlates. Materials and Methods Study design and patients This retrospective study included patients diagnosed with CLL at Ankara University School of Medicine between 2019 and 2025. Patients were eligible if IGHV mutational analysis had been performed and adequate clinical data were available. Those lacking IGHV analysis or presenting with concurrent hematologic malignancies were excluded. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ankara University Human Research Ethics Committee (Approval No: 2023000138-1 [2023/138]). Data collection and cytogenetics Clinical and laboratory data were retrospectively obtained from electronic medical records. Baseline variables included age, sex, Rai and Binet stage at diagnosis, and absolute lymphocyte count. FISH analysis was performed on peripheral blood at the time of diagnosis using probes for del(13q), trisomy 12, del(11q), and del(17p); del(17p) was considered a high-risk cytogenetic abnormality. IGHV mutational analysis IGHV mutational status was determined in accordance with the recommendations of the European Research Initiative on CLL (ERIC). DNA was extracted from peripheral blood, bone marrow aspirates, or formalin-fixed paraffin-embedded (FFPE) tissue. Next-generation sequencing (NGS) was performed using the LymphoTrack® Dx IGHV Somatic Hypermutation Assay Panel on the Illumina MiSeq platform. Sequences were analyzed using the IMGT database with a 98% homology cutoff. Only productive IGHV rearrangements were included; in patients with multiple productive clones, the dominant clone determined classification. Discordant cases (mutated and unmutated productive clones coexisting) were classified as U-CLL per ERIC recommendations. Dominant sequences were subsequently analyzed using the ARResT/AssignSubsets platform ( http://arrest.tools/assignsubsets ) for immunogenetic classification. BCR stereotypy analysis Stereotyped BCR subset assignment was performed using the ARResT/AssignSubsets tool ( http://arrest.tools/assignsubsets ) based on IMGT-defined immunogenetic criteria, including IGHV gene clan usage, VH CDR3 length, amino acid identity, and physicochemical similarity. Cases fulfilling full assignment criteria were classified as major stereotyped subsets; those demonstrating immunogenetic similarity without meeting strict thresholds were designated nearest stereotyped subsets. Statistical analysis Categorical variables were compared using chi-square or Fisher's exact tests; continuous variables were assessed using the Mann–Whitney U test or independent-samples t-test. Survival outcomes (TTFT, PFS, OS) were analyzed by Kaplan–Meier method with log-rank comparisons. Multivariate analysis of TTFT employed Cox proportional hazards regression incorporating age, sex, clinical stage, and high-risk cytogenetics. Analyses were performed using IBM SPSS Statistics version 26.0; survival curves were generated in Python 3.10 with Matplotlib. Missing data were handled using an available-case approach. Results Patient characteristics A total of 145 patients were included. Median age at diagnosis was 59.0 years (range, 30–93), with a male predominance (n = 88, 60.7%). IGHV status was unmutated in 80 patients (55.2%) and mutated in 65 patients (44.8%). Baseline characteristics stratified by IGHV status are summarized in Table 1 . Association of IGHV mutational status with clinical features Mutated IGHV was associated with earlier clinical stage. In M-CLL, 32.3% presented at Rai stage 0 versus 16.2% in U-CLL, and Binet A was more frequent in M-CLL when compared with U-CLL (53.8% vs. 37.5%; p = 0.068). Risk stratification using the CLL-IPI revealed a significant association with IGHV mutational status (p < 0.001). High and very high-risk CLL-IPI scores were predominantly clustered within the unmutated group (72.0%), whereas these risk categories accounted for only 28.0% of patients with mutated IGHV. Lymphocyte count at diagnosis did not differ between groups (p = 0.573). Cytogenetic data were available for 121 patients (83.4% of the cohort). Cytogenetic profiles showed distinct distributions by IGHV status. Del(13q) was significantly more frequent in M-CLL than U-CLL (66.7% vs. 37.5%; p = 0.004), while del(11q) predominated in U-CLL (27.0% vs. 8.0%; p = 0.014). Multiple cytogenetic abnormalities were more common in U-CLL (29.4% vs. 11.3%; p = 0.029). While trisomy 12 (27.4% vs. 14.9%) and del(17p) (16.7% vs. 9.4%) were numerically higher in U-CLL, these differences did not reach statistical significance (p = 0.162 and p = 0.290, respectively). Table 1 Baseline demographic and clinical characteristics of the study cohort according to IGHV mutational status Characteristics Total cohort (n = 145) IGHV mutated (n = 65) IGHV unmutated (n = 80) p-value Age , years, median (range) 59.0 (30–93) 59.5 (33–86) 58.5 (30–93) 0.443 Gender Male, n (%) 88 (60.7%) 37 (56.9%) 51 (63.8%) 0.505 Female, n (%) 57 (39.3%) 28 (43.1%) 29 (36.2%) Lymphocyte count (cells/µL), median (range) 17,000 (1,730 − 420,000) 15,345 (1,730 − 420,000) 17,960 (2,330 − 294,710) 0.573 Rai Stage , n (%) Stage 0 34 (23.4%) 21 (32.3%) 13 (16.2%) 0.131 Stage I 55 (37.9%) 23 (35.4%) 32 (40.0%) Stage II 24 (16.6%) 7 (10.8%) 17 (21.2%) Stage III 19 (13.1%) 7 (10.8%) 12 (15.0%) Stage IV 8 (5.5%) 4 (6.2%) 4 (5.0%) Missing data 5 (3.4%) 3 (4.6%) 2 (2.5%) Binet Stage , n (%) Stage A 65 (44.8%) 35 (53.8%) 30 (37.5%) 0.068 Stage B 55 (37.9%) 18 (27.7%) 37 (46.2%) Stage C 20 (13.8%) 9 (13.8%) 11 (13.8%) Missing data 5 (3.4%) 3 (4.6%) 2 (2.5%) Cytogenetics (FISH) , n/eval (%) del(13q) 56/112 (50.0%) 32/48 (66.7%) 24/64 (37.5%) 0.004* del(11q) 21/113 (18.6%) 4/50 (8.0%) 17/63 (27.0%) 0.014* del(17p) 16/119 (13.4%) 5/53 (9.4%) 11/66 (16.7%) 0.290 Trisomy 12 24/109 (22.0%) 7/47 (14.9%) 17/62 (27.4%) 0.162 Multiple abnormalities 26/121 (21.5%) 6/53 (11.3%) 20/68 (29.4%) 0.029* Note : Data are presented as number (percentage) for categorical variables and median (minimum–maximum) for continuous variables. Percentages were calculated based on the number of patients with available data in each group. *Statistically significant. Abbreviations : CLL : Chronic Lymphocytic Leukemia; FISH : Fluorescence in situ hybridization; IGHV : Immunoglobulin heavy chain variable region. IGHV gene repertoire A total of 161 productive IGHV rearrangements were identified among 145 patients; 130 (89.7%) had a single productive rearrangement and 15 patients (10.3%) had multiple. The most frequently used IGHV genes were IGHV4-34 (11.2%), IGHV1-69 (8.1%), and IGHV3-23 (6.8%). Gene usage differed by mutational status: IGHV4-34 predominated in M-CLL (20.8%), and IGHV1-69 in U-CLL (13.1%), as shown in Supplementary Table 1. Biclonal IGHV rearrangements and discordant IGHV mutational status Among 15 patients with multiple productive rearrangements, 10 showed concordant mutational status and 5 (3.4%) were discordant harboring both mutated and unmutated clones (Supplementary Table 2). IGHV4-34 was recurrent in discordant mutated clones. All five were classified as U-CLL per ERIC recommendations. Four