Publication details

ARResT/AssignSubsets: a novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy

Authors

BYSTRÝ Vojtěch AGATHANGELIDIS Andreas BIKOS Vasileios SUTTON Lesley Ann BALIAKAS Panagiotis HADZIDIMITRIOU Anastasia STAMATOPOULOS Kostas DARZENTAS Nikos

Year of publication 2015
Type Article in Periodical
Magazine / Source Bioinformatics
MU Faculty or unit

Central European Institute of Technology

Citation
Web http://bioinformatics.oxfordjournals.org/content/31/23/3844
Doi http://dx.doi.org/10.1093/bioinformatics/btv456
Field Biochemistry
Keywords PATHOGENETIC IMPLICATIONS; IMMUNOGLOBULIN; GENES
Description Motivation: An ever-increasing body of evidence supports the importance of B cell receptor immunoglobulin (BcR IG) sequence restriction, alias stereotypy, in chronic lymphocytic leukemia (CLL). This phenomenon accounts for similar to 30% of studied cases, one in eight of which belong to major subsets, and extends beyond restricted sequence patterns to shared biologic and clinical characteristics and, generally, outcome. Thus, the robust assignment of new cases to major CLL subsets is a critical, and yet unmet, requirement. Results: We introduce a novel application, ARResT/AssignSubsets, which enables the robust assignment of BcR IG sequences from CLL patients to major stereotyped subsets. ARResT/AssignSubsets uniquely combines expert immunogenetic sequence annotation from IMGT/V-QUEST with curation to safeguard quality, statistical modeling of sequence features from more than 7500 CLL patients, and results from multiple perspectives to allow for both objective and subjective assessment. We validated our approach on the learning set, and evaluated its real-world applicability on a new representative dataset comprising 459 sequences from a single institution.
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