Prognostic value of fatty acid metabolism-related signature and integrated analysis of the immune microenvironment in multiple myeloma

Objective : Exploring fatty acid metabolism-related genes and features to predict survival outcomes in patients with multiple myeloma. Methods : Transcriptional, survival, and clinicopathologic data of MM patients were downloaded from the GEO and MMRF dataset. Fatty acid-related genes were screened by WGCNA, and one-way cox analysis was performed to identify genes associated with survival. Lasso regression analysis was then performed to construct fatty acid metabolism-related gene characteristics and risk scores. In addition, a nomogram model containing risk scores was constructed to guide clinical decision-making. We also performed immune infiltration analysis and functional analysis to deeply explore the differences between high and low risk groups. Meanwhile, qPCR was conducted on BMMCs from 10 newly diagnosed MM patients and 10 healthy controls to validate the expression of CCNA2 , KIF11 , and NUSAP1 . Results : In total, 37 prognosis-related FMGs genes were identified. Among them, 16 genes were used to construct lasso regression models. KM analysis showed that high-risk patients had poorer prognosis (training set: P < 0.001; test set: P < 0.05). The area under the ROC curve was 0.787. Immunoscape analysis showed that high-risk patients had an immunosuppressive microenvironment. Functional enrichment studies confirmed that high-risk patients had increased abnormalities in cell cycle, aging and metabolic processes. The qPCR analysis revealed CCNA2 , KIF11 , and NUSAP1 up-regulated in MM patients. Conclusion : We identified 37 survival-associated FMGs in MM patients. Our results also suggest that survival-associated traits based on these genes are potentially robust prognostic biomarkers for MM patients.