of the five (80%) required systemic therapy with short TTFT (0, 8, 24, and 72 months), with clinical trajectories consistent with U-CLL. BCR stereotypy Major stereotyped BCR subsets Major stereotyped BCR subsets were identified in 23 of 145 patients (15.9%) using ARResT/AssignSubsets. Subset #1 was most frequent (n = 9, 39.1%), followed by subsets #3 and #4 (each n = 3, 13.0%). Subsets #1, #3, #64B, #7H, #99, #31, and #8 were exclusive to U-CLL; subsets #4, #77, and #14 were confined to M-CLL ( Table 2 ). Table 2 Distribution of major stereotyped BCR subsets according to IGHV mutational status Major subsets All patients (n = 23), n (%) Mutated IGHV, n (%) Unmutated IGHV, n (%) Subset #1 9 (39.1%) 0 (0%) 9 (100%) Subset #3 3 (13.0%) 0 (0%) 3 (100%) Subset #4 3 (13.0%) 3 (100%) 0 (0%) Subset #64B 2 (8.7%) 0 (0%) 2 (100%) Subset #7H 1 (4.3%) 0 (0%) 1 (100%) Subset #77 1 (4.3%) 1 (100%) 0 (0%) Subset #14 1 (4.3%) 1 (100%) 0 (0%) Subset #99 1 (4.3%) 0 (0%) 1 (100%) Subset #31 1 (4.3%) 0 (0%) 1 (100%) Subset #8 1 (4.3%) 0 (0%) 1 (100%) Total 23 (100 % ) 5 (21.7 % ) 18 (78.3 % ) Percentages in the “Mutated IGHV” and “Unmutated IGHV” columns represent row-wise percentages. Nearest stereotyped BCR subsets Nearest stereotyped subsets were identified in 27 patients (28 total assignments). Nearest subsets #77 and #64B were most frequent (14.3% each). Unmutated IGHV predominated (67.9% of assignments): nearest subsets #64B, #6, #4, #8, and #202 were exclusive to U-CLL, while nearest subsets #77, #201, and #14 occurred only in M-CLL (Supplementary Table 3). Treatment modalities and relapse characteristics Of 145 patients, 82 (56.6%) required first-line systemic therapy. Most (n = 53) received conventional chemoimmunotherapy, primarily fludarabine-based regimens (FCR), bendamustine plus rituximab (BR), chlorambucil-based combinations, or cyclophosphamide-containing protocols (R-CHOP, R-CVP). Upfront targeted therapy was administered in 26 patients, including covalent and non-covalent BTK inhibitors (ibrutinib, acalabrutinib, pirtobrutinib, nemtabrutinib) and the BCL-2 inhibitor venetoclax, used as monotherapy or in fixed-duration combinations with anti-CD20 antibodies; detailed treatment distribution is provided in Supplementary Table 4. Disease progression requiring second-line therapy occurred in 29 patients (35.4% of treated). Most had initially received fludarabine-based chemoimmunotherapy (FCR, n = 17), with smaller proportions receiving chlorambucil-based combinations (n = 6), BR (n = 3), or R-CVP (n = 2). At relapse, treatment shifted toward targeted approaches: ibrutinib-based regimens were most frequently used (n = 15), followed by BR (n = 7) and venetoclax-based combinations (n = 3). The relapsed subgroup showed marked enrichment of adverse features: unmutated IGHV predominated (79.3%), del(11q) was present in 34.5%, and del(17p) in 17.2%. BCR stereotypy was identified in 13 of 29 relapsed patients. Subset #1 was the most frequent (n = 5), with relapse occurring in 5 of the 6 treated subset #1 patients in the overall cohort. Subsets #64B (n = 2) and #8 (n = 1) were also identified among relapsed cases. Among nearest subsets, nearest subset #64B (n = 3) and nearest subset #4 (n = 2) were represented, collectively suggesting that subsets #1 and #64B may be associated with heightened susceptibility to early treatment failure. Survival analyses Median follow-up was 43.0 months (range: 0–191). U-CLL patients had significantly shorter median TTFT than M-CLL (17.0 vs. 70.0 months; log-rank p < 0.0001; Fig. 1 ). Multivariate Cox regression confirmed unmutated IGHV as an independent predictor: Model 1 (Binet) HR 2.39 (95% CI 1.38–4.14; p = 0.0018), Model 2 (Rai) HR 2.28 (95% CI 1.31–3.95; p = 0.0034). Advanced clinical stage and del(11q) were also independent predictors in both models (p < 0.05). PFS showed no significant difference between U-CLL and M-CLL (median 48.0 vs. 42.0 months; p = 0.9922; Fig. 2 ). OS was likewise similar between groups (log-rank p = 0.3060; Fig. 3 ), consistent with the efficacy of modern targeted therapies in attenuating the historically adverse impact of unmutated IGHV. Among relapsed patients (n = 29), 79.3% harbored unmutated IGHV, del(11q) was present in 34.5%, and del(17p) in 17.2%. Subsets #1 and #64B were overrepresented, with relapse in 5 of 6 treated subset #1 patients, suggesting BCR stereotypy as a marker of early treatment failure. Discussion This study characterizes IGHV mutational status, clonal architecture, and BCR stereotypy in a Turkish CLL cohort. The proportion of U-CLL (55.2%) exceeded the approximately 40% reported in Western populations yet closely resembled frequencies in Mediterranean and Middle Eastern series [ 9 , 10 ], supporting the concept of population-specific immunogenetic variability in CLL. The median age at diagnosis (59 years) was lower than the 70–72 years reported in Western studies [ 7 , 11 , 12 ], mirroring figures from African and East Asian populations [ 13 , 14 ], and may partly reflect tertiary referral dynamics that concentrate younger, biologically complex patients. The IGHV gene repertoire mirrored Western and Mediterranean data— IGHV4-34 predominating in M-CLL, IGHV1-69 enriched in U-CLL—consistent with antigen-driven selection [ 6 , 9 , 15 – 17 ]. Oligoclonality (10.3%) fell within expected ranges [ 18 ]. Discordant mutational profiles were observed in one-third of oligoclonal cases, with U-CLL-like trajectories, suggesting that minor unmutated subclones may carry independent prognostic relevance. Among the most distinctive findings was the absence of stereotyped subset #2—prevalent in large Western cohorts [ 1 , 6 , 9 , 19 ]—whereas subset #1 was the most frequent major subset (6.2%). Consistent with prior reports [ 6 , 9 , 16 , 20 – 22 ], subset #1 patients uniformly harbored unmutated IGHV, presented at a younger age (median 56 years), and frequently exhibited del(17p) and trisomy 12. Richter transformation was observed in two patients; the case belonging to subset #8—carrying both del(17p) and trisomy 12 and dying 13 months after diagnosis—aligns with the aggressive biology and transformation risk associated with this subset [ 1 , 6 , 23 – 25 ]. The absence of subset #2 warrants consideration. In large European series this subset accounts for 2–5% of CLL cases and carries adverse prognosis linked to unmutated IGHV and del(11q) [ 1 , 9 , 19 ]. Two explanations may apply. First, stochastic variation cannot be excluded: with 145 patients, expected subset #2 cases would number two to seven, and sampling variability alone may explain non-detection. Second, population-level differences in HLA haplotype composition and microbial antigen exposure—both implicated in shaping the B-cell repertoire available for antigen selection—may reduce the frequency of this configuration [ 6 , 16 ]. Geographic variation in subset #2 prevalence has been noted in prior studies, with some Mediterranean and East Asian cohorts similarly reporting low or absent representation [ 25 , 26 ]. Confirmation requires larger multicenter Turkish series. Subset #3 cases uniformly displayed unmutated IGHV and del(11q), consistent with their established adverse phenotype [ 2 , 27 ]. Subset #4, by contrast, followed a reproducibly indolent course: all three cases harbored mutated IGHV with isolated del(13q), and none required therapy during follow-up [ 1 , 24 , 28 ]. Nearest stereotyped subsets showed clinically meaningful heterogeneity. Nearest subset #64B was invariably associated with aggressive disease and unmutated IGHV, while nearest subset #77 demonstrated rapid progression despite exclusive occurrence in M-CLL patients (median TTFT 1.5 months)—suggesting intrinsic BCR-driven aggressiveness that may override the protective effect of somatic hypermutation. Nearest subset #4 cases similarly diverged from the canonical indolent phenotype, primarily due to unmutated IGHV, underscoring that immunogenetic proximity does not guarantee equivalent clinical behavior. Cytogenetic findings were concordant with international data: del(11q) and genomic complexity enriched in U-CLL, del(13q) predominating in M-CLL (11, 15, 28–30). Replication of these associations in a Turkish cohort confirms that the relationship between IGHV status and cytogenetic risk transcends geographic boundaries. Within nearest subset matches, cytogenetic profiles were less predictable, with occasional discordance from expected lesion patterns, illustrating that immunogenetic similarity does not ensure cytogenetic or clinical homogeneity. Treatment failure concentrated among U-CLL patients with adverse cytogenetics; nearly 80% of relapsed cases harbored unmutated IGHV, reflecting the limited durability of chemoimmunotherapy in this population. At progression, treatment shifted toward targeted approaches—primarily BTK inhibitors and venetoclax-based regimens—and the absence of OS differences between groups is consistent with their established capacity to mitigate the survival disadvantage historically associated with unmutated IGHV [ 6 , 20 , 29 , 30 ]. The absence of a significant PFS difference should be interpreted cautiously given treatment heterogeneity: patients received regimens ranging from conventional chemoimmunotherapy to BTK inhibitors and venetoclax-based combinations, which have substantially different efficacy profiles. This heterogeneity may have diluted IGHV-dependent effects on post-treatment outcomes. The finding is nonetheless consistent with evidence that targeted therapies largely abrogate the prognostic impact of unmutated IGHV on survival [ 6 , 20 , 29 , 30 ]. Several limitations deserve acknowledgment. The retrospective, single-center design introduces selection bias, and our tertiary referral setting may have enriched the cohort for younger, biologically complex cases. FISH data were unavailable in approximately 20% of patients; comparison of patients with and without FISH data revealed no significant differences in age, sex, Rai stage, or IGHV status, suggesting missingness was largely at random. Numbers within certain stereotyped subsets were small, and those observations should be considered hypothesis-generating. In summary, CLL in Türkiye exhibits immunogenetic features that are regionally distinct yet biologically coherent with established clinico-molecular correlations. Integrating IGHV mutational status, BCR stereotypy, clonal architecture, and cytogenetic profiling may support more refined risk stratification. Multicenter prospective studies are needed to define how immunogenetic risk translates into outcomes in the era of targeted therapies. Declarations Conflict of Interest The authors declare no competing of interests. Ethics Approval The study was approved by the Institutional Ethics Committee of Ankara University (Approval No: 2023000138-1 [2023/138]). The study was conducted in accordance with the Declaration of Helsinki. Author Contributions SY, IK: Study conception and design, data collection, manuscript drafting, interpretation of data. RŞA, MBÖ, MY, GCS, ÖA, MÖ: Data collection, clinical or laboratory data acquisition. EDS: Statistical analysis. All authors approved the final version of the manuscript. Acknowledgments The authors thank Merve BESLER, PhD, and Laleh MADAYEN, PhD, at Molecular Pathology Laboratory, Department of Pathology, Ankara University for their technical assistance. Funding The authors did not receive any specific funding for this study. Competing Interests The authors declare that they have no competing interests. Consent to Participate Informed consent was obtained from all individual participants included in the study. All patients had previously provided consent for the use of their clinical and molecular data for research purposes in accordance with institutional policies. Consent to Publish Not applicable. 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Haematologica 105(11):2598–2607. https://doi.org/10.3324/haematol.2019.231027 Marinelli M, Ilari C, Xia Y, Del Giudice I, Cafforio L, Della Starza I et al (2016) Immunoglobulin gene rearrangements in Chinese and Italian patients with chronic lymphocytic leukemia. Oncotarget 7(15):20520–20531. https://doi.org/10.18632/oncotarget.7819 Wu SJ, Lin CT, Agathangelidis A, Lin LI, Kuo YY, Tien HF et al (2017) Distinct molecular genetics of chronic lymphocytic leukemia in Taiwan: clinical and pathogenetic implications. Haematologica 102(6):1085–1090. https://doi.org/10.3324/haematol.2016.157552 Sutton LA, Young E, Baliakas P, Hadzidimitriou A, Moysiadis T, Plevova K et al (2016) Different spectra of recurrent gene mutations in subsets of chronic lymphocytic leukemia harboring stereotyped B-cell receptors. Haematologica 101(8):959–967. https://doi.org/10.3324/haematol.2016.141812 Xochelli A, Baliakas P, Kavakiotis I, Agathangelidis A, Sutton LA, Minga E et al (2017) Chronic Lymphocytic Leukemia with Mutated IGHV4-34 Receptors: Shared and Distinct Immunogenetic Features and Clinical Outcomes. Clin Cancer Res 23(17):5292–5301. https://doi.org/10.1158/1078-0432.CCR-16-3100 Blombery P, Chatzikonstantinou T, Gerousi M, Rosenquist R, Gaidano G, Pospisilova S et al (2025) Resistance to targeted therapies in chronic lymphocytic leukemia: Current status and perspectives for clinical and diagnostic practice. Leukemia 39(9):2049–2060. https://doi.org/10.1038/s41375-025-02662-y Giudice ID, Foa R (2019) Another step forward in the 20-year history of IGHV mutations in chronic lymphocytic leukemia. Haematologica 104(2):219–221. https://doi.org/10.3324/haematol.2018.207399 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 16 May, 2026 Reviews received at journal 16 May, 2026 Reviewers agreed at journal 25 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor assigned by journal 14 Apr, 2026 Submission checks completed at journal 14 Apr, 2026 First submitted to journal 10 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9375280","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":629379546,"identity":"ac251dad-8d8b-4b9c-96ca-5cb088f697a7","order_by":0,"name":"Seher