ArticleScientific reports2024
Identification of a novel lactylation-related gene signature predicts the prognosis of multiple myeloma and experiment verification.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Correlation analysis of serum CCL3, TRACP-5b, and sclerostin with the prognosis of multiple myeloma patients.Journal of medical biochemistry · 2026Article
- Role and clinical importance of lactylation in tumors (Review).Molecular medicine reports · 2026Review
- Lactylation-related gene signature for prognosis prediction and immune infiltration assessment in lung adenocarcinoma via bulk and single-cell RNA sequencing.Discover oncology · 2026Article
- Lactylation in cancer: molecular mechanisms and advances in clinical study.Molecular cancer · 2026Review
- Non-histone lactylation in cancer: current advances and clinical implications.Frontiers in immunology · 2026Review
- Metabolic-immune crosstalk in head and neck squamous cell carcinoma: CD44 and APP identified as causal therapeutic targets via integrated lactylation-Mendelian randomization analysis.Frontiers in immunology · 2026Article
- Multiomics Mendelian Randomization Identifies Lactylation-Related Molecular Traits in Type 1 Diabetes.Journal of diabetes research · 2026Article
- Concurrent expression of glucose-6-phosphate dehydrogenase and secreted phosphoprotein 1 characterizes an aggressive and immunosuppressive tumor state in hepatocellular carcinoma.Frontiers in cell and developmental biology · 2026Article
- Longitudinal profiling of serum ADAM17 across clinical stages in multiple myeloma: a dynamic biomarker and its association with T cell alterations.Frontiers in molecular biosciences · 2026Article
- Integrative profiling of lactylation reveals prognostic biomarkers and an immunosuppressive niche in acute myeloid leukemia.Frontiers in immunology · 2026Article
- Metabolic reprogramming in tumor-associated cells of hematologic malignancies: mechanisms, crosstalk networks, and therapeutic implications in the tumor microenvironment.Frontiers in immunology · 2026Review
- An AI-driven multi-omics framework identifies lactylation-mediated therapeutic targets to overcome drug resistance in ovarian cancer.NPJ precision oncology · 2025Article
- Lactylation-related multigene signature in multiple myeloma: integrated prognostic stratification, immune landscape profiling, and therapeutic guidance.Immunologic research · 2025Article
- Research advances of lactylation modification in breast cancer.Discover oncology · 2025Review
- Construction of lactylation-related prognostic signature for glioma.Discover oncology · 2025Article
- Roles of lactylation in lipid metabolism and related diseases.Cell death discovery · 2025Review
- A novel indirubin- 3-monoxime derivative I3MV- 8b exhibits remarkable cytotoxicity against multiple myeloma by targeting TRIM28.Biomarker research · 2025Article
- Lactylation modification in cancer: mechanisms, functions, and therapeutic strategies.Experimental hematology & oncology · 2025Review
- A Monocyte-Driven Prognostic Model for Multiple Myeloma: Multi-Omics and Machine Learning Insights.Blood and lymphatic cancer : targets and therapy · 2025Article
- Lactylation in tumor: mechanisms and therapeutic potentials.Frontiers in immunology · 2025Review
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Authors and funding
8 authors.
Funding
Abstract
Multiple myeloma (MM) is an incurable hematological malignancy with poor survival. Accumulating evidence reveals that lactylation modification plays a vital role in tumorigenesis. However, research on lactylation-related genes (LRGs) in predicting the prognosis of MM remains limited. Differentially expressed LRGs (DELRGs) between MM and normal samples were investigated from the Gene Expression Omnibus database. Univariate Cox regression and LASSO Cox regression analysis were applied to construct gene signature associated with overall survival. The signature was validated in two external datasets. A nomogram was further constructed and evaluated. Additionally, Enrichment analysis, immune analysis, and drug chemosensitivity analysis between the two groups were investigated. qPCR and immunofluorescence staining were performed to validate the expression and localization of PFN1. CCK-8 and flow cytometry were performed to validate biological function. A total of 9 LRGs (TRIM28, PPIA, SOD1, RRP1B, IARS2, RB1, PFN1, PRCC, and FABP5) were selected to establish the prognostic signature. Kaplan-Meier survival curves showed that high-risk group patients had a remarkably worse prognosis in the training and validation cohorts. A nomogram was constructed based on LRGs signature and clinical characteristics, and showed excellent predictive power by calibration curve and C-index. Moreover, biological pathways, immunologic status, as well as sensitivity to chemotherapy drugs were different between high- and low-risk groups. Additionally, the hub gene PFN1 is highly expressed in MM, knocking down PFN1 induces cell cycle arrest, suppresses cell proliferation and promotes cell apoptosis. In conclusion, our study revealed that LRGs signature is a promising biomarker for MM that can effectively early distinguish high-risk patients and predict prognosis.
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