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. 2024 Jan;26(1):e3595.
doi: 10.1002/jgm.3595. Epub 2023 Sep 20.

Integrative analysis of an endoplasmic reticulum stress-related signature in multiple myeloma

Chengyu Wu  1 , Mei Liu  2 , Jia Liu  1 , Mingyuan Jia  1 , Xinyi Zeng  3 , Ze Fu  1 , Yanlai Geng  2 , Ziqi He  1 , Xian Zhang  4 , Hua Yan  1   4
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Integrative analysis of an endoplasmic reticulum stress-related signature in multiple myeloma

Chengyu Wu et al. J Gene Med. 2024 Jan.

Abstract

Background: Multiple myeloma (MM) is a malignancy in which plasma cells proliferate abnormally, and it remains incurable. The cells are characterized by high levels of endoplasmic reticulum stress (ERS) and depend on the ERS response for survival. Thus, we aim to find an ERS-related signature of MM and assess its diagnostic value.

Methods: We downloaded three datasets of MM from the Gene Expression Omnibus database. After identifying ERS-related differentially expressed genes (ERDEGs), we analyzed them using Gene Ontology enrichment analysis. A protein-protein interaction network, a transcription factor-mRNA network, a miRNA-mRNA network and a drug-mRNA network were constructed to explore the ERDEGs. The clinical application of these genes was identified by calculating the infiltration of immune cells and using receiver operating characteistic analyses. Finally, qPCR was performed to further confirm the roles of ERDEGs.

Results: We obtained nine ERDEGs of MM. Gene Ontology enrichment indicated that the ERDEGs played a role in the endoplasmic reticulum membrane. Additionally, the protein-protein interaction network showed interaction among the ERDEGs, and there were 20 proteins, 107 transcription factors, 42 drugs or molecular compounds and 51 miRNAs which were likely to interact with the nine genes. In addition, immune cell infiltration analyses showed that there was a strong correlation between the nine genes and immune cells, and these potential biomarkers exhibited good diagnostic values. Finally, the expression of ERDEGs in MM cells was different from that in healthy donor samples.

Conclusion: The nine ERS-related genes, CR2, DHCR7, DNAJC3, KDELR2, LPL, OSBPL3, PINK1, VCAM1 and XBP1 are potential biomarkers of MM, and this supports further clinical development of the diagnosis and treatment of MM.

Keywords: PPI network; ROC curve; biomarker; endoplasmic reticulum stress; immune infiltration; regulatory network.

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