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Integrative analysis of an endoplasmic reticulum stress-related signature in multiple myeloma
Chengyu Wu1, Mei Liu2, Jia Liu1
1Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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.
Insights
We identified nine endoplasmic reticulum stress-related genes (ERS-RG) as potential diagnostic biomarkers for multiple myeloma (MM). These ERS-RG signatures may aid in the clinical development of new MM diagnostic and therapeutic strategies.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Multiple myeloma (MM) is an incurable plasma cell malignancy.
- MM cells exhibit high endoplasmic reticulum stress (ERS) and rely on its response for survival.
- Identifying ERS-related molecular signatures is crucial for MM diagnosis and treatment.
Purpose of the Study:
- To identify an ERS-related gene signature for multiple myeloma (MM).
- To evaluate the diagnostic value of the identified ERS-related genes in MM.
- To explore potential therapeutic targets and molecular interactions associated with ERS in MM.
Main Methods:
- Downloaded and analyzed three MM datasets from the Gene Expression Omnibus database.
- Identified ERS-related differentially expressed genes (ERDEGs) and performed Gene Ontology enrichment analysis.
- Constructed protein-protein interaction, transcription factor-mRNA, miRNA-mRNA, and drug-mRNA networks.
- Assessed immune cell infiltration and diagnostic value using receiver operating characteristic analyses.
- Validated ERDEG expression using quantitative polymerase chain reaction (qPCR).
Main Results:
- Identified a signature of nine ERDEGs in MM.
- ERDEGs are implicated in endoplasmic reticulum membrane functions.
- Established interaction networks revealing potential molecular partners and drug targets for the ERDEGs.
- Demonstrated significant correlations between ERDEGs and immune cell infiltration.
- Confirmed good diagnostic values for these potential MM biomarkers.
- Observed differential expression of ERDEGs in MM cells compared to healthy donors.
Conclusions:
- The nine identified ERS-related genes (CR2, DHCR7, DNAJC3, KDELR2, LPL, OSBPL3, PINK1, VCAM1, XBP1) are potential biomarkers for MM.
- This gene signature holds promise for advancing the clinical diagnosis and treatment of multiple myeloma.
- Further research into these ERDEGs could uncover novel therapeutic strategies for MM.
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