2022
DOI: 10.3389/fonc.2022.976262
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Identification of methylation signatures associated with CAR T cell in B-cell acute lymphoblastic leukemia and non-hodgkin’s lymphoma

Abstract: CD19-targeted CAR T cell immunotherapy has exceptional efficacy for the treatment of B-cell malignancies. B-cell acute lymphocytic leukemia and non-Hodgkin’s lymphoma are two common B-cell malignancies with high recurrence rate and are refractory to cure. Although CAR T-cell immunotherapy overcomes the limitations of conventional treatments for such malignancies, failure of treatment and tumor recurrence remain common. In this study, we searched for important methylation signatures to differentiate CAR-transdu… Show more

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Cited by 4 publications
(3 citation statements)
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“…Consequently, Song et al demonstrated the potential role of Serpinb6 as a contributor to the regular functioning of CAR-T cells. However, additional research is necessary to validate this concept [ 43 ]. Among the other Serpins studied in the literature, Serpinb3 showed a suppressor of lysosomal-mediated cell death in glioblastoma cancer stem cells.…”
Section: Discussionmentioning
confidence: 99%
“…Consequently, Song et al demonstrated the potential role of Serpinb6 as a contributor to the regular functioning of CAR-T cells. However, additional research is necessary to validate this concept [ 43 ]. Among the other Serpins studied in the literature, Serpinb3 showed a suppressor of lysosomal-mediated cell death in glioblastoma cancer stem cells.…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, we can state that it can be a better approach to adopt for finding relevant methylation signatures and sample classification rules created by ML classifiers. Some of its limitations include the stringent selection criteria for features, leading to the exclusion of relevant features [160] , [161] , [162] . A comprehensive overview of all the reviewed articles unveils the classification models using DMRs with a clear tabulated analysis input, the algorithm followed for model formation, and the output of the study is given in Table 2 .…”
Section: Dna Methylation Microarray Data Analysismentioning
confidence: 99%
“…Even though post‐infusion CAR T cells were left unanalysed, pre‐infusion inspections of these sites can act as a predictive marker to foretell treatment response or potential side effects in advance in other clinical settings. The raw data from the methylation profile of such experiments are also useful for mining in machine learning‐based algorithms to discover the correlation between specific gene methylations and CAR T cell functions [63]. Besides T cell exhaustion, the presence of long‐lived memory T cells that can differentiate into effector cells upon tumour cell reappearance is key for a long‐term, relapse‐free treatment.…”
Section: Epigenomicsmentioning
confidence: 99%