OBJECTIVE: To entrap carvacrol (CAR) in bovine serum albumin nanoparticles (BSANPs) to form CAR-loaded BSANPs (CAR@BSANPs) and to explore the anti-cancer effects in breast adenocarcinoma cells (MCF-7 cells) treated with CAR and CAR@BSANPs. METHODS: A desolvation method was used to synthesize BSANPs and CAR@BSANPs. The BSANPs and CAR@BSANPs were characterized by several physicochemical methods, including visual observation, high-resolution field emission scanning electron microscopy, Fourier transform infrared spectroscopy, and high-performance liquid chromatography. MCF-7 cells were used and analyzed after 24 h of exposure to CAR and CAR@BSANPs at half-maximal inhibitory concentration. The anti-proliferative, apoptotic, reactive oxygen species (ROS), and nitric oxide (NO) scavenging activity as well as gene expression analysis were investigated by the cell viability assay, phase-contrast microscopy, 2',7'-dichlorofluorescein-diacetate assay, Griess-Illosvoy colorimetric assay, and quantitative real-time polymerase chain reaction, respectively. RESULTS: CAR and CAR@BSANPs showed anti-proliferative, apoptotic, ROS generation, and NO scavenging effects on MCF-7 cells. Expression profile of B-cell lymphoma 2-like 11 (BCL2L11), vascular endothelial growth factor A (VEGFA), hypoxia inducible factor factor-1α (HIF1A), BCL2L11/apoptosis regulator (BAX), and BCL2L11/Bcl2 homologous antagonist/killer 1 (BAK1) ratios revealed downregulated genes; and BAX, BAK1, and CASP8 were upregulated by CAR and CAR@BSANPs treatment. In vitro anticancer assays of the CAR and CAR@BSANPs showed that CAR@BSANPs demonstrated higher therapeutic efficacy in the MCF-7 cells than CAR. CONCLUSIONS CAR and CAR@BSANPs affect gene expression and may subsequently reduce the growth and proliferation of the MCF-7 cells. Molecular targeting of regulatory genes of the MCF-7 cells with CAR and CAR@BSANPs may be an effective therapeutic strategy against breast cancer.
Humans ; Cymenes ; Nanoparticles/ultrastructure* ; MCF-7 Cells ; Breast Neoplasms/genetics* ; Apoptosis/drug effects* ; Serum Albumin, Bovine/chemistry* ; Monoterpenes/therapeutic use* ; Adenocarcinoma/genetics* ; Cell Proliferation/drug effects* ; Reactive Oxygen Species/metabolism* ; Female ; Cell Survival/drug effects* ; Animals ; Gene Expression Regulation, Neoplastic/drug effects* ; Nitric Oxide/metabolism* ; Cattle

OBJECTIVE: To investigate the effect of miR-483-5p on hepatocellular carcinoma (HCC) cells proliferation and stemness, as well as the attenuating effect of Pien Tze Huang (PZH). METHODS: Differentially expressed miRNA between HepG2 cells and hepatic cancer stem-like cells (HCSCs) were identified by a miRNA microarray assay. miR-483-5p mimics were transfected into HepG2 cells to explore the effects of miR-483-5p on cell proliferation and stemness. HepG2 cells and HCSCs were treated with PZH (0, 0.25, 0.50 and 0.75 mg/mL) to explore the effects of PZH on the proliferation and stemness, both in non-induced state and the state induced by miR-483-5p mimics. RESULTS: miR-483-5p was significantly up-regulated in HCSCs and its overexpression increased cell proliferation and stemness in HepG2 cells (P<0.05). PZH not only significantly inhibited proliferation in HepG2 cells, but also significantly suppressed the cell proliferation and self-renewal of HCSCs (P<0.05). The effects of miR-483-5p mimics on proliferation and stemness of HepG2 cells were partially abolished by PZH. CONCLUSIONS miR-483-5p promotes proliferation and enhances stemness of HepG2 cells, which were attenuated by PZH, demonstrating that miR-483-5p is a potential molecular target for the treatment of HCC and provide experimental evidence to support clinical use of PZH for patients with HCC.
