Yang Song

Osteonecrosis of the femoral head (ONFH) is a disabling orthopedic condition that remains challenging to diagnose at an early stage. Recent evidence suggests that immune dysregulation plays a central role in the development of both ONFH and metabolic syndrome (MetS), a cluster of metabolic abnormalities associated with increased ONFH risk. However, reliable noninvasive diagnostic biomarkers for ONFH, particularly in high-risk MetS populations, are still lacking. This study aimed to identify key diagnostic long non-coding RNAs (lncRNAs) in ONFH patients with MetS and to construct an immune-related competitive endogenous RNA (ceRNA) network. Plasma lncRNA and mRNA expression profiles from 9 ONFH patients and 6 healthy controls were analyzed to identify differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs), followed by ceRNA network construction. The MetS dataset from the Gene Expression Omnibus (GEO) was integrated, and weighted gene co-expression network analysis (WGCNA), functional enrichment, protein-protein interaction (PPI) network analysis, MCODE, CytoHubba-MCC, and random forest (RF) algorithms were employed to identify hub mRNAs and their associated lncRNAs. A nomogram model was developed, and diagnostic potential was evaluated using receiver operating characteristic (ROC) analysis and validation in an independent cohort (45 ONFH and 45 control samples). A total of 424 DElncRNAs and 1,431 DEmRNAs were identified, and a ceRNA network involving 7 lncRNAs, 24 miRNAs, and 683 mRNAs was constructed. Integration with the MetS dataset yielded 506 intersecting mRNAs, from which 11 hub mRNAs and 6 related lncRNAs were screened. Five key lncRNAs were selected by RF analysis to construct a diagnostic model with strong predictive performance (AUC > 0.7 in both RNA-seq and qRT-PCR validation). The immune-related ceRNA network also demonstrated significant associations with immune cell infiltration patterns. In conclusion, five candidate lncRNAs (MRPS30-DT, LINC01106, MIR100HG, WDR11-AS1, and PELATON) were identified as promising noninvasive diagnostic biomarkers for ONFH in MetS populations. These findings offer novel insights into immune-related regulatory mechanisms and may support early diagnosis using peripheral blood.

The genes of Wnt/β-catenin pathway may have potential roles in fat accumulation of Non-traumatic osteonecrosis of the femoral head (ONFH), but the effects of their variants in the pathway on ONFH development have been remained unclear. To explore the potential roles of the variants in the development of ONFH, we completed the investigation of the paired interactions as well as their related biological functions of 17 variants of GSK3β, LRP5, and FRP4 genes etc. in the pathway. The genotyping of the 17 variants were finished by MASS ARRAY PLATFORM in a 560 ONFH case–control system. The association of variants interactions with ONFH risk and clinical traits was evaluated by logistic regression analysis etc. and bioinformatics technology. The results showed that the genotype, allele frequency, and genetic models of Gsk3β rs334558 (G/A), SFRP4 rs1052981 (A/G), and LRP5 rs312778 (T/C) were significantly associated with the increased and decreased ONFH risk and clinical traits, respectively (P < 0.001–0.0002). Particularly, the paired interactions of six variants as well as eight variants also showed statistically increased and decreased ONFH risk, bilateral hip lesions risk and stage IV risk of ONFH, respectively (P < 0.044–0.004). Our results not only at the first time simultaneously showed exact serum lipid disorder and abnormal platelet function of ONFH in the same study system with the 17 variants polymorphisms of Wnt/β-catenin pathway but also shed light on the variants closely intervening the lipid disorder and abnormal coagulation of ONFH.

The molecular pathogenesis and therapeutic target research studies on osteosarcoma (OS) have developed well during the last few years using various OS cell lines with reverse transcription quantitative polymerase chain reaction (RT-qPCR). However, the identification of suitable reference genes of RT-qPCR for OS cell lines has not been reported. Here, we conducted the normalization research of 12 reference genes (GAPDH, ACTB, 18S, B2M, ALAS1, GUSB, HPRT1, HMBS, PPIA, PUM1, RPL29, and TBP) for gene expression analysis in four kinds of human OS cell lines (U2OS, Saos-2, HOS, and MG-63) to improve the investigation of molecular mechanisms and the accuracy of diagnosis and prognostic molecular targets of OS. The gene expression stability and applicability of the 12 reference gene candidates were determined using geNorm, NormFinder, and BestKeeper software. The results indicated that PUM1 and the combination of PPIA + ALAS1 were recommended as the optimal reference gene in these four different sources of human OS cell lines under proliferative conditions. The present study identified the most suitable reference genes and reference gene combinations for OS cell lines under proliferative conditions in order to use in gene expression profile analysis. A reliable standardized method has the potential to improve the understanding of the biological mechanisms underlying OS in the future.

