Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11199273 | PMC |
http://dx.doi.org/10.1007/s10238-024-01398-w | DOI Listing |
Background: Metabolic pathways are known to significantly impact the development and advancement of lung cancer. This study sought to establish a signature related to butyrate metabolism that is specifically linked to lung adenocarcinoma (LUAD).
Methods: For the purpose of identifying butyrate metabolism-related differentially expressed genes (BMR-DEGs) in the TCGA-LUAD dataset, we introduced transcriptome data.
BMC Genomics
January 2025
College of Fisheries, Huazhong Agricultural University, No.1, Shizishan street, Wuhan, 430070, Hubei, China.
Background: Megalobrama amblycephala presents unsynchronized growth, which affects its productivity and profitability. The liver is essential for substance exchange and energy metabolism, significantly influencing the growth of fish.
Results: To investigate the differential metabolites and genes governing growth, and understand the mechanism underlying their unsynchronized growth, we conducted comprehensive transcriptomic and metabolomic analyses of liver from fast-growing (FG) and slow-growing (SG) M.
Am J Reprod Immunol
January 2025
State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University, Jinan, Shandong, China.
Background: Alterations in lipid metabolism were reported to impact human fertility; however, there is limited evidence on the association of lipid metabolism with embryo implantation as well as the etiology of recurrent implantation failure (RIF), especially regarding arachidonic acid metabolism.
Methods: Experimental verification research (16 RIF patients and 30 control patients) based on GEO database analysis (24 RIF patients and 24 control patients). The methods in bioinformatics included differential gene screening, functional enrichment analysis, protein-protein interaction network, cluster analysis, weighted gene co-expression network analysis, and so forth.
Acta Physiol (Oxf)
February 2025
Laboratory of Biological Rhythms, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic.
Aim: Exposure to light at night and meal time misaligned with the light/dark (LD) cycle-typical features of daily life in modern 24/7 society-are associated with negative effects on health. To understand the mechanism, we developed a novel protocol of complex chronodisruption (CD) in which we exposed female rats to four weekly cycles consisting of 5-day intervals of constant light and 2-day intervals of food access restricted to the light phase of the 12:12 LD cycle.
Methods: We examined the effects of CD on behavior, estrous cycle, sleep patterns, glucose homeostasis and profiles of clock- and metabolism-related gene expression (using RT qPCR) and liver metabolome and lipidome (using untargeted metabolomic and lipidomic profiling).
J Agric Food Chem
January 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu 214122, China.
This study investigated whether the galactooligosaccharide (GOS)-metabolism-related genes (GOS-cluster) in contribute to alleviating glucose and lipid metabolic disorders in type 2 diabetic mice. Genomic analysis of 69 strains based on the GOS-cluster, combined with in vitro fermentation experiments, revealed that high-GOS-cluster strains (≥24 MFS, ≥39 GOS-cluster) demonstrated superior GOS utilization and bile salt tolerance. In vivo the high-GOS-cluster strains resulted in a significant reduction of blood glucose levels by 18.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!