Antić, Darko

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

Abstract The IGHV4-34 gene is very frequent (~10%) in the B cell receptor immunoglobulin (BcR IG) gene repertoire of chronic lymphocytic leukemia (CLL). Over 30% of IGHV4-34 CLL cases can be assigned to different subsets with stereotyped BcR IG. The largest is subset #4 which represents ~1% of all CLL and ~10% of IGHV4-34 CLL and is considered a prototype for indolent disease. The BcR IG of a great majority (~85%) of IGHV4-34 CLL cases carry a significant load of somatic hypermutation (SHM), often with distinctive SHM patterns. This holds especially true for stereotyped subsets and is suggestive of particular modes of interactions with the selecting antigen(s). In detail, subsets #4 and #16, both involving IgG-switched cases (IgG-CLL), exhibit the greatest sequence similarity in SHM profiles, whereas they differ in this respect from IgM/D subsets #29 and #201. Prompted by these observations, here we explored the extent that these subset-biased SHM profiles in different IGHV4-34 stereotyped subsets were reflected in distinct demographics, clinical presentation, genomic aberrations and outcomes. Within a multi-institutional series of 20,331 CLL patients, 1790 (8.8%) expressed IGHV4-34 BcR IG. Following established bioinformatics approaches for the identification of BcR IG stereotypy, 573/1790 IGHV4-34 CLL cases (32%) were assigned to stereotyped subsets; of these, 340 cases (19% of all IGHV4-34 CLL and 60% of stereotyped IGHV4-34 cases) belonged to subsets #4, #16, #29 and #201, all concerning IGHV-mutated CLL (M-CLL). Clinicobiological information was available for 275/340 patients: #4, n=150; #16, n=44; #29, n=39; and #201, n=42. Comparisons between subsets revealed no differences in gender and age distribution. Interestingly, however, 36-43% of each subset cases were young for CLL (defined as patients aged ≤55 years), which is higher compared to general CLL cohorts, where young patients generally account for ~25% of cases. In contrast, significant differences were identified between subsets regarding: (i) disease stage at diagnosis, with >90% of IgG subsets #4 and #16 diagnosed at Binet stage A versus 83% in subset #201 and 74% in subset #29 (p=0.029); (ii) CD38 expression, ranging from 1% in subset #4 to 10% in subset #201 (p=0.013); (iii) the distribution of del(13q), peaking at a remarkable 92% in subset #29 versus only 37% in subset #16 (p<0.0001). Regarding other genomic aberrations, they were either absent (NOTCH1 mutations) or rare (SF3B1 mutations, trisomy 12, del(11q), TP53 aberrations due to either del(17p) and/or TP53 mutations). The sole exception concerned a high frequency (14%) of TP53 aberrations in subset #29 (p<0.05 compared with the other subsets), which is notable for M-CLL cases in general. Time to first treatment (TTFT) could be analyzed in 228 cases. IgG subsets #4 and #16 had significantly (p=0.036) longer TTFT (median TTFT: not yet reached) compared to the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). In conclusion, we have identified distinct clinicobiological profiles for different stereotyped IGHV4-34 M-CLL subsets, highlighting subsets #4 and #16 as particularly indolent, which is important for both medical and social reasons, especially considering that a significant proportion of patients in these subsets are diagnosed at younger ages. Our findings support the notion that BcR IG stereotypy refines prognostication in CLL, superseding the crude immunogenetic distinction based on SHM load only. Additionally, the observed heterogeneity suggests that not all M-CLL are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Disclosures Tausch: Gilead: Other: Travel support. Shanafelt:Glaxo-Smith_Kline: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Polyphenon E Int'l: Research Funding; Hospira: Research Funding; Janssen: Research Funding; Pharmactckucs: Research Funding; Cephalon: Research Funding. Niemann:Gilead: Consultancy; Janssen: Consultancy; Roche: Consultancy; Novartis: Other: Travel grant. Langerak:InVivoScribe: Patents & Royalties: Licensing of IP and Patent on BIOMED-2-based methods for PCR-based Clonality Diagnostics.; DAKO: Patents & Royalties: Licensing of IP and Patent on Split-Signal FISH. Royalties for Dept. of Immunology, Erasmus MC, Rotterdam, NL; Roche: Other: Lab services in the field of MRD diagnostics provided by Dept of Immunology, Erasmus MC (Rotterdam). Hallek:Celgene: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; AbbVie: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Roche: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Boehringher Ingelheim: Honoraria, Other: Speakers Bureau and/or Advisory Boards; Pharmacyclics: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Mundipharma: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Janssen: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Gilead: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding. Ghia:Janssen Pharmaceuticals: Research Funding.

