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.

Highlights

  • Acute lymphoblastic leukemia (ALL) as a common cancer is a heterogeneous disease that originates from lymphocyte progenitor cells of B-cells or T-cells

  • According to the World Health Organization (WHO) classification, ALL can be divided into B-cell ALL (B-ALL) and T-cell ALL (T-ALL)

  • The Boruta method can find out the relevant features and significantly reduce the number of features based on ensemble learning of random forest classifiers

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Summary

Introduction

Acute lymphoblastic leukemia (ALL) as a common cancer is a heterogeneous disease that originates from lymphocyte progenitor cells of B-cells or T-cells. The incidence of ALL is much lower, accounting for only 0.2% of all cancers. B-cell precursor ALL (BCP-ALL) is one of the B-ALL (Herold et al, 2014; Jones et al, 2016). In children’s ALL, it is mainly divided into BCP-ALL and T-ALL, accounting for 80–85% and 15–20%, respectively (Graux, 2011). These different subtypes are characterized by structural chromosomal rearrangements and repeated copy number alterations, which with great clinical significance (Goldberg et al, 2003)

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