Background Numerous studies have manifested long noncoding RNAs (lncRNAs) as biomarkers to determine the prognosis of multiple myeloma (MM) patients. Nevertheless, the prognostic role of lncRNAs in MM is still ambiguous. Herein, we performed a meta‐analysis to evaluate the predictive value of aberrantly expressed lncRNAs in MM. Methods A systemic literature search was performed in PubMed, EMBASE, Cochrane, and Web of Science databases until October 9, 2021, and the protocol was registered in the PROSPERO database (CRD42021284364). Our study extracted the hazard ratios (HRs) and 95% confidence intervals (CIs) of overall survival (OS), progression‐free survival (PFS), or event‐free survival (EFS). Begg's and Egger's tests were employed to correct publication bias. Result Twenty‐six individual studies containing 3501 MM patients were enrolled in this study. The results showed that aberrant expression of lncRNAs was associated with poor OS and PFS of MM patients. The pooled HRs for univariate OS and PFS were 1.48 (95% CI = 1.17–1.88, p < 0.001) and 1.30 (95% CI = 1.18‐1.43, p < 0.001), respectively, whereas the pooled HRs for multivariate OS and PFS were 1.50 (95% CI = 1.16‐1.95, p < 0.001) and 1.59 (95% CI = 1.22‐2.07, p < 0.001), respectively. Subgroup analysis suggested that MALAT1, TCF7, NEAT1, and PVT1 upregulation were associated with poor OS ( p < 0.05), PVT1, and TCF7 upregulation were implicated with worse PFS ( p < 0.05), while only TCF7 overexpression was correlated with reduced EFS ( p < 0.05). Moreover, the contour‐enhanced funnel plot demonstrated the reliability of our current conclusion, which was not affected by publication bias. Conclusion Aberrantly expressed particular lncRNAs are critical prognostic indicators in long‐term survival as well as promising biomarkers in progression‐free status. However, different cutoff values and dissimilar methods to assess lncRNA expression among studies may lead to heterogeneity.

Emerging insights into iron-dependent form of regulated cell death ferroptosis in cancer have opened a perspective for its use in cancer therapy. Of interest, a systematic profiling of ferroptosis gene signatures as prognostic factors has gained special attention in several cancers. Herein, we sought to investigate the presence of repetitive genomes in the vicinity of ferroptosis genes that may influence their expression and to establish a prognostic gene signature associated with multiple myeloma (MM). Our analysis showed that genes associated with ferroptosis were enriched with the repetitive genome in their vicinity, with a strong predominance of the SINE family, followed by LINE, of which the most significant discriminant values were SINE/Alu and LINE/L1, respectively. In addition, we examined in detail the performance of these genes as a cancer risk prediction model and specified fourteen ferroptosis-related gene signatures, which identified MM high-risk patients with lower immune/stromal scores with higher tumor purity in their immune microenvironment. Of interest, we also found that lncRNA CRNDE correlated with a risk score and was highly associated with the majority of genes comprising the signature. Taken together, we propose to investigate the molecular impact of the repetitive genome we have highlighted on the local transcriptome of ferroptosis genes in cancer. Furthermore, we revealed a genomic signature/biomarker related to ferroptosis that can be used to predict the risk of survival in MM patients.