Humans ; MicroRNAs/metabolism* ; Cell Proliferation/drug effects* ; Liver Neoplasms/drug therapy* ; Carcinoma, Hepatocellular/drug therapy* ; Hep G2 Cells ; Neoplastic Stem Cells/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Gene Expression Regulation, Neoplastic/drug effects*

OBJECTIVES: Ovarian cancer is a common gynecologic malignancy, with poor prognosis in advanced stages. This study aimed to identify differentially expressed long noncoding RNA (lncRNA) associated with ovarian cancer prognosis and to explore the effects of lncRNA RP11-499E18.1 on the malignant biological behavior of ovarian cancer cells. METHODS: Ovarian cancer-related lncRNA datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed and prognostically relevant tumor-suppressive lncRNAs were screened using lncRNA sequencing combined with clinical data. Reverse transcription PCR (RT-PCR) was used to detect the expression of lncRNA RP11-499E18.1 in ovarian cancer tissues, adjacent normal tissues, the IOSE80 normal ovarian epithelial cell line, and various ovarian cancer cell lines. Fluorescence in situ hybridization (FISH) was performed to determine its subcellular localization. Ovarian cancer cell lines CaOV3 and SKOV3 were divided into 3 groups: a negative control (NC) group, a knockdown (si-RP11-499E18.1) group, and a overexpression (pcDNA-RP11-499E18.1) group. Methyl thiazolyl tetrazolium (MTT) and Transwell assays were used to assess the effects of lncRNA RP11-499E18.1 on cell proliferation and migration. Western blotting was used to evaluate its effect on epithelial-mesenchymal transition (EMT)-related molecules. BALB/c nude mice were injected with CaOV3 cells transfected with pcDNA-RP11-499E18.1 (experimental group) or empty vector (control group), and tumor growth was monitored. Immunohistochemistry was used to assess the expression of Caspase 3 and Ki67 in tumor tissues. RESULTS: LncRNA sequencing identified RP11-499E18.1 as a differentially expressed and associated with prognosis. GEO data analysis showed that low RP11-499E18.1 expression was correlated with shorter overall and progression-free survival (both P<0.05). Its expression was significantly lower in ovarian cancer tissues and cell lines compared to normal controls (P<0.05 or P<0.001), and it was localized in both the nucleus and cytoplasm. In CaOV3 and SKOV3 cells, proliferation rates increased significantly in the si-RP11-499E18.1 group and decreased in the pcDNA-RP11-499E18.1 group (P<0.05 or P<0.001). Cell migration was enhanced in the si-RP11-499E18.1 group and suppressed in the pcDNA-RP11-499E18.1 group. Overexpression increased E-cadherin and decreased vimentin expression, while knockdown had the opposite effect. Tumor volume in the mouse model was significantly smaller in the experimental group (P<0.001), with increased Caspase 3 and decreased Ki67 expression in tumor tissues (both P<0.05). CONCLUSIONS LncRNA RP11-499E18.1 inhibits proliferation, migration, and EMT of ovarian cancer cells, and its low expression is associated with poor prognosis.
