Identification of a 20-Gene Expression-Based Risk Score as a Predictor of Clinical Outcome in Chronic Lymphocytic Leukemia Patients

• Published in: BioMed research international Vol. 2014; no. 2014; pp. 1 - 10
• Main Authors: Bou Samra, Elias, Klein, Bernard, Commes, Thérèse, Moreaux, Jérôme
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Puplishing Corporation 01-01-2014; Hindawi Publishing Corporation; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Adaptor Proteins, Signal Transducing - biosynthesis; Cell adhesion & migration; Chemokines; Chronic lymphocytic leukemia; Clinical outcomes; Deoxyribonucleic acid; DNA; DNA repair; Gene expression; Gene Expression Regulation, Neoplastic; Genetic aspects; Humans; Immunology; Kinases; Leukemia; Leukemia, Lymphocytic, Chronic, B-Cell - genetics; Leukemia, Lymphocytic, Chronic, B-Cell - pathology; Life Sciences; Medical prognosis; Microarray Analysis; Multivariate analysis; Mutation; Neoplasm Proteins - biosynthesis; Nuclear Proteins - biosynthesis; Patient outcomes; Prognosis; Risk factors; Survival Analysis; T Cell Transcription Factor 1 - biosynthesis; Treatment Outcome; France; gene expression; chronic lymphocytic leukemia
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2014/423174

Despite the improvement in treatment options, chronic lymphocytic leukemia (CLL) remains an incurable disease and patients show a heterogeneous clinical course requiring therapy for many of them. In the current work, we have built a 20-gene expression (GE)-based risk score predictive for patients overall survival and improving risk classification using microarray gene expression data. GE-based risk score allowed identifying a high-risk group associated with a significant shorter overall survival (OS) and time to treatment (TTT) P≤.01, comprising 19.6% and 13.6% of the patients in two independent cohorts. GE-based risk score, and NRIP1 and TCF7 gene expression remained independent prognostic factors using multivariate Cox analyses and combination of GE-based risk score together with NRIP1 and TCF7 gene expression enabled the identification of three clinically distinct groups of CLL patients. Therefore, this GE-based risk score represents a powerful tool for risk stratification and outcome prediction of CLL patients and could thus be used to guide clinical and therapeutic decisions prospectively.