Lactate Metabolism-Related Genes to Predict the Clinical Outcome and Molecular Characteristics of Multiple Myeloma

Background Metabolic reprogramming is a hallmark of cancer progression and holds great significance for the tumor microenvironment (TME). Lactate, as an abundant metabolite, has been found to play a critical role in the development of cancer and in the immunosuppression of TME. However, the potential role of lactate metabolism-related genes in multiple myeloma (MM) remains unclear. Methods RNA sequencing data and clinical information of multiple myeloma (MM) were obtained from The Cancer Genome Atlas (TCGA) database. Lactate metabolism-related genes (LMRGs) were sourced from Molecular Signature Database v7.4, and then compared with the candidate genes from TCGA to obtain the final gene set. Prognostic genes were screened using univariate analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. A lactate metabolism-related risk profile was constructed using multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analysis and Kaplan-Meier analysis. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional analysis were performed to compare high-risk groups with low-risk groups. CCK8 assays were utilized to assess the proliferation ability of MM cells. Transwell assay was employed to detect their migration ability. Intracellular lactate content as well as glucose content was measured to evaluate lactate metabolism levels. Loss or gain-of-function studies were carried out using shRNA knockdown or lentiviral transduction strategies in order to investigate the precise role of LMRGs in MM. Results We developed a risk signature based on 18 LMRGs. Kaplan-Meier curves confirmed that the high-risk group exhibited a poorer prognosis compared to the low-risk group. Subsequently, a nomogram was constructed to predict the probability of MM survival. Additionally, we conducted GO enrichment analysis and KEGG pathway functional analysis between the high and low-risk groups, which revealed significant associations with immune regulation and energy metabolism. Furthermore, we demonstrated that one of the lactate metabolism-related genes, JAMIP2, could promote myeloma cell proliferation, migration, and lactate metabolism via activating PI3K-Akt signaling pathway. Conclusion In conclusion, this study identified and constructed LMRGs in MM, which showed high diagnostic accuracy in predicting OS in MM patients and linked to immunity and drug sensitivity. JAMIP2, which was identified as a novel molecule mediating lactate metabolism, promoted MM cell proliferation, migration and lactate metabolism through PI3K-Akt signaling pathway. Future studies are expected to validate the utility of the constructed LMRGs in MM patients.