Female ; Humans ; RNA, Long Noncoding/physiology* ; Ovarian Neoplasms/pathology* ; Cell Line, Tumor ; Animals ; Mice ; Mice, Nude ; Cell Proliferation ; Prognosis ; Mice, Inbred BALB C ; Gene Expression Regulation, Neoplastic ; Cell Movement ; Epithelial-Mesenchymal Transition

OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is characterized by complex pathogenesis and poor prognosis. In recent years, epithelial-mesenchymal transition (EMT) in tumor initiation and progression has attracted increasing attention. Enhancer of zeste homolog 2 (EZH2), which is aberrantly expressed in various tumors, may be closely related to the EMT process. This study aims to examine the expression and correlation of EZH2 and EMT markers in ESCC cells and tissues, evaluate the effects of EZH2 knockdown on ESCC cell proliferation, invasion, and migration, and explore how EZH2 contributes to the malignant biological behavior of ESCC. METHODS: Bioinformatics analyses were used to assess EZH2 expression levels in ESCC. Small interfering RNA was used to knock down EZH2 in ESCC cell lines EC109 and EC9706. Cell proliferation, invasion, and migration were evaluated using cell counting kit-8 (CCK-8), wound healing, and Transwell assays. Protein and mRNA expression levels of EZH2, E-cadherin (E-cad), and vimentin (Vim) were detected by Western blotting and real time fluorogenic quantitative PCR (RT-qPCR), respectively. Immunohistochemical (IHC) staining was performed on 70 ESCC tissue samples and 40 paired adjacent normal tissues collected from the First Affiliated Hospital of Shihezi University between 2010 and 2016 to assess the expression of EZH2, E-cad, and Vim, and to analyze their associations with clinicopathological feature and patient prognosis. RESULTS: Bioinformatics analysis showed that EZH2 was highly expressed in ESCC (P<0.001), and high EZH2 expression was associated with worse prognosis (P<0.001). CCK-8, wound healing, and Transwell assays demonstrated that EZH2 knockdown significantly suppressed the proliferation, invasion, and migration of ESCC cells (P<0.001). In addition, Vim expression was significantly reduced, while E-cad expression was significantly increased at both protein and mRNA levels in EZH2-silenced cells (all P<0.05). IHC staining analysis revealed higher expression of EZH2 and Vim and lower expression of E-cad in ESCC tissues compared to adjacent normal tissues. Kaplan-Meier survival analysis showed that low expression of EZH2 and Vim and high expression of E-cad were associated with longer survival (all P<0.05). CONCLUSIONS EZH2 promotes malignant biological behavior in ESCC by mediating EMT. Elevated EZH2 expression is associated with poor prognosis in ESCC patients.
Humans ; Enhancer of Zeste Homolog 2 Protein/physiology* ; Esophageal Squamous Cell Carcinoma/pathology* ; Epithelial-Mesenchymal Transition/genetics* ; Esophageal Neoplasms/metabolism* ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement ; Cadherins/genetics* ; Vimentin/genetics* ; Male ; Female ; Middle Aged ; Neoplasm Invasiveness ; Prognosis ; RNA, Small Interfering/genetics* ; Gene Expression Regulation, Neoplastic

OBJECTIVES: Hepatocellular carcinoma is one of the most common primary malignant tumors with the third highest mortality rate worldwide. This study aims to identify key genes associated with hepatocellular carcinoma prognosis using the Gene Expression Omnibus (GEO) database and provide a theoretical basis for discovering novel prognostic biomarkers for hepatocellular carcinoma. METHODS: Hepatocellular carcinoma-related datasets were retrieved from the GEO database. Differentially expressed genes (DEGs) were identified using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and key genes were identified using Cytoscape software. The University of Alabama at Birmingham Cancer Data Analysis Resource (UALCAN) was used to analyze the expression levels of key genes in normal and hepatocellular carcinoma tissues, as well as their associations with pathological grade, clinical stage, and patient survival. The Human Protein Atlas (THPA) was used to further validate the impact of key genes on overall survival. Expression levels of key genes in the blood of hepatocellular carcinoma patients were evaluated using the expression atlas of blood-based biomarkers in the early diagnosis of cancers (BBCancer). RESULTS: A total of 78 DEGs were identified from the GEO database. GO and KEGG analyses indicated that these genes may contribute to hepatocellular carcinoma progression by promoting cell division and regulating protein kinase activity. Sixteen key genes were screened via Cytoscape and validated using UALCAN and THPA. These genes were overexpressed in hepatocellular carcinoma tissues and were associated with disease progression and poor prognosis. Finally, BBCancer analysis showed that ASPM and NCAPG were also elevated in the blood of hepatocellular carcinoma patients. CONCLUSIONS This study identified 16 key genes as potential prognostic biomarkers for hepatocellular carcinoma, among which ASPM and NCAPG may serve as promising blood-based markers for hepatocellular carcinoma.
