Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Jan 24, 2024; 15(1): 115-129
Published online Jan 24, 2024. doi: 10.5306/wjco.v15.i1.115
Gene signatures to therapeutics: Assessing the potential of ivermectin against t(4;14) multiple myeloma
Yang Song, Hao-Jun Zhang, Xia Song, Jie Geng, Hong-Yi Li, Li-Zhong Zhang, Bo Yang, Xue-Chun Lu
Yang Song, Hong-Yi Li, School of Basic Medicine, Medical School of Chinese PLA, Beijing 100853, China
Hao-Jun Zhang, Xia Song, Jie Geng, Li-Zhong Zhang, School of Basic Medicine, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
Bo Yang, Xue-Chun Lu, Department of Hematology, The Second Medical Centre, Chinese PLA General Hospital, Beijing 100853, China
Author contributions: Song Y and Lu XC conceived and designed the experiments. Zhang HJ, Geng J, and Song Y conducted the experiments and drafted the manuscript; Zhong LZ and Song X contributed to the techniques used and commented on the manuscript; Li HY performed the data analysis; Yang B and Lu XC assisted with revising the manuscript; All the authors reviewed the results and approved the final version of the manuscript.
Supported by the National Key Research and Development Program of China, No. 2021YFC2701704; the National Clinical Medical Research Center for Geriatric Diseases, "Multicenter RCT" Research Project, No. NCRCG-PLAGH-20230010; and the Military Logistics Independent Research Project, No. 2022HQZZ06.
Institutional review board statement: This study does not involve research on humans/animals and does not include the initial version formally approved by the Institutional Review Board in the official language of the authors' country.
Informed consent statement: This study does not involve clinical research and does not include the initial version of the informed consent form signed by all subjects and investigators.
Conflict-of-interest statement: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Xue-Chun Lu, PhD, Chief Doctor, Professor, Research Scientist, Department of Hematology, The Second Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing 100853, China.
Received: November 20, 2023
Peer-review started: November 20, 2023
First decision: December 5, 2023
Revised: December 13, 2023
Accepted: January 2, 2024
Article in press: January 2, 2024
Published online: January 24, 2024

Multiple myeloma (MM) is a terminal differentiated B-cell tumor disease characterized by clonal proliferation of malignant plasma cells and excessive levels of monoclonal immunoglobulins in the bone marrow. The translocation, (t)(4;14), results in high-risk MM with limited treatment alternatives. Thus, there is an urgent need for identification and validation of potential treatments for this MM subtype. Microarray data and sequencing information from public databases could offer opportunities for the discovery of new diagnostic or therapeutic targets.


To elucidate the molecular basis and search for potential effective drugs of t(4;14) MM subtype by employing a comprehensive approach.


The transcriptional signature of t(4;14) MM was sourced from the Gene Expression Omnibus. Two datasets, GSE16558 and GSE116294, which included 17 and 15 t(4;14) MM bone marrow samples, and five and four normal bone marrow samples, respectively. After the differentially expressed genes were identified, the Cytohubba tool was used to screen for hub genes. Then, the hub genes were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Using the STRING database and Cytoscape, protein–protein interaction networks and core targets were identified. Potential small-molecule drugs were identified and validated using the Connectivity Map database and molecular docking analysis, respectively.


In this study, a total of 258 differentially expressed genes with enriched functions in cancer pathways, namely cytokine receptor interactions, nuclear factor (NF)-κB signaling pathway, lipid metabolism, atherosclerosis, and Hippo signaling pathway, were identified. Ten hub genes (cd45, vcam1, ccl3, cd56, app, cd48, btk, ccr2, cybb, and cxcl12) were identified. Nine drugs, including ivermectin, deforolimus, and isoliquiritigenin, were predicted by the Connectivity Map database to have potential therapeutic effects on t (4;14) MM. In molecular docking, ivermectin showed strong binding affinity to all 10 identified targets, especially cd45 and cybb. Ivermectin inhibited t(4;14) MM cell growth via the NF-κB pathway and induced MM cell apoptosis in vitro. Furthermore, ivermectin increased reactive oxygen species accumulation and altered the mitochondrial membrane potential in t(4;14) MM cells.


Collectively, the findings offer valuable molecular insights for biomarker validation and potential drug development in t(4;14) MM diagnosis and treatment, with ivermectin emerging as a potential therapeutic alternative.

Keywords: Multiple myeloma, Functional enrichment analysis, Molecular docking simulation, Gene expression profiling, Therapeutic target, Ivermectin

Core Tip: Multiple myeloma is a hematological malignancy with a significant impact on public health, and the t(4;14) subtype is particularly aggressive and resistant to existing treatments. Our study addresses the urgent need for new therapeutic approaches by employing a comprehensive approach that includes bioinformatics analysis, molecular docking, and experimental validation. We identified ten key genes associated with t(4;14) multiple myeloma (MM), shedding light on the molecular basis of this subtype. We explored the potential of ivermectin to assess whether it may be “repurposed” as a therapeutic agent for t(4;14) MM. Our findings indicate that ivermectin not only inhibits MM cell growth but also induces apoptosis via the nuclear factor-κB signaling pathway.