AbstractAntigen stimulation may be important for splenic marginal zone lymphoma pathogenesis. To address this hypothesis, the occurrence of stereotyped B-cell receptors was investigated in 133 SMZL (26 HCV+) compared with 4,414 HCDR3 sequences from public databases. Sixteen SMZL (12%) showed stereotyped BCR; 7 of 86 (8%) SMZL sequences retrieved from public databases also belonged to stereotyped HCDR3 subsets. Three categories of subsets were identified: i) "SMZL-specific subsets" (n=5), composed only of 12 SMZL (9 HCV-from our series); ii) "Non-Hodgkin’s lymphoma-like subsets" (n=5), comprising 5 SMZL (4 from our series) clustering with other indolent lymphomas; iii) “CLL-like subsets” (n=6), comprising 6 SMZL (3 from our series) that belonged to known CLL subsets (n=4) or clustered with public CLL sequences. Immunoglobulin 3D modeling of 3 subsets revealed similarities in antigen binding regions not limited to HCDR3. Overall, data suggest that the pathogenesis of splenic marginal zone lymphoma may involve also HCV-unrelated epitopes or an antigenic trigger common to other indolent lymphomas.
Splenic marginal zone lymphoma (SMZL) is recognized by the WHO classification as an individual entity.1,2 Based on the association with HCV infection and autoimmunity,3 it is conceivable that antigen stimulation may play a role in SMZL.4,5 Though several studies investigated usage of immunoglobulin heavy chain variable (IGHV) genes in SMZL,5–9 and two SMZL cases with highly similar HCDR3 have been previously reported,10 at present no definitive immunogenetic clues for antigen stimulation have emerged.
In other B-cell malignancies, namely chronic lymphocytic leukemia (CLL), non-random combinations of specific IGHV-D-J genes lead to stereotyped complementarity determining region 3 (HCDR3) of the B-cell receptor (BCR) in a significant fraction of cases.11,12 Occurrence of stereotyped HCDR3 in CLL is regarded as an indication of antigen stimulation during disease development.13
The purpose of the present study was to investigate the occurrence and patterns of stereotyped HCDR3 in a large panel of SMZL.
Design and Methods
The study was based on a multi-institutional series of 133 SMZL cases. Diagnosis of SMZL was based on criteria proposed by the WHO classification1 and by Matutes et al.2 (with spleen histology in 40 patients and with bone marrow histology coupled with flow cytometry in 93). Patients provided informed consent in accordance with local institutional review board requirements (IRB) and the Declaration of Helsinki. The study was approved by the IRB of the Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Analysis of IGHV-D-J, IGKV-J and IGLV-J rearrangements in SMZL
Mononuclear cells were obtained from bone marrow (n=62 cases), peripheral blood (n=44), spleen tissue (n=25) or locoregional lymph node (n=2). IGHV-D-J, IGKV-J and IGLV-J rearrangements were amplified and directly sequenced from cDNA as previously reported.9,14 Sequences were aligned to ImMunoGeneTics sequence directory using the IMGT V-QUEST analysis software15 to obtain IGV, IGD, IGJ gene usage, mutational profile, functional status and CDR3 amino acid (AA) sequence.