Humans ; Carcinoma, Hepatocellular/mortality* ; Liver Neoplasms/pathology* ; Prognosis ; Computational Biology/methods* ; Protein Interaction Maps/genetics* ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Gene Ontology ; Databases, Genetic

OBJECTIVES: Oxaliplatin (OXA) and 5-fluorouracil (5-FU) are 2 commonly used chemotherapeutic agents for colorectal cancer (CRC). MicroRNAs (miRNAs, miRs) play crucial roles in the development of chemoresistance in various cancers. However, the role and mechanism of miR-224-5p in regulating CRC chemoresistance remain unclear. This study aims to investigate the function of miR-224-5p in chemoresistant CRC cells and the underlying mechanisms. METHODS: CRC datasets GSE28702 and GSE69657 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs between drug-sensitive and resistant groups (OXA or 5-FU) were analyzed, and miR-224-5p was identified as the target miRNA. Chemoresistant cell lines HCT15-OXR, HCT15-5-FU, SW480-OXR, and SW480-5-FU were established. Transient transfections were performed using miR-224-5p mimics, inhibitors, and their respective negative controls (control mimic, control inhibitor) in these cell lines. Cells were treated with different concentrations of OXA or 5-FU post-transfection, and the half-maximal inhibitory concentration (IC₅₀) was determined using the cell counting kit-8 (CCK-8) assay. Cell proliferation was assessed by CCK-8 and colony formation assays. The expression levels of miR-224-5p, LC3, and P62 were measured by real-time polymerase chain reaction (real-time PCR) and/or Western blotting. Autophagic flux was assessed using a tandem fluorescent-tagged LC3 reporter assay. TargetScan 8.0, miRTarBase, miRPathDB, and HADb were used to predict B-cell lymphoma-2 (Bcl-2) as a potential miR-244-5p target, which was further validated by dual-luciferase reporter assays. RESULTS: Chemoresistant CRC cells exhibited down-regulated miR-224-5p expression, whereas up-regulation of miR-224-5p enhanced chemotherapy sensitivity. Exposure to OXA or 5-FU significantly increased autophagic activity in chemoresistant CRC cells, which was reversed by miR-224-5p overexpression. Dual-luciferase assays verified Bcl-2 as a direct target of miR-224-5p. CONCLUSIONS MiR-224-5p regulates chemoresistance in CRC by modulating autophagy through direct targeting of Bcl-2.
Humans ; MicroRNAs/physiology* ; Colorectal Neoplasms/drug therapy* ; Drug Resistance, Neoplasm/genetics* ; Autophagy/drug effects* ; Fluorouracil/pharmacology* ; Oxaliplatin ; Cell Line, Tumor ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Gene Expression Regulation, Neoplastic

OBJECTIVES: Metastasis is the primary cause of death in osteosarcoma, and current clinical treatments remain limited. BRD4, a key epigenetic regulator, has shown therapeutic promise in various cancers through its inhibition. However, the mechanistic role of BRD4 in osteosarcoma remains poorly understood. This study aims to elucidate the molecular mechanisms by which BRD4 regulate osteosarcoma progression and to explore novel therapeutic strategies. METHODS: Immunofluorescence was used to assess BRD4 expression levels in a tissue microarray containing 80 osteosarcoma samples from different patients. The Gene Expression Omnibus (GEO) dataset (GSE42352, containing survival data from 88 osteosarcoma patients) was downloaded to perform Kaplan-Meier survival analysis based on BRD4 gene expression levels. In vivo, an orthotopic intramedullary osteosarcoma model was established using HOS cells in C57 mice, followed by treatment with varying doses of the BRD4 inhibitor (+)-JQ1. Micro-CT, 3D reconstruction of bone tissue, and HE staining were employed to evaluate pathological changes in bone and intestinal lymph nodes. In vitro, cell viability was measured using the methyl thiazolyl tetrazolium (MTT) assay, while colony formation and Transwell assays assessed proliferative and invasive capacities. Chromatin-bound BRD4 was analyzed via co-immunoprecipitation combined with mass spectrometry (Co-IP/MS), and O-GlcNAc glycosylation sites