Epigenetic profiling and response to CD19 chimeric antigen receptor (CAR) T-cell therapy in B-cell malignancies
收藏NIAID Data Ecosystem2026-03-12 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE179414
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Chimeric antigen receptor (CAR) T-cells directed against CD19 (CART19) are effective in relapsed/refractory (R/R) B-cell malignancies. Not all patients show treatment efficacy, but little is known about the molecular factors predicting clinical outcome of CART19 therapy. Our objective was to determine the effect of epigenetic changes in CART19 cells on the clinical course of B-cell malignancy patients treated with adoptive therapy. We report a case series of B-cell malignancy patients (68 males (M) and 46 females (F); median age of 24 years (range 3-70 years)), comprising 77 acute lymphoblastic leukemia (ALL) cases and 37 non-Hodgkin lymphoma (NHL) cases, who were treated with CART19 cells. Using a DNA methylation microarray, we determined the epigenomic changes that occur in the patient T-cells upon transduction of the CAR vector. We identified 984 genomic sites with differential DNA methylation between CAR-untransduced (UT) and CAR-transduced (TD) T-cells before infusion into the patient. 18 of these distinct epigenetic loci were significantly associated with complete response (CR). Using the sites linked to CR, the EPICART signature was established, which was associated with enhanced overall survival (OS). The DNA methylation status of the CART19 transduced T-cells from 114 patients was established using the Infinium MethylationEPIC Array following the manufacturer’s instructions for the automated processing of arrays with a liquid handler (Illumina Infinium HD Methylation Assay Experienced User Card, Automated Protocol 15019521 v01). Raw signal intensity data were initially QC’d and preprocessed from resulting idat files using minfi Bioconductor package (v1.36.0). EPICART DNA methylation signature was obtained using a trained supervised classification model based on ridge regularized logistic regression. The classification model was optimized by tuning parameters with 10-fold cross-validation repeated three times using caret CRAN package (v6.0-86). All analyses were performed under R statistical environment (v4.0.3). >>>Submitter states: IDAT files were not being provided due to privacy issues (idat files include SNPs that can be used to identify patients)<<<
创建时间:
2021-10-05



