Title:Machine Learning Algorithms Identify Target Genes and the Molecular
Mechanism of Matrine against Diffuse Large B-cell Lymphoma
Volume: 20
Issue: 6
Author(s): Yidong Zhu, Zhongping Ning, Ximing Li*Zhikang Lin*
Affiliation:
- Department of Cardiology, Shanghai Pudong New District Zhoupu Hospital, Shanghai University
of Medicine & Health Sciences, Shanghai, 201318, China
- Longhua Hospital, Shanghai University of Traditional
Chinese Medicine, Shanghai, 200032, China
Keywords:
Matrine, diffuse large B-cell lymphoma, machine learning, targeted therapy, PI3K-Akt, molecular mechanism.
Abstract:
Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type
of non-Hodgkin's lymphoma worldwide. Novel treatment strategies are still needed for this
disease.
Objective: The present study aimed to systematically explore the potential targets and molecular
mechanisms of matrine in the treatment of DLBCL.
Methods: Potential matrine targets were collected from multiple platforms. Microarray data and
clinical characteristics of DLBCL were downloaded from publicly available database. Differential
expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to
identify the hub genes of DLBCL using R software. Then, the shared target genes between
matrine and DLBCL were identified as the potential targets of matrine against DLBCL. The least
absolute shrinkage and selection operator (LASSO) algorithm was used to determine the final
core target genes, which were further verified by molecular docking simulation and receiver operating
characteristic (ROC) curve analysis. Functional analysis was also performed to elucidate the
potential mechanisms.
Results: A total of 222 matrine target genes and 1269 DLBCL hub genes were obtained through
multiple databases and machine learning algorithms. From the nine shared target genes of matrine
and DLBCL, five final core target genes, including CTSL, NR1H2, PDPK1, MDM2, and JAK3,
were identified. Molecular docking showed that the binding of matrine to the core genes was stable.
ROC curves also suggested close associations between the core genes and DLBCL. Additionally,
functional analysis showed that the therapeutic effect of matrine against DLBCL may be
related to the PI3K-Akt signaling pathway.
Conclusion: Matrine may target five genes and the PI3K-Akt signaling pathway in DLBCL treatment.