and glycan chains of BRD4 were identified using Co-IP with Nano-LC MS/MS. Real-time PCR and Western blotting were used to analyze the relative mRNA and protein expression levels of target genes, respectively. RESULTS: BRD4 was positively expressed in 61.25% (49/80) of osteosarcoma tissues. Patients with high BRD4 expression exhibited significantly shorter survival times (P<0.05). In the orthotopic mouse model, intervention with (+)-JQ1, a potent and commonly used BETi, significantly inhibited tumor growth in vivo and reduced bone destruction (P<0.05). (+)-JQ1 treatment significantly suppressed the proliferation (P<0.001), invasion (P<0.001), and migration (P<0.05) of HOS cells. In osteosarcoma cells, BRD4 exhibited O-GlcNAc modifications at both N- and C- C-termini, particularly at Thr73, which is essential for protein stability. This modification also contributed to the activation of the EGFR tyrosine kinase inhibitor resistance pathway (KEGG Pathway: hsa01521). (+)-JQ1 treatment displaced BRD4 from enhancers and downregulated the transcription of pathway-related genes, such as EGFR and PDGFC, thereby suppressing the malignant behavior of osteosarcoma cells. CONCLUSIONS BRD4 promotes osteosarcoma progression via O-GlcNAc modification at Thr73 and plays a crucial role in tumor growth and metastasis.
Osteosarcoma/drug therapy* ; Humans ; Transcription Factors/metabolism* ; Animals ; Cell Cycle Proteins ; Mice ; Bone Neoplasms/drug therapy* ; Azepines/pharmacology* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Triazoles/pharmacology* ; Mice, Inbred C57BL ; Nuclear Proteins/metabolism* ; Gene Expression Regulation, Neoplastic ; Male ; Bromodomain Containing Proteins

OBJECTIVES: Osteoarthritis (OA) and sarcopenia are significant health concerns in the elderly, substantially impacting their daily activities and quality of life. However, the relationship between them remains poorly understood. This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia. METHODS: Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between disease and control groups were identified using R software. Common DEGs were extracted via Venn diagram analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs. Protein-protein interaction (PPI) networks were constructed, and candidate hub genes were ranked using the maximal clique centrality (MCC) algorithm. Further validation of hub gene expression was performed using 2 independent datasets. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia. Mouse models of OA and sarcopenia were established. Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model. The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement. Real-time reverse transcription PCR (real-time RT-PCR) was employed to assess the mRNA expression levels of candidate key genes in both models. Gene set enrichment analysis (GSEA) was conducted to identify pathways associated with the selected shared key genes in both diseases. RESULTS: A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia, including 76 upregulated and 13 downregulated genes. These 89 DEGs were significantly enriched in protein digestion and absorption, the PI3K-Akt signaling pathway, and extracellular matrix-receptor interaction. PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes. Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets, AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases, both of which showed a significant upregulation trend in the disease groups (all P<0.05). The value of area under the curve (AUC) for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7, indicating that both genes have potential value in predicting OA and sarcopenia. Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups (all P<0.05), consistent with the results observed in the bioinformatics analysis. GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction, ribosome, and oxidative phosphorylation in OA and sarcopenia. CONCLUSIONS AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia. The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.