YÜKSEL","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYDCCAyCi4gCE/YB4LWcOMPCA2AlEa2Fsg2hhIEoL3+0DzJ95592Rsxc7/BBoi52cbgMBLZLnEtikebc9M+aRTjMAakk2NjtAQIvBGQY2Zt5thxN7pBNAWg4kbiNCC9Bhc0Ba0j8QrYVBmrcBpCWHSFskzzC2Sc45dtiY53ZOwYEEAyL8wneG+fCHNzWH5dhnp2/+8KHCTo6gFmCkNDDxINxJUDlU0w8iFY6CUTAKRsEIBQA4SEYaCKct3wAAAABJRU5ErkJggg==","orcid":"","institution":"Ankara University","correspondingAuthor":true,"prefix":"","firstName":"Seher","middleName":"","lastName":"YÜKSEL","suffix":""},{"id":629379547,"identity":"914a6f03-e43d-4c60-9402-9306f112847c","order_by":1,"name":"Rahmi Şinasi","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Rahmi","middleName":"","lastName":"Şinasi","suffix":""},{"id":629379548,"identity":"ad4d1751-f63a-4d6e-802c-8c02648ec87f","order_by":2,"name":"Merve YÜKSEL","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Merve","middleName":"","lastName":"YÜKSEL","suffix":""},{"id":629379549,"identity":"d936ede4-8adc-4c89-9088-856c4702f4cb","order_by":3,"name":"Mehmet Berk ÖRÜNCÜ","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"Berk","lastName":"ÖRÜNCÜ","suffix":""},{"id":629379550,"identity":"408eb9af-8b69-4476-ad8e-4cdb755a229a","order_by":4,"name":"Ezgi Dicle SERBES","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Ezgi","middleName":"Dicle","lastName":"SERBES","suffix":""},{"id":629379552,"identity":"ca9a1382-9e57-4c9e-a9ef-09c1d64f91af","order_by":5,"name":"Güldane CENGİZ SEVAL","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Güldane","middleName":"CENGİZ","lastName":"SEVAL","suffix":""},{"id":629379554,"identity":"b0d31030-5e36-42e3-81b7-6670a043c9b9","order_by":6,"name":"Önder ARSLAN","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Önder","middleName":"","lastName":"ARSLAN","suffix":""},{"id":629379556,"identity":"9d5858fe-938d-4b95-a990-ff64a6493258","order_by":7,"name":"Muhit ÖZCAN","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Muhit","middleName":"","lastName":"ÖZCAN","suffix":""},{"id":629379557,"identity":"d1610f09-ffe7-49d7-a7f0-730854dc82e7","order_by":8,"name":"Işınsu KUZU","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Işınsu","middleName":"","lastName":"KUZU","suffix":""}],"badges":[],"createdAt":"2026-04-10 06:23:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9375280/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9375280/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107965893,"identity":"5494d3e0-750c-4e3e-b87f-da9ebfdcdb4a","added_by":"auto","created_at":"2026-04-28 05:41:45","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105866,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves for time to treatment (TTFT) stratified by IGHV mutational status (Median: 17.0 vs. 70.0 months; log-rank p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9375280/v1/97eae292d65bc2bba7a3b5be.jpg"},{"id":107965882,"identity":"f148f361-b1fd-4bc2-8c26-4fc1f2d5eae7","added_by":"auto","created_at":"2026-04-28 05:41:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":102230,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves for progression-free survival (PFS) in treated patients stratified by IGHV mutational status (Median: 42.0 vs. 48.0 months; log-rank p = 0.9922).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9375280/v1/7b126e6897c533253005dec2.jpg"},{"id":107965885,"identity":"e3f594c4-e364-4872-b557-3d1705c1d72a","added_by":"auto","created_at":"2026-04-28 05:41:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":104730,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves for overall survival (OS) by IGHV mutational status (log-rank p = 0.3060).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9375280/v1/8c7c44bc029379f2d281361b.jpg"},{"id":107966008,"identity":"f65fbbac-f157-467f-8875-d5baba4ac1bc","added_by":"auto","created_at":"2026-04-28 05:42:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":647731,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9375280/v1/f025e29a-4f47-48fc-98fd-f218861a0ea6.pdf"},{"id":107965913,"identity":"f5451648-9148-4a5d-a934-df5ee3e94793","added_by":"auto","created_at":"2026-04-28 05:41:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28440,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9375280/v1/5e2ac1e92c1d4881456ced9f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"IGHV Mutational Status and BCR Stereotypy in Chronic Lymphocytic Leukemia: A Turkish Cohort Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic lymphocytic leukemia (CLL) is an indolent B-cell malignancy accounting for approximately 30\u0026ndash;40% of adult leukemias, yet its clinical course is remarkably heterogeneous [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While many patients remain stable for years without requiring therapy, others progress rapidly, highlighting the importance of reliable biological markers for prognostic stratification and treatment planning.\u003c/p\u003e \u003cp\u003eContemporary risk assessment integrates the Rai and Binet staging systems with FISH-detected cytogenetic abnormalities\u0026mdash;del(17p), del(11q), trisomy 12, and del(13q)\u0026mdash;and recurrent gene mutations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The prognostic significance of somatic hypermutation (SHM) within the immunoglobulin heavy chain variable region (IGHV) gene was established in 1999 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; patients with unmutated IGHV (U-CLL; \u0026ge; 98% germline homology) experience more aggressive disease and shorter TTFT, while mutated IGHV (M-CLL; \u0026lt; 98% homology) confers a more indolent trajectory [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u0026mdash;distinctions formalized in the CLL-IPI [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImmunogenetic studies have shown that approximately 40% of CLL patients express quasi-identical BCR immunoglobulins\u0026mdash;a phenomenon termed BCR stereotypy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Subsets sharing VH CDR3 characteristics are classified as major (\u0026ge;\u0026thinsp;20 cases, reproducible clinical behavior) or minor [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite extensive investigation in Western populations, real-world immunogenetic data from T\u0026uuml;rkiye remain scarce. We therefore analyzed a Turkish CLL cohort to characterize IGHV mutational status, IGHV gene repertoire, BCR stereotypy, and their clinical and cytogenetic correlates.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and patients\u003c/h2\u003e \u003cp\u003eThis retrospective study included patients diagnosed with CLL at Ankara University School of Medicine between 2019 and 2025. Patients were eligible if IGHV mutational analysis had been performed and adequate clinical data were available. Those lacking IGHV analysis or presenting with concurrent hematologic malignancies were excluded. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ankara University Human Research Ethics Committee (Approval No: 2023000138-1 [2023/138]).