Identificación de biomarcadores potenciales de la ferroptosis en el mieloma múltiple mediante WGCNA y experimentos
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Published on: March 15, 2024
Yifan Wang1, Xing Xie2, Mengyuan Gu1
1Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, Guangxi, China.
Introduction:
Multiple myeloma is a common malignant tumor of the hematologic system, and genetic alterations play a crucial role in its occurrence and development. Ferroptosis is an oxidative and iron-dependent programmed cell death, which has a strong correlation with tumor development. This study aimed to identify potential diagnostic ferroptosis-related genes of MM.
Methods:
MM datasets were screened from the GEO database using publicly available transcriptomic data. Ferroptosis-related hub genes were identified through enrichment analysis, WGCNA, and machine learning algorithms. ROC curves, boxplots, RT-qPCR, and ELISA were conducted to validate the expression levels of these hub genes.
Results:
A total of 178 ferroptosis-related DEGs were identified, including 114 up-regulated genes and 64 down-regulated genes. Enrichment analysis indicated that the DEGs were primarily associated with stress, autophagy, and metabolism. According to the WGCNA, the brown module has the highest correlation with clinical symptoms, containing 1141 DEGs. Combining with the identified ferroptosis-related DEGs, two hub genes of CDKN1A and BCAT2 were identified by multiple bioinformatics techniques of LASSO, SVM, and Random Forest. ROC curves demonstrated strong diagnostic values in CDKN1A (test set, AUC = 0.881; validation set, AUC = 0.705) and BCAT2 (test set, AUC = 0.808; validation set, AUC = 0.756). RT-qPCR confirmed that the mRNA expression levels of CDKN1A and BCAT2 in three MM cells (RPMI 8226, WT-U266, and LP-1) were both significantly higher than the control HMy2.CIR cell line (p < 0.05). ELISA quantification revealed significantly elevated relative expression of CDKN1A protein in the MM cohort compared to healthy controls (p < 0.01), but the protein expression of BCAT2 exhibited comparable levels (p > 0.05).
Conclusion:
Our results suggest that CDKN1A and BCAT2 are potential ferroptosis-related biomarkers for MM. This may help understand the molecular mechanisms and therapeutic strategies of MM.
