The B cell receptor immunoglobulin (Ig) gene repertoires of marginal zone (MZ) lymphoproliferations were analyzed in order to obtain insight into their ontogenetic relationships. Our cohort included cases with MZ lymphomas (n = 488), i.e. splenic (SMZL), nodal (NMZL) and extranodal (ENMZL), as well as provisional entities (n = 76), according to the WHO classification. The most striking Ig gene repertoire skewing was observed in SMZL. However, restrictions were also identified in all other MZ lymphomas studied, particularly ENMZL, with significantly different Ig gene distributions depending on the primary site of involvement. Cross-entity comparisons of the MZ Ig sequence dataset with a large dataset of Ig sequences (MZ-related or not; n = 65 837) revealed four major clusters of cases sharing homologous ('public') heavy variable complementarity-determining region 3. These clusters included rearrangements from SMZL, ENMZL (gastric, salivary gland, ocular adnexa), chronic lymphocytic leukemia, but also rheumatoid factors and non-malignant splenic MZ cells. In conclusion, different MZ lymphomas display biased immunogenetic signatures indicating distinct antigen exposure histories. The existence of rare public stereotypes raises the intriguing possibility that common, pathogen-triggered, immune-mediated mechanisms may result in diverse B lymphoproliferations due to targeting versatile progenitor B cells and/or operating in particular microenvironments. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
- MeSH
- genová přestavba B-lymfocytů genetika MeSH
- geny pro imunoglobuliny genetika MeSH
- geny pro těžké řetězce imunoglobulinů genetika MeSH
- hypervariabilní oblasti genetika MeSH
- lidé MeSH
- lymfom z B-buněk marginální zóny genetika MeSH
- mutace genetika MeSH
- nádorové mikroprostředí MeSH
- receptory antigenů B-buněk genetika MeSH
- variabilní oblast imunoglobulinu genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. RESULTS: Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. CONCLUSIONS: The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.