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection and cytogenetics\u003c/h3\u003e\n\u003cp\u003eClinical and laboratory data were retrospectively obtained from electronic medical records. Baseline variables included age, sex, Rai and Binet stage at diagnosis, and absolute lymphocyte count. FISH analysis was performed on peripheral blood at the time of diagnosis using probes for del(13q), trisomy 12, del(11q), and del(17p); del(17p) was considered a high-risk cytogenetic abnormality.\u003c/p\u003e\n\u003ch3\u003eIGHV mutational analysis\u003c/h3\u003e\n\u003cp\u003e IGHV mutational status was determined in accordance with the recommendations of the European Research Initiative on CLL (ERIC). DNA was extracted from peripheral blood, bone marrow aspirates, or formalin-fixed paraffin-embedded (FFPE) tissue. Next-generation sequencing (NGS) was performed using the LymphoTrack\u0026reg; Dx IGHV Somatic Hypermutation Assay Panel on the Illumina MiSeq platform. Sequences were analyzed using the IMGT database with a 98% homology cutoff. Only productive IGHV rearrangements were included; in patients with multiple productive clones, the dominant clone determined classification. Discordant cases (mutated and unmutated productive clones coexisting) were classified as U-CLL per ERIC recommendations. Dominant sequences were subsequently analyzed using the ARResT/AssignSubsets platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://arrest.tools/assignsubsets\u003c/span\u003e\u003cspan address=\"http://arrest.tools/assignsubsets\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for immunogenetic classification.\u003c/p\u003e\n\u003ch3\u003eBCR stereotypy analysis\u003c/h3\u003e\n\u003cp\u003eStereotyped BCR subset assignment was performed using the ARResT/AssignSubsets tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://arrest.tools/assignsubsets\u003c/span\u003e\u003cspan address=\"http://arrest.tools/assignsubsets\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) based on IMGT-defined immunogenetic criteria, including IGHV gene clan usage, VH CDR3 length, amino acid identity, and physicochemical similarity. Cases fulfilling full assignment criteria were classified as major stereotyped subsets; those demonstrating immunogenetic similarity without meeting strict thresholds were designated nearest stereotyped subsets.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables were compared using chi-square or Fisher's exact tests; continuous variables were assessed using the Mann\u0026ndash;Whitney U test or independent-samples t-test. Survival outcomes (TTFT, PFS, OS) were analyzed by Kaplan\u0026ndash;Meier method with log-rank comparisons. Multivariate analysis of TTFT employed Cox proportional hazards regression incorporating age, sex, clinical stage, and high-risk cytogenetics. Analyses were performed using IBM SPSS Statistics version 26.0; survival curves were generated in Python 3.10 with Matplotlib. Missing data were handled using an available-case approach.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eA total of 145 patients were included. Median age at diagnosis was 59.0 years (range, 30\u0026ndash;93), with a male predominance (n\u0026thinsp;=\u0026thinsp;88, 60.7%). IGHV status was unmutated in 80 patients (55.2%) and mutated in 65 patients (44.8%). Baseline characteristics stratified by IGHV status are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociation of IGHV mutational status with clinical features\u003c/h3\u003e\n\u003cp\u003eMutated IGHV was associated with earlier clinical stage. In M-CLL, 32.3% presented at Rai stage 0 versus 16.2% in U-CLL, and Binet A was more frequent in M-CLL when compared with U-CLL (53.8% vs. 37.5%; p\u0026thinsp;=\u0026thinsp;0.068). Risk stratification using the CLL-IPI revealed a significant association with IGHV mutational status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). High and very high-risk CLL-IPI scores were predominantly clustered within the unmutated group (72.0%), whereas these risk categories accounted for only 28.0% of patients with mutated IGHV. Lymphocyte count at diagnosis did not differ between groups (p\u0026thinsp;=\u0026thinsp;0.573).\u003c/p\u003e \u003cp\u003eCytogenetic data were available for 121 patients (83.4% of the cohort). Cytogenetic profiles showed distinct distributions by IGHV status. Del(13q) was significantly more frequent in M-CLL than U-CLL (66.7% vs. 37.5%; p\u0026thinsp;=\u0026thinsp;0.004), while del(11q) predominated in U-CLL (27.0% vs. 8.0%; p\u0026thinsp;=\u0026thinsp;0.014). Multiple cytogenetic abnormalities were more common in U-CLL (29.4% vs. 11.3%; p\u0026thinsp;=\u0026thinsp;0.029). While trisomy 12 (27.4% vs. 14.9%) and del(17p) (16.7% vs. 9.4%) were numerically higher in U-CLL, these differences did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.162 and p\u0026thinsp;=\u0026thinsp;0.290, respectively).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic and clinical characteristics of the study cohort according to IGHV mutational status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal cohort (n\u0026thinsp;=\u0026thinsp;145)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIGHV mutated\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;65)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIGHV unmutated\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e, years, median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.0 (30\u0026ndash;93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.5 (33\u0026ndash;86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.5 (30\u0026ndash;93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (60.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (56.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (39.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocyte count\u003c/b\u003e (cells/\u0026micro;L), median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,000 (1,730\u0026thinsp;\u0026minus;\u0026thinsp;420,000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,345 (1,730\u0026thinsp;\u0026minus;\u0026thinsp;420,000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,960 (2,330\u0026thinsp;\u0026minus;\u0026thinsp;294,710)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRai Stage\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (16.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (13.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBinet Stage\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCytogenetics (FISH)\u003c/b\u003e, n/eval (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edel(13q)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56/112 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32/48 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24/64 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edel(11q)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21/113 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4/50 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17/63 (27.