Sarcopenia/genetics* ; Osteoarthritis/genetics* ; Computational Biology/methods* ; Humans ; Protein Interaction Maps/genetics* ; Animals ; Mice ; Gene Expression Profiling ; Gene Ontology ; Transcriptome ; Male ; Signal Transduction/genetics* ; Gene Regulatory Networks

OBJECTIVES: Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects women's health. This study aims to investigate gene and transcription factor (TF) expression differences between PCOS patients and healthy individuals using bioinformatics approaches, and to verify the function of key transcription factors, with the goal of providing new insights into the pathogenesis of PCOS. METHODS: Differentially expressed genes (DEGs) and differentially expressed transcription factors (DETFs) between PCOS patients and controls were identified from the RNA sequencing dataset GSE168404 using bioinformatics methods. Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The expression and function of core transcription factors were further validated in ovarian tissues of PCOS model mice and control mice using Western blotting and reverse transcription quantitative polymerase chain reaction (RT-qPCR). RESULTS: A total of 332 DEGs were identified between PCOS patients and controls, including 259 upregulated and 73 downregulated genes in the PCOS group. 19 DETFs were further screened, of which 16 were upregulated and 3 were downregulated in PCOS. The upregulated DETFs (including TFCP2L1, DACH1, ESR2, AFF3, SMAD9, ZNF331, HOPX,ATOH8, HIF3α, DPF3, HOXC4, HES1, ID1, JDP2, SOX4, and ID3) were primarily associated with lipid metabolism, development, and cell adhesion. Protein and mRNA expression analysis in PCOS model mice revealed significantly decreased levels of hypoxia-inducible factor (HIF) 1α and HIF2α, and significantly increased expression of HIF3α compared to control mice (all P<0.001). CONCLUSIONS Significant differences in gene and TF expression exist between PCOS patients and healthy individuals. HIF-3α may play a crucial role in PCOS and could serve as a novel biomarker for diagnosis and a potential therapeutic target.
Polycystic Ovary Syndrome/metabolism* ; Female ; Humans ; Animals ; Mice ; Transcription Factors/metabolism* ; Computational Biology ; Gene Expression Profiling ; Adult

OBJECTIVES: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy, with disease progression driven by cytogenetic abnormalities and a complex bone marrow microenvironment. This study aims to construct a prognostic model for MM based on transcriptomic data and lipid metabolism related genes (LRGs), and to identify potential drug targets for high-risk patients to support clinical decision-making. METHODS: In this study, 2 transcriptomic datasets covering 985 newly diagnosed MM patients were retrieved from the Gene Expression Omnibus (GEO) database. Univariate Cox regression and 101 machine learning algorithms were used for gene selection. An LRG-based prognostic model was constructed using Stepwise Cox (both directions) and random survival forest (RSF) algorithms. The association between the prognostic score and clinical events was evaluated, and model performance was assessed using time-dependent receiver operating characteristic (ROC) curves and the C-index. The added predictive value of combining prognostic scores with clinical variables and staging systems was also analyzed. Differentially expressed genes between high- and low-risk groups were identified using limma and clusterProfiler and subjected to pathway enrichment analysis. Drug sensitivity analysis was conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database and oncoPredict to identify potential therapeutic targets for high-risk patients. The functional role of key LRGs in the model was validated via in vitro cell experiments. RESULTS: An LRG-based prognostic model (LRG17) was successfully developed using transcriptomic data and machine learning. The model demonstrated robust predictive performance, with area under the curve (AUC) values of 0.962, 0.912, and 0.842 for 3-, 5-, and 7-year survival, respectively. Patients were stratified into high- and low-risk groups, with high-risk patients showing significantly shorter overall survival (OS) and event-free survival (EFS) (both P<0.001) and worse clinical profiles (e.g., lower albumin, higher β2-microglobulin and lactate dehydrogenase levels). Enrichment analysis revealed that high-risk patients were significantly enriched for pathways related to chromosome segregation and mitosis, whereas low-risk patients were enriched for immune response and immune cell activation pathways. Drug screening suggested that AURKA inhibitor BMS-754807 and FGFR3 inhibitor I-BET-762 may be more effective in high-risk patients. Functional assays demonstrated that silencing of key LRG PLA2G4A significantly inhibited cell viability and induced apoptosis. CONCLUSIONS LRGs serve as promising biomarkers for prognosis prediction and risk stratification in MM. The overexpression of chromosomal instability-related and high-risk genetic event-associated genes in high-risk patients may explain their poorer outcomes. Given the observed resistance to bortezomib and lenalidomide in high-risk patients, combination therapies involving BMS-754807 or I-BET-762 may represent effective alternatives.
Humans ; Multiple Myeloma/mortality* ; Prognosis ; Lipid Metabolism/genetics* ; Transcriptome ; Machine Learning ; Male ; Female ; Gene Expression Profiling ; Algorithms