Analysis of IGHV-D-J rearrangements and identification of SMZL with stereotyped HCDR3
Using the multiple sequence alignment software ClustalX (2.0),16 HCDR3 AA sequences from 133 SMZL were aligned to each other and to 4,414 sequences derived from B-cell neoplasia entities and retrieved from in-house and public databases (Online Supplementary Table S1), regardless of usage of different IGHV genes. Subsets of stereotyped HCDR3 were defined according to the criteria proposed by Messmer17 and Stamatopoulos.11 AA differences at the same HCDR3 position in cases within a subset were also evaluated (volume, hydropathy index, and chemical characteristics). Subsets not previously reported have been assigned a number preceded by N ("Novel”). A difference in HCDR3 length of greater than 3 AA was not allowed in the same cluster. Nomenclature of previously reported subsets was made according to Stamatopoulos11 and Murray.12 Subsets composed of 3 or more cases have been defined as “confirmed”.11 Subsets composed of 2 cases were defined as “provisional” and were characterized by identical IGHV/IGHD/IGHJ or IGHD/IGHJ genes, shared junctional residues and/or restricted light-chain CDR3.18
The PIGS web-server19 was used to model the immunoglobulins (Igs) for which both light and heavy chains were sequenced. In 3 cases (cases 3926, 4625 and PV3) in which no suitable template for the H3 region was found, we used the Modeller20 ab-initio loop modeling procedure to build 10 different H3 loop conformations for each Ig and then, among these, we selected the centroid. Surface potentials were derived using the APBS software21 with standard parameters. All pictures where generated using the PyMol software (http://www.pymol.org).
Analysis of clinical data
The χ test and Fisher’s exact test were used to compare groups. Overall survival (OS) and progression free survival (PFS) were defined according to current criteria.22 Survival analysis was performed by the Kaplan-Meier method, using Gehan–Wilcoxon statistics to test for significant associations. Cox’s analysis was used to build a multivariate model. Analyses were carried out using Stata SE 9 (StataCorp LP), Statistica 8 (StatSoft Inc.) and Microsoft Excel 2000.
Results and Discussion
The clinical features of the 133 SMZL are summarized in the Online Supplementary Table S2. Median age at diagnosis was 67 years (range 40–82). HCV serology was positive in 26 of 127 cases (20%). Five-year OS was 81% and 5-year PFS 46%.
Productive IGHV-D-J rearrangements were obtained from all 133 SMZL cases. Use of IGHV, IGHD, and IGHJ genes is reported in Table 1. The IGHV families most frequently used were IGHV3 (n=66, 50%), IGHV1 (n=40, 30%) and IGHV4 (n=23, 17%). The IGHV genes most frequently rearranged were IGHV1-2 (n=26, 20%), IGHV3-23 (n=24, 18%), IGHV4-34 (n=10, 8%), and IGHV1-69 (n=10, 8%), confirming a biased VH gene usage in SMZL as already suggested. Using the 98% identity cut-off value, 93 (70%) sequences were mutated and 40 (30%) sequences were unmutated (15 with 100% identity, 10 with 99–99.9%, 15 with 98–98.9%).
By means of HCDR3 clustering analysis, 16 of 133 (12%) SMZL investigated in this study met the minimal criteria to be included in subsets with stereotyped HCDR3 (Table 2 and Online Supplementary Table S3); 7 of 86 (8%) SMZL sequences retrieved from public databases also belonged to stereotyped HCDR3 subsets (Online Supplementary Table S3).
On the basis of disease representation within individual subsets, three major patterns of HCDR3 subsets were identified: i) "SMZL-specific subsets", that included only cases of SMZL; ii) "non-Hodgkin’s lymphoma (NHL)-like subsets", that included cases of both SMZL and NHL in the same subset; and iii) "CLL-like subsets", that included cases of both SMZL and CLL in the same subset (Table 2 and Online Supplementary Table S3).
The 5 SMZL-specific subsets were in all instances novel subsets (confirmed: N1, N2; provisional: N3, N4, N5). Nine HCV-negative SMZL cases from our cohort and 3 SMZL cases from public databases belonged to SMZL-specific subsets. The 5 NHL-like subsets (confirmed: N6, N7, N8; provisional: N9, N10) were composed of 5 SMZL cases (4 from this series) clustering with non-splenic MZL and extranodal indolent lymphomas. Four SMZL (2 from our series) clustered within known CLL subsets (subsets 1, 6, 9, 25) and two (one from our series) formed 2 novel provisional subsets (N11, N12).
