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ARResT/AssignSubsets : a novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy
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- Bystry, Vojtech (author)
- Masaryk Univ, CEITEC Cent European Inst Technol, Brno, Czech Republic.
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- Agathangelidis, Andreas (author)
- IRCCS San Raffaele Sci Inst, Div Mol Oncol, Milan, Italy.;IRCCS San Raffaele Sci Inst, Dept Oncohematol, Milan, Italy.;Univ Vita Salute San Raffaele, Milan, Italy.
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- Bikos, Vasilis (author)
- Masaryk Univ, CEITEC Cent European Inst Technol, Brno, Czech Republic.
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- Masaryk Univ, CEITEC Cent European Inst Technol, Brno, Czech Republic IRCCS San Raffaele Sci Inst, Div Mol Oncol, Milan, Italy.;IRCCS San Raffaele Sci Inst, Dept Oncohematol, Milan, Italy.;Univ Vita Salute San Raffaele, Milan, Italy. (creator_code:org_t)
- 2015-08-06
- 2015
- English.
- In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 31:23, s. 3844-3846
- Journal article (peer-reviewed)
Abstract
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- 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.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinsk bioteknologi -- Medicinsk bioteknologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Medical Biotechnology -- Medical Biotechnology (hsv//eng)
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