Abstract
Background: Ferroptosis, an iron-dependent form of programmed cell death, has been implicated in various types of cancer. However, the association between ferroptosis-related long noncoding RNAs (FRLs) and multiple myeloma (MM) remains unclear. This study aimed to develop an FRL-based predictive model to assess its potential role in predicting overall survival prognosis and evaluating immune cell infiltration and chemotherapy response in MM patients. Methods: We identified FRLs using the GEO and FerrDb databases and employed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) to establish a prognostic FRLs signature in the training cohort. The reliability of the risk model was evaluated using Kaplan-Meier (K-M) and time-dependent receiver operating characteristic (ROC) curve analyses. Gene set enrichment analysis (GSEA) was conducted to explore the biological functions associated with the FRLs signature. We also assessed immune cell infiltration and estimated the IC50 of drugs using the R package 'pRRophetic'. The expression of FRLs was validated by qRT-PCR. Results: We established a novel 8 FRLs signature, comprising AC005592.1, AC093714.1, AC104041.1, AL122058.1, DIRC1, ERVH-1, FAM223B, and TDRKH-AS1. The risk model was identified as an independent risk factor for overall survival (OS) in MM patients. Bioinformatics analysis indicated that the high-risk group exhibited activation of carcinogenic signaling pathways and immune cell infiltration. The qRT-PCR confirmed the significant upregulation in the expression of ERVH-1, TDRKH-AS1, and AC104041.1, and the downregulation of DIRC1, AC005592.1, AC093714.1, and AL122058.1 in MM samples. Furthermore, the ferroptosis inducer erastin triggered ferroptosis, inhibited cell viability, and upregulated TDRKH-AS1. Conclusion: Our study highlights the potential of the FRLs signature as a prognostic tool and its implications for therapeutic strategies in MM.