Prognostic value assessment and in vitro validation of mitochondria-ferroptosis-related genes in multiple myeloma
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Published on: March 15, 2024
Jing Wu1, Chen Li2, Jiayou Zhang1
1Department of Hematology, The Second Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital, Chengdu, 610051, China.
Abstract:
Multiple myeloma (MM) is a malignant plasma cell tumor. Mitochondria-related genes (MRGs) are significant inducers of ferroptosis. However, research on the involvement of mitochondria-ferroptosis-related genes (MFRGs) in the MM is relatively scarce, and further identification of key genes associated with MFRGs in MM treatment is needed. In this study, transcriptomic data and related genes were initially downloaded from public databases and literature. Subsequently, candidate genes were obtained by intersecting the differential expression genes (DEGs) from MM and control groups, and MFRGs. Through regression analyses, clinically relevant genomic signatures were delineated, culminating in the development of a predictive algorithm. An independent prognostic analysis was conducted, followed by the creation of a nomogram. Subsequently, these prognostic genes were studied from various aspects. Finally, the transcriptional abundance of predictive biomarkers was experimentally validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR). The intersection of DEGs and MFRGs yielded 15 candidate genes. Then, GPR15, NLRP7, ZNF208, PRDM13, and CRIM1 were identified as prognostic genes. The prognostic model constructed using these prognostic genes was confirmed to be robust. The 2 independent prognostic factors (risk score and age) were determined, and the constructed nomogram provided an excellent predictive model. Then, risk score and activated dendritic cells were found to be significantly negatively correlated (cor = -0.43, p < 0.05). Additionally, GPR15 was positively associated with M2 macrophages (cor = 0.34, p < 0.05), while NLRP7 and PRDM13 were negatively associated with activated dendritic cells (cor = -0.34, p < 0.05; cor = -0.40, p < 0.05). There were 3 significantly different immune cells, 31 significantly immune checkpoint genes, and 11 significantly different immune checkpoints (p < 0.05). ZNF208, PRDM13, and CPIM1 were all mainly enriched in ribosome-related pathways. Finally, 86 potential drugs for the treatment of MM were discovered, such as shikonin. RT-qPCR results showed that NLRP7 and PRDM13 were significantly upregulated in MM group, while GPR15 and CRIM1 were significantly downregulated in MM group (p < 0.05). In this study, 5 MFRGs were identified as prognostic genes (GPR15, NLRP7, ZNF208, PRDM13, and CRIM1) for MM, which provide reference significance for the prognosis of MM.
Insights
This study identifies five key mitochondria-ferroptosis-related genes (MFRGs) as crucial prognostic markers for multiple myeloma (MM). These MFRGs offer new insights for predicting MM patient outcomes and potential therapeutic targets.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Multiple myeloma (MM) is a plasma cell malignancy.
- Mitochondria-related genes (MRGs) influence ferroptosis.
- The role of mitochondria-ferroptosis-related genes (MFRGs) in MM is under-researched.
Purpose of the Study:
- To identify key MFRGs associated with MM prognosis.
- To develop a predictive model for MM treatment using MFRGs.
- To validate the expression of identified prognostic MFRGs.
Main Methods:
- Transcriptomic data from public databases were analyzed.
- Differential expression analysis and MFRG intersection identified candidate genes.
- Regression analysis, prognostic analysis, and nomogram construction were performed.
- RT-qPCR validated gene expression levels.
Main Results:
- Five MFRGs (GPR15, NLRP7, ZNF208, PRDM13, CRIM1) were identified as prognostic genes for MM.
- A robust predictive model and nomogram incorporating risk score and age were developed.
- Significant correlations were found between risk score, MFRGs, and immune cells.
- RT-qPCR confirmed differential expression of NLRP7, PRDM13, GPR15, and CRIM1 in MM.
Conclusions:
- The identified five MFRGs serve as significant prognostic biomarkers for multiple myeloma.
- The developed predictive model and nomogram offer valuable tools for MM prognosis.
- These findings provide a basis for exploring MFRGs in MM treatment strategies.