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edel(17p)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16/119 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5/53 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11/66 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrisomy 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24/109 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7/47 (14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17/62 (27.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple abnormalities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26/121 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6/53 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20/68 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.029*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cem\u003eData are presented as number (percentage) for categorical variables and median (minimum\u0026ndash;maximum) for continuous variables. Percentages were calculated based on the number of patients with available data in each group. *Statistically significant.\u003c/em\u003e \u003cb\u003eAbbreviations\u003c/b\u003e: \u003cb\u003eCLL\u003c/b\u003e: \u003cem\u003eChronic Lymphocytic Leukemia;\u003c/em\u003e \u003cb\u003eFISH\u003c/b\u003e: \u003cem\u003eFluorescence in situ hybridization;\u003c/em\u003e \u003cb\u003eIGHV\u003c/b\u003e: \u003cem\u003eImmunoglobulin heavy chain variable region.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIGHV gene repertoire\u003c/h2\u003e \u003cp\u003eA total of 161 productive IGHV rearrangements were identified among 145 patients; 130 (89.7%) had a single productive rearrangement and 15 patients (10.3%) had multiple. The most frequently used IGHV genes were \u003cem\u003eIGHV4-34\u003c/em\u003e (11.2%), \u003cem\u003eIGHV1-69\u003c/em\u003e (8.1%), and \u003cem\u003eIGHV3-23\u003c/em\u003e (6.8%). Gene usage differed by mutational status: \u003cem\u003eIGHV4-34\u003c/em\u003e predominated in M-CLL (20.8%), and \u003cem\u003eIGHV1-69\u003c/em\u003e in U-CLL (13.1%), as shown in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBiclonal IGHV rearrangements and discordant IGHV mutational status\u003c/h2\u003e \u003cp\u003eAmong 15 patients with multiple productive rearrangements, 10 showed concordant mutational status and 5 (3.4%) were discordant harboring both mutated and unmutated clones (Supplementary Table\u0026nbsp;2). \u003cem\u003eIGHV4-34\u003c/em\u003e was recurrent in discordant mutated clones. All five were classified as U-CLL per ERIC recommendations. Four of the five (80%) required systemic therapy with short TTFT (0, 8, 24, and 72 months), with clinical trajectories consistent with U-CLL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBCR stereotypy\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eMajor stereotyped BCR subsets\u003c/h2\u003e \u003cp\u003eMajor stereotyped BCR subsets were identified in 23 of 145 patients (15.9%) using ARResT/AssignSubsets. Subset #1 was most frequent (n\u0026thinsp;=\u0026thinsp;9, 39.1%), followed by subsets #3 and #4 (each n\u0026thinsp;=\u0026thinsp;3, 13.0%). Subsets #1, #3, #64B, #7H, #99, #31, and #8 were exclusive to U-CLL; subsets #4, #77, and #14 were confined to M-CLL \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of major stereotyped BCR subsets according to IGHV mutational status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor subsets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients (n\u0026thinsp;=\u0026thinsp;23), n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutated IGHV, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnmutated IGHV, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #64B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #7H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubset #8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e23 (100\u003c/b\u003e%\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5 (21.7\u003c/b\u003e%\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e18 (78.3\u003c/b\u003e%\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ePercentages in the \u0026ldquo;Mutated IGHV\u0026rdquo; and \u0026ldquo;Unmutated IGHV\u0026rdquo; columns represent row-wise percentages.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eNearest stereotyped BCR subsets\u003c/h2\u003e \u003cp\u003eNearest stereotyped subsets were identified in 27 patients (28 total assignments). Nearest subsets #77 and #64B were most frequent (14.3% each). Unmutated IGHV predominated (67.9% of assignments): nearest subsets #64B, #6, #4, #8, and #202 were exclusive to U-CLL, while nearest subsets #77, #201, and #14 occurred only in M-CLL (Supplementary Table\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTreatment modalities and relapse characteristics\u003c/h2\u003e \u003cp\u003eOf 145 patients, 82 (56.6%) required first-line systemic therapy. Most (n\u0026thinsp;=\u0026thinsp;53) received conventional chemoimmunotherapy, primarily fludarabine-based regimens (FCR), bendamustine plus rituximab (BR), chlorambucil-based combinations, or cyclophosphamide-containing protocols (R-CHOP, R-CVP). Upfront targeted therapy was administered in 26 patients, including covalent and non-covalent BTK inhibitors (ibrutinib, acalabrutinib, pirtobrutinib, nemtabrutinib) and the BCL-2 inhibitor venetoclax, used as monotherapy or in fixed-duration combinations with anti-CD20 antibodies; detailed treatment distribution is provided in Supplementary Table\u0026nbsp;4.\u003c/p\u003e \u003cp\u003eDisease progression requiring second-line therapy occurred in 29 patients (35.4% of treated). Most had initially received fludarabine-based chemoimmunotherapy (FCR, n\u0026thinsp;=\u0026thinsp;17), with smaller proportions receiving chlorambucil-based combinations (n\u0026thinsp;=\u0026thinsp;6), BR (n\u0026thinsp;=\u0026thinsp;3), or R-CVP (n\u0026thinsp;=\u0026thinsp;2). At relapse, treatment shifted toward targeted approaches: ibrutinib-based regimens were most frequently used (n\u0026thinsp;=\u0026thinsp;15), followed by BR (n\u0026thinsp;=\u0026thinsp;7) and venetoclax-based combinations (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003cp\u003eThe relapsed subgroup showed marked enrichment of adverse features: unmutated IGHV predominated (79.3%), del(11q) was present in 34.5%, and del(17p) in 17.2%. BCR stereotypy was identified in 13 of 29 relapsed patients. Subset #1 was the most frequent (n\u0026thinsp;=\u0026thinsp;5), with relapse occurring in 5 of the 6 treated subset #1 patients in the overall cohort. Subsets #64B (n\u0026thinsp;=\u0026thinsp;2) and #8 (n\u0026thinsp;=\u0026thinsp;1) were also identified among relapsed cases. Among nearest subsets, nearest subset #64B (n\u0026thinsp;=\u0026thinsp;3) and nearest subset #4 (n\u0026thinsp;=\u0026thinsp;2) were represented, collectively suggesting that subsets #1 and #64B may be associated with heightened susceptibility to early treatment failure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSurvival analyses\u003c/h2\u003e \u003cp\u003eMedian follow-up was 43.0 months (range: 0\u0026ndash;191). U-CLL patients had significantly shorter median TTFT than M-CLL (17.0 vs. 70.0 months; log-rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Multivariate Cox regression confirmed unmutated IGHV as an independent predictor: Model 1 (Binet) HR 2.39 (95% CI 1.38\u0026ndash;4.14; p\u0026thinsp;=\u0026thinsp;0.0018), Model 2 (Rai) HR 2.28 (95% CI 1.31\u0026ndash;3.95; p\u0026thinsp;=\u0026thinsp;0.0034). Advanced clinical stage and del(11q) were also independent predictors in both models (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003ePFS showed no significant difference between U-CLL and M-CLL (median 48.0 vs. 42.0 months; p\u0026thinsp;=\u0026thinsp;0.9922; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). OS was likewise similar between groups (log-rank p\u0026thinsp;=\u0026thinsp;0.3060; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), consistent with the efficacy of modern targeted therapies in attenuating the historically adverse impact of unmutated IGHV.