ArticleBMC cancer2025
Prognostic value of fatty acid metabolism-related signature and integrated analysis of the immune microenvironment in multiple myeloma.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Aggressive multiple myeloma with lymph node involvement, loss of CD138, and adipophilin-positive cytoplasmic vacuolization: a case report.Medical molecular morphology · 2026Article
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Abstract
objectiveIdentifying fatty acid metabolism (FAM)-related molecular signatures to construct a prognostic model for multiple myeloma (MM) patients.
methodsTranscriptomic profiles and clinical data from MM patients were retrieved from GEO and MMRF databases. FAM-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 FAM-related gene characteristics and risk scores. A clinical nomogram incorporating risk scores was developed. Immune microenvironment analysis (CIBERSORT) and functional enrichment (GO/KEGG/GSVA) were performed to characterize risk groups. Quantitative PCR validated hub gene expression in bone marrow mononuclear cells (BMMCs) from 10 newly diagnosed MM patients and 10 healthy donors. In vitro functional assays (CCK-8 proliferation, flow cytometry cell cycle analysis) assessed the impact of CCNA2/KIF11/NUSAP1 knockdown in MM cell lines.
resultsWe identified 37 prognostic FAM-related genes (FMGs). 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 qRT-PCR analysis revealed CCNA2, KIF11, and NUSAP1 up-regulated in MM patients. CCNA2, KIF11, and NUSAP1 knockdown significantly caused cell cycle arrest and decreased proliferation ability of MM cells.
conclusionWe identified 37 survival-associated FMGs in MM patients, and verified the effects of CCNA2, KIF11, and NUSAP1 on the cell cycle and proliferation of MM cells. Our results also suggest that survival-associated traits based on these genes are potentially robust prognostic biomarkers for MM patients.
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