Abstract
Introduction: The aim of this study was to develop a prognostic model for chronic lymphocytic leukemia (CLL). Methods: GEO2R was used to retrieve the gene expression data of CLL and normal B cells from the Gene Expression Omnibus (GEO; GSE22529 and GSE50006 datasets) database. Practical Extraction and Report Language was used to extract the gene expression and overall survival (OS) data of CLL patients from the Chronic Lymphocytic Leukemia – ES (CLLE-ES) project in the International Cancer Genome Consortium (ICGC) database. Cox regression with Lasso was used to create and validate a prognostic model for CLL. Results: A total of 267 genes exhibited differential expression between CLL and normal B cells. Cox univariate analysis identified 14 DEGs that correlated with OS. Lasso multivariate evaluation demonstrated that AKAP12 and IGFBP4 are independent prognostic factors for CLL. Kaplan-Meier survival analysis revealed a significant association between the estimated risk score and survival. The area under the receiver operating characteristic curve was calculated to be 0.97, indicating high predictive accuracy. In addition, high AKAP12 and IGFBP4 risk scores were associated with the high incidence of trisomy 12q. Conclusion: Taken together, AKAP12 and IGFBP4 are independent prognostic factors for CLL.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
