Disease-biased and shared characteristics of the immunoglobulin gene repertoires in marginal zone B cell lymphoproliferations.
van den Brand, Michiel
Piris, Miguel Angel
Journal of Pathology
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Xochelli, A., Bikos, V., Polychronidou, E., Galigalidou, C., Agathangelidis, A., Charlotte, F., Moschonas, P., et al. (2018). Disease-biased and shared characteristics of the immunoglobulin gene repertoires in marginal zone B cell lymphoproliferations.. Journal of Pathology https://doi.org/10.1002/path.5209
The B cell receptor immunoglobulin (BcR 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 World Health Organization 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 spleen 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.
Marginal zone lymphoma, antigen, immunoglobulin gene, ontogeny
This work was supported in part by H2020 “AEGLE, An analytics framework for integrated and personalized healthcare services in Europe”, by the European Union (EU); H2020 No. 692298 project “MEDGENET, Medical Genomics and Epigenomics Network” by the EU; grant AZV 15-30015A from the Ministry of Health of the Czech Republic, and the project CEITEC2020 LQ1601 from the Ministry of Education, Youth, and Sports of the Czech Republic; Bloodwise Research Grant (15019); the Swedish Cancer Society, the Swedish Research Council, the Knut and Alice Wallenberg Foundation, Karolinska Institutet, Stockholm, the Lion’s Cancer Research Foundation, Uppsala, the Marcus Borgström Foundation and Selander’s Foundation, Uppsala.
External DOI: https://doi.org/10.1002/path.5209
This record's URL: https://www.repository.cam.ac.uk/handle/1810/287557