Literature DB >> 33553159

Multi-Omics Analysis of Acute Lymphoblastic Leukemia Identified the Methylation and Expression Differences Between BCP-ALL and T-ALL.

Jin-Fan Li1, Xiao-Jing Ma1, Lin-Lin Ying1, Ying-Hui Tong2, Xue-Ping Xiang1.   

Abstract

Acute lymphoblastic leukemia (ALL) as a common cancer is a heterogeneous disease which is mainly divided into BCP-ALL and T-ALL, accounting for 80-85% and 15-20%, respectively. There are many differences between BCP-ALL and T-ALL, including prognosis, treatment, drug screening, gene research and so on. In this study, starting with methylation and gene expression data, we analyzed the molecular differences between BCP-ALL and T-ALL and identified the multi-omics signatures using Boruta and Monte Carlo feature selection methods. There were 7 expression signature genes (CD3D, VPREB3, HLA-DRA, PAX5, BLNK, GALNT6, SLC4A8) and 168 methylation sites corresponding to 175 methylation signature genes. The overall accuracy, accuracy of BCP-ALL, accuracy of T-ALL of the RIPPER (Repeated Incremental Pruning to Produce Error Reduction) classifier using these signatures evaluated with 10-fold cross validation repeated 3 times were 0.973, 0.990, and 0.933, respectively. Two overlapped genes between 175 methylation signature genes and 7 expression signature genes were CD3D and VPREB3. The network analysis of the methylation and expression signature genes suggested that their common gene, CD3D, was not only different on both methylation and expression levels, but also played a key regulatory role as hub on the network. Our results provided insights of understanding the underlying molecular mechanisms of ALL and facilitated more precision diagnosis and treatment of ALL.
Copyright © 2021 Li, Ma, Ying, Tong and Xiang.

Entities:  

Keywords:  Boruta; Monte Carlo feature selection; acute lymphoblastic leukemia; expression; hub; methylation; multi-omics; network analysis

Year:  2021        PMID: 33553159      PMCID: PMC7859262          DOI: 10.3389/fcell.2020.622393

Source DB:  PubMed          Journal:  Front Cell Dev Biol        ISSN: 2296-634X


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