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http://purl.uniprot.org/citations/26318878http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttp://purl.uniprot.org/core/Journal_Citation
http://purl.uniprot.org/citations/26318878http://www.w3.org/2000/01/rdf-schema#comment"Chronic lymphocytic leukemia (CLL) is a clonal disease of B lymphocytes manifesting as an absolute lymphocytosis in the blood. However, not all lymphocytoses are leukemic. In addition, first-degree relatives of CLL patients have an ~15 % chance of developing a precursor condition to CLL termed monoclonal B cell lymphocytosis (MBL), and distinguishing CLL and MBL B lymphocytes from normal B cell expansions can be a challenge. Therefore, we selected FMOD, CKAP4, PIK3C2B, LEF1, PFTK1, BCL-2, and GPM6a from a set of genes significantly differentially expressed in microarray analyses that compared CLL cells with normal B lymphocytes and used these to determine whether we could discriminate CLL and MBL cells from B cells of healthy controls. Analysis with receiver operating characteristics and Bayesian relevance determination demonstrated good concordance with all panel genes. Using a random forest classifier, the seven-gene panel reliably distinguished normal polyclonal B cell populations from expression patterns occurring in pre-CLL and CLL B cell populations with an error rate of 2 %. Using Bayesian learning, the expression levels of only two genes, FMOD and PIK3C2B, correctly distinguished 100 % of CLL and MBL cases from normal polyclonal and mono/oligoclonal B lymphocytes. Thus, this study sets forth effective computational approaches that distinguish MBL/CLL from normal B lymphocytes. The findings also support the concept that MBL is a CLL precursor."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.org/dc/terms/identifier"doi:10.1007/s12026-015-8688-3"xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Li W."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Paul S."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Moreno C."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Kolitz J.E."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"McCarthy B.A."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Rai K.R."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Wang X.P."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Chiorazzi N."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Lesser M."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Yan X.J."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Ferrarini M."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Bennett F."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Allen S.L."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Boyle E."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Tipping M."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Rawstron A.C."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Cutrona G."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Messmer B.T."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Yancopoulos S."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/author"Catera R."xsd:string
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/date"2015"xsd:gYear
http://purl.uniprot.org/citations/26318878http://purl.uniprot.org/core/name"Immunol Res"xsd:string