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Analysis of the Potential Link Between Dermatomyositis and Cancer
Jianwei Guo1,2, Tianyi Lei1,3, Xiang Yu1,3
1Research Center of Hyperuricemia and Gout, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Background:
Dermatomyositis (DM) is an inflammatory muscle disease that increases the risk of cancer, although the precise connection is not fully understood. The aim of this study was to investigate the mechanisms linking DM to cancer and identify potential therapeutic targets.
Methods:
We conducted differential gene expression analysis on the GSE128470 dataset and employed WGCNA to pinpoint key genes related to DM. Central genes were identified with the LASSO and SVM-RFE methods. The expression levels and diagnostic relevance of these genes were confirmed via the GSE1551 dataset. Immune cell infiltration was analyzed in relation to central genes, and RT‒qPCR was utilized to evaluate the expression of key genes across various cancers.
Results:
In total, differentially expressed genes (DEGs), involved mainly in innate immunity, cytokine responses, and autoimmune diseases, were identified. In the WGCNA, 399 significant genes related to DM were identified, with central genes including MIF, C1QA, and CDKN1A. Immune infiltration analysis revealed diverse immune cell populations in DM patients, with significant correlations between central genes and these immune cells. MIF levels were notably elevated in various tumors and correlated with the prognosis of specific cancers. Furthermore, MIF was negatively associated with most immune cells but positively correlated with CD4+ Th1 cells, NKT cells, and MDSCs. Factors such as immune regulatory elements, TMB, and MSI indicated that MIF may affect immunotherapy outcomes. The increased expression of MIF mRNA was confirmed via RT‒qPCR.
Conclusion:
The findings demonstrate that MIF, C1QA, and CDKN1A are differentially expressed in DM patients, with MIF showing significant alterations in DM patients with cancer. MIF may serve as a crucial prognostic biomarker and therapeutic target for various cancers, playing a pivotal role in linking DM to cancer through the modulation of CD4+ Th1 cells, NKT cells, and MDSCs.
Insights
This study identifies macrophage migration inhibitory factor (MIF) as a key link between dermatomyositis (DM) and cancer. Elevated MIF levels in DM patients with cancer suggest it as a potential therapeutic target for improving cancer prognosis and immunotherapy outcomes.
Area of Science:
- Immunology
- Oncology
- Genetics
Background:
- Dermatomyositis (DM) is an inflammatory myopathy associated with an increased risk of cancer.
- The precise biological mechanisms connecting DM to cancer remain incompletely understood.
- Identifying these links is crucial for developing targeted therapies.
Purpose of the Study:
- To investigate the molecular mechanisms linking DM to cancer.
- To identify key genes and pathways involved in this association.
- To explore potential therapeutic targets for DM-associated cancers.
Main Methods:
- Differential gene expression analysis and Weighted Gene Correlation Network Analysis (WGCNA) were performed on patient datasets (GSE128470, GSE1551).
- Key genes were identified using LASSO and SVM-RFE methods.
- Immune cell infiltration analysis and RT-qPCR were used to validate findings and assess gene expression in various cancers.
Main Results:
- Differentially expressed genes (DEGs) related to innate immunity and autoimmune responses were identified.
- WGCNA highlighted MIF, C1QA, and CDKN1A as central genes in DM.
- Elevated MIF expression in DM patients correlated with cancer presence, prognosis, and modulated specific immune cell populations (CD4+ Th1, NKT, MDSCs), impacting immunotherapy potential.
Conclusions:
- MIF, C1QA, and CDKN1A are differentially expressed in DM, with MIF significantly altered in DM patients with cancer.
- MIF emerges as a critical prognostic biomarker and therapeutic target for various cancers.
- MIF plays a key role in linking DM to cancer by modulating immune cells, potentially influencing immunotherapy outcomes.
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