\u003c/p\u003e \u003cp\u003eAmong relapsed patients (n\u0026thinsp;=\u0026thinsp;29), 79.3% harbored unmutated IGHV, del(11q) was present in 34.5%, and del(17p) in 17.2%. Subsets #1 and #64B were overrepresented, with relapse in 5 of 6 treated subset #1 patients, suggesting BCR stereotypy as a marker of early treatment failure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study characterizes IGHV mutational status, clonal architecture, and BCR stereotypy in a Turkish CLL cohort. The proportion of U-CLL (55.2%) exceeded the approximately 40% reported in Western populations yet closely resembled frequencies in Mediterranean and Middle Eastern series [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], supporting the concept of population-specific immunogenetic variability in CLL.\u003c/p\u003e \u003cp\u003eThe median age at diagnosis (59 years) was lower than the 70\u0026ndash;72 years reported in Western studies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], mirroring figures from African and East Asian populations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and may partly reflect tertiary referral dynamics that concentrate younger, biologically complex patients.\u003c/p\u003e \u003cp\u003eThe IGHV gene repertoire mirrored Western and Mediterranean data\u0026mdash;\u003cem\u003eIGHV4-34\u003c/em\u003e predominating in M-CLL, \u003cem\u003eIGHV1-69\u003c/em\u003e enriched in U-CLL\u0026mdash;consistent with antigen-driven selection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Oligoclonality (10.3%) fell within expected ranges [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Discordant mutational profiles were observed in one-third of oligoclonal cases, with U-CLL-like trajectories, suggesting that minor unmutated subclones may carry independent prognostic relevance.\u003c/p\u003e \u003cp\u003eAmong the most distinctive findings was the absence of stereotyped subset #2\u0026mdash;prevalent in large Western cohorts [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u0026mdash;whereas subset #1 was the most frequent major subset (6.2%). Consistent with prior reports [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], subset #1 patients uniformly harbored unmutated IGHV, presented at a younger age (median 56 years), and frequently exhibited del(17p) and trisomy 12. Richter transformation was observed in two patients; the case belonging to subset #8\u0026mdash;carrying both del(17p) and trisomy 12 and dying 13 months after diagnosis\u0026mdash;aligns with the aggressive biology and transformation risk associated with this subset [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe absence of subset #2 warrants consideration. In large European series this subset accounts for 2\u0026ndash;5% of CLL cases and carries adverse prognosis linked to unmutated IGHV and del(11q) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Two explanations may apply. First, stochastic variation cannot be excluded: with 145 patients, expected subset #2 cases would number two to seven, and sampling variability alone may explain non-detection. Second, population-level differences in HLA haplotype composition and microbial antigen exposure\u0026mdash;both implicated in shaping the B-cell repertoire available for antigen selection\u0026mdash;may reduce the frequency of this configuration [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Geographic variation in subset #2 prevalence has been noted in prior studies, with some Mediterranean and East Asian cohorts similarly reporting low or absent representation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Confirmation requires larger multicenter Turkish series.\u003c/p\u003e \u003cp\u003eSubset #3 cases uniformly displayed unmutated IGHV and del(11q), consistent with their established adverse phenotype [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Subset #4, by contrast, followed a reproducibly indolent course: all three cases harbored mutated IGHV with isolated del(13q), and none required therapy during follow-up [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNearest stereotyped subsets showed clinically meaningful heterogeneity. Nearest subset #64B was invariably associated with aggressive disease and unmutated IGHV, while nearest subset #77 demonstrated rapid progression despite exclusive occurrence in M-CLL patients (median TTFT 1.5 months)\u0026mdash;suggesting intrinsic BCR-driven aggressiveness that may override the protective effect of somatic hypermutation. Nearest subset #4 cases similarly diverged from the canonical indolent phenotype, primarily due to unmutated IGHV, underscoring that immunogenetic proximity does not guarantee equivalent clinical behavior.\u003c/p\u003e \u003cp\u003eCytogenetic findings were concordant with international data: del(11q) and genomic complexity enriched in U-CLL, del(13q) predominating in M-CLL (11, 15, 28\u0026ndash;30). Replication of these associations in a Turkish cohort confirms that the relationship between IGHV status and cytogenetic risk transcends geographic boundaries. Within nearest subset matches, cytogenetic profiles were less predictable, with occasional discordance from expected lesion patterns, illustrating that immunogenetic similarity does not ensure cytogenetic or clinical homogeneity.