TY - JOUR
T1 - ARResT/AssignSubsets
T2 - A novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy
AU - Bystry, Vojtech
AU - Agathangelidis, Andreas
AU - Bikos, Vasilis
AU - Sutton, Lesley Ann
AU - Baliakas, Panagiotis
AU - Hadzidimitriou, Anastasia
AU - Stamatopoulos, Kostas
AU - Darzentas, Nikos
PY - 2015/6/18
Y1 - 2015/6/18
N2 - 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 ∼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.
AB - 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 ∼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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U2 - 10.1093/bioinformatics/btv456
DO - 10.1093/bioinformatics/btv456
M3 - Article
C2 - 26249808
AN - SCOPUS:84950249761
VL - 31
SP - 3844
EP - 3846
JO - Bioinformatics
JF - Bioinformatics
SN - 1367-4803
IS - 23
ER -