Three-dimensional models of Igs were produced for 3 subsets (2 SMZL-specific: N1, N3; 1 NHL-like: N9), after obtaining light chain sequences (Online Supplementary Table S3). Details of the modeling are reported in the Figure 1 legend. In all cases, Igs belonging to the same stereotyped group displayed an overall similarity, both in sequence and structure, not limited to HCDR3. In particular, in subset N1, a large hydrophobic area has been found on loop H3 (Figure 1) that is likely to be involved in antigen recognition.
HCV serology was negative in SMZL belonging to SMZL-specific subsets and CLL-like subsets, whereas was positive in 2/3 SMZL belonging to NHL subsets (P=0.02; Online Supplementary Table S4). Median PFS was 1.7 years (SE 0.5, 95% CI 0.7–4.7) for stereotyped cases and 5.3 for non-stereotyped (SE 0.8, 95% CI 2.6–7.3) (P=0.06). Median PFS was 2.7 years (SE 0.45, 95% CI 1.2-ND) for unmutated cases and 4.7 for mutated cases (SE 0.48, 95% CI 2.6-ND) (P=0.06). By Cox’s regression analysis with mutational status and stereotyped HCDR3 as covariates, both had a significant effect on PFS (mutational status HR=1.8, P=0.04; cluster HR=2.1 P=0.02).
These data point to the occurrence of SMZL-specific, stereotyped HCDR3 sequences and Igs structures in SMZL. Occurrence of stereotyped HCDR3 in both HCV-negative and HCV-positive cases suggests that the potential role of antigens in SMZL pathogenesis is not restricted to HCV, but may involve also HCV-unrelated epitopes with a common BCR-binding signature. The role of antigen stimulation in SMZL is further reinforced by the observation that a fraction of SMZL share stereotyped HCDR3 with non-splenic MZL and with CLL, suggesting a potential common pathogenetic trigger in different indolent B-cell malignancies.
the authors wish to thank Prof. Andrea Mattevi for helpful discussion. The authors are also grateful to Cristiana Pascutto and Virginia Ferretti for statistical analysis. This publication is based on work partially supported by Ricerca Sanitaria Finalizzata 2008 and 2009, Regione Piemonte, Torino, Italy (to DC, DR and GG); Progetto Integrato Oncologia and Programma di Ricerca di Rilevante Interesse Nazionale (PRIN) 2008, Ministero della Salute, Rome, Italy (to GG); Progetto Giovani Ricercatori 2008 Ministero della Salute, Rome, Italy (to DR); Novara-Associazione Italiana contro le Leucemie, Linfomi e Mielomi (AIL) Onlus, Novara, Italy (to GG, DR); AIL, Venezia Section, Pramaggiore Group, Pramaggiore (VE), Italy (to VG); Associazione Italiana per la Ricerca contro il Cancro, Milan, Italy (to FF, ES, EC and VG); Ministero della Salute (Ricerca Finalizzata IRCCS., “Alleanza Contro il Cancro” and Rete Nazionale Bio-Informatica Oncologica/RN-BIO), Rome, Italy (to VG); Ricerca Scientifica Applicata, Regione Friuli-Venezia-Giulia, Trieste (“Linfonet” Project), Italy (to VG); Award No. KUK-I1-012-43, made by King Abdullah University of Science and Technology (KAUST) (to AT and PM); Oncosuisse grant OCS-02034-02-2007 (to FB); Fondazione per la Ricerca e la Cura sui Linfomi, Lugano, Switzerland (to FB).
- Authorship and Disclosures The information provided by the authors about contributions from persons listed as authors and in acknowledgments is available with the full text of this paper at www.haematologica.org.
- Financial and other disclosures provided by the authors using the ICMJE (www.icmje.org) Uniform Format for Disclosure of Competing Interests are also available at www.haematologica.org.
- The online version of this article has a Supplementary Appendix.
- Received March 25, 2010.
- Revision received April 28, 2010.
- Accepted May 17, 2010.
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