Bombyxin, as an insulin‐like insect hormone, was discovered in the silkmoth Bombyx mori. It can regulate the metabolism of trehalose and glycogen in Bombyx mori, but whether it has glucose absorption and glycogen synthesis effect on mammalian cells was not clear. BombyxinII (BbxII) and mutant BbxII (mBbxII) genes were cloned into pcDNA3.1(+) vector, respectively; then, gene vectors were transfected into 293FT cells using Lipofectamine 2000. Levels of mRNA and protein expression of BbxII and mBbxII were detected by PCR and Western blot in 293FT cells, respectively. Glucose consumption and glycogenesis were determined by glucose oxidase‐peroxidase (GOD‐POD) and periodic acid‐Schiff (PAS) staining in HepG2 cells; the PI3K signaling pathway was inhibited with wortmannin S1952 in HepG2 cells. Result showed that BbxII and mBbxII genes were being successfully expressed in 293FT cells, respectively. The expression protein of BbxII gene is 10kd pre‐bombyxinII, and yet, the expression protein of mBbxII gene is 4kd mature bombyxinII. Only the 4kd bombyxinII showed increased glucose uptake and glycogenesis in HepG2 cells, and the ability of increasing glucose uptake was equal to the human insulin (10 nM). PI3K‐wortmannin S1952 inhibitor can decrease the glycogen synthesis induced by bombyxin II protein in HepG2 cells. In conclusion, mature bombyxin II may adjust glucose absorption and glycogen synthesis in HepG2 cells through the PI3K signaling pathway.

Lung cancer remains the most lethal cancer worldwide because of its high metastasis potential. Epithelial-mesenchymal transition (EMT) is known as the first step of the metastasis cascade, but the potential regulatory mechanisms of EMT have not been clearly established. In this study, we first found that low CUEDC1 expression correlated with lymph node metastasis in non-small cell lung cancer (NSCLC) patients using immunohistochemistry (IHC). CUEDC1 knockdown promoted the metastasis of NSCLC cells and EMT process and activated TβRI/Smad signaling pathway. Overexpression of CUEDC1 decreased the metastatic potential of lung cancer cells and inhibited the EMT process and inactivated TβRI/Smad signaling pathway. Immunoprecipitation (IP) assays showed that Smurf2 is a novel CUEDC1-interacting protein. Furthermore, CUEDC1 could regulate Smurf2 expression through the degradation of Smurf2. Overexpression of Smurf2 abolished CUEDC1 knockdown induced-EMT and the activation of TβRI/Smad signaling pathway, while siRNA Smurf2 reversed CUEDC1 overexpression-mediated regulation of EMT and TβRI/Smad signaling pathway. Additionally, CUEDC1 inhibited proliferation and promoted apoptosis of NSCLC cells. In vivo, CUEDC1-knockdown cells promoted metastasis and tumor growth compared with control cells. In conclusion, our findings indicate that the crucial role of CUEDC1 in NSCLC progression and provide support for its clinical investigation for therapeutic approaches.

Objectives: Rheumatoid arthritis (RA) is the most common inflammatory arthritis in the world, but its underlying mechanism is still unclear. The present study aims to screen and verify the potential biomarkers of RA. Methods: We searched the Gene Expression Omnibus (GEO) database for synovial expression profiling from different RA microarray studies to perform a systematic analysis. Functional annotation of differentially expressed genes (DEGs) was conducted, including GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The protein–protein interaction (PPI) networks of the DEGs were constructed based on data from the STRING database. The expression levels of the hub genes in normal membranes and RA synovium were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot system. Results: A total of 444 differential expression genes were identified, including 172 up-regulated and 272 down-regulated genes in RA synovium compared with normal controls. The top ten hub genes; protein tyrosine phosphatase receptor type C (PTPRC), LCK proto-oncogene (LCK), cell division cycle 20 (CDC20), Jun proto-oncogene (JUN), cyclin-dependent kinase 1 (CDK1), kinesin family member 11 (KIF11), epidermal growth factor receptor (epidermal growth factor receptor (EGFR), vascular endothelial growth factor A (VEGFA), mitotic arrest deficient 2 like 1 (MAD2L1), and signal transducer and activator of transcription 1 (STAT1) were identified from the PPI network, and the expression level of VEGFA and EGFR was significantly increased in RA membranes (P<0.05). Conclusion: Our results indicate that the hub genes VEGFA and EGFR may have essential effects during the development of RA and can be used as potential biomarkers of RA.