Background: Thromboembolism (TE) is one of major causes of morbidity and mortality in patients with malignancy. Pathophysiological connection between TE and inflammation has been established and it is being thoroughly studied recently. The neutrophil to lymphocyte ratio (NLR) and the platelet to lymphocyte ratio (PLR) are biomarkers for systemic inflammation and might represent a yet unrecognized risk factor for development of venous thromboembolism in lymphoma patients having in mind chronic inflammatory milieu specific for lymphomas. Aims: We aimed to investigate the association between NLR, PLR and future risk of TE, in a prospective cohort of lymphoma patients receiving chemotherapy. Methods: We prospectively included 630 patients with B cell non Hodgkin lymphoma /indolent and agressive/, T cell non Hodgkin lymphoma and Hodgkin lymphoma who were diagnosed and treated (period 2014-2019.) at the Clinic for Hematology, Clinical Center of Serbia. Data for newly diagnosed patients, who had completed a minimum of one chemotherapy cycle, were collected for venous TE events from time of diagnosis to 3 months after the last cycle of therapy. NLR and PLR were calculated according to the CBC with differential count. TE complications were diagnosed based on clinical examination, laboratory evaluation and radiographic studies (duplex venous ultrasound, contrast-enhanced computed tomography scan, magnetic resonance imaging (MRI)). Response to therapy was assessed according to Cheson criteria. Logistic regression analysis and ROC curve were performed to assess the association of NLR and PLR with TE and therapy response. Cox regression and Kaplan Meier analysis were used to assess overall survival. Results: The mean age in our group of patients was 53 years (range, 18-89 years) while 52.8% were males. Most patients had advanced stage disease: clinical stage III 20.6% and stage IV, 41.5%. A total of 327 patients (51.9%) had aggressive NHL; 175 (27.8%) had indolent NHL; 102 (16.2%) had HL; 26 (4.1%) had T cell NHL. 51 (8.2%) patients developed thromboembolic events. NLR and PLR were significantly higher in TE patients compared to patients without TE (p=0.001 and p=0.002, respectively). The NLR was positively associated with PLR (p&lt;0.001). A positive NLR was considered 3 or higher, while a positive PLR was a ratio of 10 or more. The ROC curve analysis demonstrated acceptable specificity and sensitivity of NLR and PLR in predicting TE. NLR and PLR were found to be prognostic factors for the TE (relative risk [RR] = 2.9, 95% confidence interval [CI] = 1.6-5.3, p=0.001 and RR=2.7, 95% CI =1.4-5.1, p=0.002, respectively) as well as for overall response to therapy (RR=2.7, 95%CI=1.7-5.7, p&lt;0.001 and RR=2.0, 95%CI=1.1-3.4, p=0.015, respectively). Regarding the overall survival, in univariate analysis there was an association of the development of TE and decreased survival, while in multivariate model NLR was found to be an independent risk factor for overall survival in lymphoma patients (HR=1.8, 95%CI=1.1-2.9, p=0.024) (Figure 1). Summary/Conclusion: NLR could represent useful clinical predictor of TE complications in patients with lymphoma without additional costs to the national health systems. Our research showed that NLR is also predictive for response to therapy and overall survival of lymphoma patients. Simplicity, cost effectiveness, and rapid turn around qualify this new tool for routine prognostic assessment in lymphoma patients. Figure 1 Disclosures No relevant conflicts of interest to declare.

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

Lymphoma patients are at increased risk of thromboembolic events but thromboprophylaxis in these patients is largely underused. We sought to develop and validate a simple model, based on individual clinical and laboratory patient characteristics that would designate lymphoma patients at risk for thromboembolic event. The study population included 1,820 lymphoma patients who were treated in the Lymphoma Departments at the Clinics of Hematology, Clinical Center of Serbia and Clinical Center Kragujevac. The model was developed using data from a derivation cohort (n = 1,236), and further assessed in the validation cohort (n = 584). Sixty‐five patients (5.3%) in the derivation cohort and 34 (5.8%) patients in the validation cohort developed thromboembolic events. The variables independently associated with risk for thromboembolism were: previous venous and/or arterial events, mediastinal involvement, BMI>30 kg/m2, reduced mobility, extranodal localization, development of neutropenia and hemoglobin level < 100g/L. Based on the risk model score, the population was divided into the following risk categories: low (score 0‐1), intermediate (score 2‐3), and high (score >3). For patients classified at risk (intermediate and high‐risk scores), the model produced negative predictive value of 98.5%, positive predictive value of 25.1%, sensitivity of 75.4%, and specificity of 87.5%. A high‐risk score had positive predictive value of 65.2%. The diagnostic performance measures retained similar values in the validation cohort. Developed prognostic Thrombosis Lymphoma – ThroLy score is more specific for lymphoma patients than any other available score targeting thrombosis in cancer patients. Am. J. Hematol. 91:1014–1019, 2016. © 2016 Wiley Periodicals, Inc.