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

Bystry V, Agathangelidis A, Bikos V, Sutton LA, Baliakas P, Hadzidimitriou A, Stamatopoulos K, Darzentas N, European Research Initiative on CLL

Bioinformatics 31 (23) 3844-3846 [2015-12-01; online 2015-08-06]

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 ∼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. 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. ARResT/AssignSubsets is freely available on the web at Supplementary data are available at Bioinformatics online.

Affiliated researcher

PubMed 26249808

DOI 10.1093/bioinformatics/btv456

Crossref 10.1093/bioinformatics/btv456

pii: btv456

Publications 9.5.0