\u003c/p\u003e \u003cp\u003eTreatment failure concentrated among U-CLL patients with adverse cytogenetics; nearly 80% of relapsed cases harbored unmutated IGHV, reflecting the limited durability of chemoimmunotherapy in this population. At progression, treatment shifted toward targeted approaches\u0026mdash;primarily BTK inhibitors and venetoclax-based regimens\u0026mdash;and the absence of OS differences between groups is consistent with their established capacity to mitigate the survival disadvantage historically associated with unmutated IGHV [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe absence of a significant PFS difference should be interpreted cautiously given treatment heterogeneity: patients received regimens ranging from conventional chemoimmunotherapy to BTK inhibitors and venetoclax-based combinations, which have substantially different efficacy profiles. This heterogeneity may have diluted IGHV-dependent effects on post-treatment outcomes. The finding is nonetheless consistent with evidence that targeted therapies largely abrogate the prognostic impact of unmutated IGHV on survival [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral limitations deserve acknowledgment. The retrospective, single-center design introduces selection bias, and our tertiary referral setting may have enriched the cohort for younger, biologically complex cases. FISH data were unavailable in approximately 20% of patients; comparison of patients with and without FISH data revealed no significant differences in age, sex, Rai stage, or IGHV status, suggesting missingness was largely at random. Numbers within certain stereotyped subsets were small, and those observations should be considered hypothesis-generating.\u003c/p\u003e \u003cp\u003eIn summary, CLL in T\u0026uuml;rkiye exhibits immunogenetic features that are regionally distinct yet biologically coherent with established clinico-molecular correlations. Integrating IGHV mutational status, BCR stereotypy, clonal architecture, and cytogenetic profiling may support more refined risk stratification. Multicenter prospective studies are needed to define how immunogenetic risk translates into outcomes in the era of targeted therapies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\n\u003cp\u003eThe authors declare no competing of interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\n\u003cp\u003eThe study was approved by the Institutional Ethics Committee of Ankara University (Approval No: 2023000138-1 [2023/138]). The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\n\u003cp\u003eSY, IK: Study conception and design, data collection, manuscript drafting, interpretation of data.\u003c/p\u003e\n\u003cp\u003eRŞA, MB\u0026Ouml;, MY, GCS, \u0026Ouml;A, M\u0026Ouml;: Data collection, clinical or laboratory data acquisition.\u003c/p\u003e\n\u003cp\u003eEDS: Statistical analysis.\u003c/p\u003e\n\u003cp\u003eAll authors approved the final version of the manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\n\u003cp\u003eThe authors thank Merve BESLER, PhD, and Laleh MADAYEN, PhD, at Molecular Pathology Laboratory, Department of Pathology, Ankara University for their technical assistance.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive any specific funding for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study. All patients had previously provided consent for the use of their clinical and molecular data for research purposes in accordance with institutional policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to patient confidentiality but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStamatopoulos K, Agathangelidis A, Rosenquist R, Ghia P (2017) Antigen receptor stereotypy in chronic lymphocytic leukemia. 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Haematologica 104(2):219\u0026ndash;221. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3324/haematol.2018.207399\u003c/span\u003e\u003cspan address=\"10.3324/haematol.2018.207399\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chronic lymphocytic leukemia, IGHV mutational status, BCR stereotypy, major stereotyped subsets, real-world cohort","lastPublishedDoi":"10.21203/rs.3.rs-9375280/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9375280/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective:\u003c/h2\u003e \u003cp\u003eImmunoglobulin heavy chain variable region (IGHV) mutational status and B-cell receptor (BCR) stereotypy are established prognostic markers in chronic lymphocytic leukemia (CLL). However, immunogenetic data from T\u0026uuml;rkiye and surrounding regions are scarce. We evaluated IGHV mutational status, BCR stereotypy including nearest subset assignment, and their clinical and cytogenetic correlates in a real-world Turkish CLL cohort.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed 145 patients with CLL at a tertiary referral center in T\u0026uuml;rkiye. IGHV mutational status was determined by next-generation sequencing (98% germline homology cutoff). BCR stereotypy was assigned using ARResT/AssignSubsets. Cytogenetic abnormalities were assessed by fluorescence in situ hybridization (FISH). Time-to-first treatment (TTFT), progression-free survival (PFS), and overall survival (OS) were analyzed by Kaplan\u0026ndash;Meier method, with multivariate Cox regression for TTFT.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eUnmutated IGHV was detected in 55.2% of patients, higher than Western reports but consistent with Mediterranean and Middle Eastern cohorts. Unmutated cases showed adverse cytogenetics\u0026mdash;del(11q) and higher genomic complexity\u0026mdash;whereas del(13q) predominated in mutated cases. TTFT was significantly shorter in U-CLL when compared to M-CLL (17.0 vs. 70.0 months; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). PFS and OS did not differ statistically. Major stereotyped subsets were present in 15.9% of patients; subset #2 was absent, while subset #1 was predominant (39.1%). Subsets #1 and #64B were overrepresented among relapsed cases. Nearest subset #77 showed rapid progression despite mutated IGHV.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eCLL in T\u0026uuml;rkiye demonstrates region-specific immunogenetic features while preserving established clinico-biological correlations. Integration of IGHV status, cytogenetics, and BCR stereotypy may improve risk stratification in underrepresented populations.\u003c/p\u003e","manuscriptTitle":"IGHV Mutational Status and BCR Stereotypy in Chronic Lymphocytic Leukemia: A Turkish Cohort Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 05:40:19","doi":"10.21203/rs.3.rs-9375280/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-16T18:31:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-16T13:54:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91300401007799904844871537091558748332","date":"2026-04-25T08:13:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T03:58:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-14T12:58:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-14T12:58:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Annals of Hematology","date":"2026-04-10T06:07:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b0439359-ff77-4257-aeb8-cac56bd67318","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-16T18:31:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-16T13:54:32+00:00","index":12,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T18:38:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 05:40:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9375280","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9375280","identity":"rs-9375280","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}