Multiple gene polymorphisms have been demonstrated to correlate with the susceptibility to osteonecrosis of the femoral head (ONFH). However, as a complex disease induced by multiple genes, the development of ONFH has rarely been reported to involve in gene interaction. In this study, we first explored the association of 10 variants interactions in receptor activator of nuclear factor-kappa B (RANK), RANK ligand (RANKL), osteoprotegerin (OPG), tumor necrosis factor receptor-associated factor 6 (TRAF6), and nuclear factor of activated T cells cytoplasmic 1 (NFATC1) genes with the development and clinical phenotypes of ONFH in a 377 ONFH case–control study with using Mass ARRAY^® platform. Our results showed that not only a total of 6 interactional variants in the paired 10 variants interactions were significantly associated with the development of ONFH (OPG rs2073617 and NFATC1 rs754093, p < 0.019; OPG rs2073618 and NFATC1 rs754093, p < 0.008; OPG rs2073617 and RANKL rs1054016, p < 0.039, respectively) but also a total of 4 paired interactional variants were found to involve significantly in the increased risk of bilateral hip lesions in ONFH (OPG rs2073617 and TRAF6 rs5030411, p = 0.044; RANK rs884205 and TRAF6 rs5030411, p = 0.045, respectively). Moreover, the results from generalized multifactor dimensionality reduction also showed that the five best models were identified and associated significantly with ONFH risk, p = 0.001, 0.01, 0.01, 0.01, and 0.01, respectively. Our results first suggest that the variants in RANK/RANKL/OPG pathway genes affected the development of ONFH in gene interaction manner through the interaction of the paired variants and multiple variants.

Background. Osteoarthritis (OA) is the most common degenerative disease in orthopedics. However, the cause and underlying molecular mechanisms are not clear. This study aims to identify the hub genes and pathways involved in the occurrence of osteoarthritis. Methods. The raw data of GSE89408 were downloaded from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) were identified by R software. The DAVID database was used for pathway and gene ontology analysis, and p2 were set as the cut-off point. Moreover, protein-protein interaction (PPI) network construction was applied for exploring the hub genes in osteoarthritis. The expression levels of the top ten hub genes in knee osteoarthritis synovial membranes and controls were detected by quantitative real-time PCR system. Results. A total of 229 DEGs were identified in osteoarthritis synovial membranes compared with normal synovial membranes, including 145 upregulated and 84 downregulated differentially expressed genes. The KEGG pathway analysis results showed that up-DEGs were enriched in proteoglycans in cytokine-cytokine receptor interaction, chemokine signaling pathway, rheumatoid arthritis, and TNF signaling pathway, whereas down-DEGs were enriched in the PPAR signaling pathway and AMPK signaling pathway. The qRT-PCR results showed that the expression levels of ADIPOQ, IL6, and CXCR1 in the synovium of osteoarthritis were significantly increased (p <0.05).

Osteosarcoma (OS) is one of the most common primary malignant bone tumors in adolescents with a high mortality rate. MicroRNA (miRNA) is a kind of noncoding RNAs and has been proved to participate in many physiological processes. Many miRNAs have been reported to act as function regulators in OS. In our study, the miRNA and gene expression profiles of OS were downloaded from GEO Datasets and the differential expression analysis was performed using GEO2R. 58 up- and 126 downregulated miRNAs were found. In the three OS gene profiles, 125 up- and 27 downregulated genes were found to be differentially expressed in at least two profiles. The miRNA-mRNA networks were constructed to predict the potential target genes of 10 most up- and downregulated miRNA. Venn analysis was used to detect the coexpressed differentially expressed genes (DEGs). EBF2, one of the upregulated DEGs, was also a potential target gene of miR-182-3p. Knockdown and overexpression of miR-182-3p resulted in overexpression and downexpression of EBF2 separately. Luciferase reporter gene experiment further verified the binding site of miR-182-3p and EBF2. CCK8 assay showed that miR-182-3p knockdown can further enhance the proliferation activity of OS cells, while overexpressing miR-182-3p can inhibit the proliferation activity of OS cells. Our research indicated that downexpression of miR-182-3p in OS cells results in overexpression of EBF2 and promotes the progression of OS.