Molecular Mechanisms of Medicinal Plant Securinega Suffruticosa-derived Compound Securinine against Spinal Muscular Atrophy based on Network Pharmacology and Experimental Verification.

BACKGROUND: Spinal Muscular Atrophy (SMA) is a severe motor neuronal disorder with high morbidity and mortality. Securinine has shown the potential to treat SMA; however, its anti-SMA role remains unclear. OBJECTIVE: This study aims to reveal the anti-SMA mechanisms of securinine. METHODS: Securinine-associated targets were acquired from Herbal Ingredients' Targets (HIT), Similarity Ensemble Approach (SEA), and SuperPred. SMA-associated targets were obtained from GeneCards and Dis- GeNET. Protein-protein interaction (PPI) network was constructed using GeneMANIA, and hug targets were screened using cytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfifiler. Molecular docking was conducted using Pymol and Auto- Dock. In vitro assays were used to verify the anti-SMA effects of securinine. RESULTS: Twenty-six intersection targets of securinine and SMA were obtained. HDAC1, HDAC2, TOP2A, PIK3R1, PRMT5, JAK2, HSP90AB1, TERT, PTGS2, and PAX8 were the core targets in PPI network. GO analysis demonstrated that the intersecting targets were implicated in the regulation of proteins, steroid hormones, histone deacetylases, and DNA transcription. KEGG analysis, pathway-pathway, and hub target-pathway networks revealed that securinine might treat SMA through TNF, JAK-STAT, Ras, and PI3K-Akt pathways. Securinine had a favorable binding affinity with HDAC1, HSP90AB, JAK2, PRMT5, PTGS2, and TERT. Securinine rescued viability suppression, mitochondria damage, and SMN loss in the SMA cell model. Furthermore, securinine increased HDAC1 and PRMT5 expression, decreased PTGS2 expression, suppressed the JAK2-STAT3 pathway, and promoted the PI3K-Akt pathway. CONCLUSION: Securinine might alleviate SMA by elevating HDAC1 and PRMT5 expression and reducing PTGS2 via JAK2-STAT3 suppression and PI3K-Akt activation.

Effects of toxin metalloproteinases from jellyfish Nemopilema nomurai nematocyst on the dermal toxicity and potential treatment of jellyfish dermatitis.

Jellyfish dermatitis is a common medical problem in many countries due to the jellyfish envenomation. However, there are no specific and targeted medications for their treatment. Here we investigated the possible therapeutic effects of metalloproteinase inhibitors on the dermal toxicity of Nemopilema nomurai nematocyst venom (NnNV), a giant venomous jellyfish from China, using the jellyfish dermatitis model, focusing on inflammatory effector molecules during jellyfish envenomation. Metalloproteinase may further stimulate inflammation by promoting oxidative stress in the organism and play key roles by activating MAPK and NF-κB, in the pathogenesis of jellyfish dermatitis. And the metalloproteinase inhibitors batimastat and EDTA disodium salt may treat the Jellyfish dermatitis by inhibiting the metalloproteinase activity in NnNV. These observations suggest that the metalloproteinase components of NnNV make a considerable contribution to dermal toxicity as the inflammation effect molecular, and metalloproteinase inhibitors can be regarded as novel therapeutic medicines in jellyfish envenomation. This study contributes to understanding the mechanism of jellyfish dermatitis and suggests new targets and ideas for the treatment of jellyfish envenomation.

Toxin metalloproteinases exert a dominant influence on pro-inflammatory response and anti-inflammatory regulation in jellyfish sting dermatitis.

Toxin metalloproteinases are the primary components responsible for various toxicities in jellyfish venom, and there is still no effective specific therapy for jellyfish stings. The comprehension of the pathogenic mechanisms underlying toxin metalloproteinases necessitates further refinement. In this study, we conducted a differential analysis of a dermatitis mouse model induced by jellyfish Nemopilema nomurai venom (NnNV) samples with varying levels of metalloproteinase activity. Through skin tissue proteomics and serum metabolomics, the predominant influence of toxin metalloproteinase activity on inflammatory response was revealed, and the signal pathway involved in its regulation was identified. In skin tissues, many membrane proteins were significantly down-regulated, which might cause tissue damage. The expression of pro-inflammatory factors was mainly regulated by PI3K-Akt signaling pathway. In serum, many fatty acid metabolites were significantly down-regulated, which might be the anti-inflammation feedback regulated by NF-κB p65 signaling pathway. These results reveal the dermatitis mechanism of toxin metalloproteinases and provide new therapeutic targets for further studies. SIGNIFICANCE: Omics is an important method to analyze the pathological mechanism and discover the key markers, which can reveal the pathological characteristics of jellyfish stings. Our research first analyzed the impact of toxin metalloproteinases on jellyfish sting dermatitis by skin proteomics and serum metabolomics. The present results suggest that inhibition of toxin metalloproteinases may be an effective treatment strategy, and provide new references for further jellyfish sting studies.

Fucoidan may treat jellyfish dermatitis by inhibiting the inflammatory effect of jellyfish venom.

Jellyfish dermatitis is a common medical problem caused by jellyfish stings. However, there are no targeted and effective medications for their treatment. Here, the biological activity of fucoidan for treatment of jellyfish dermatitis was investigated for the first time. 3 mg/mL Fucoidan attenuated the inflammatory effects of Nemopilema nomurai nematocyst venom (NnNV), including dermal toxicity and myotoxicity. Fucoidan may decrease the inflammatory effects of NnNV by downregulating MAPK and NF-κB pathways. This may be attributed to the inhibitory effect of fucoidan on metalloproteinases and phospholipase A2 (PLA2) in NnNV. 3 mg/mL fucoidan reduced the metalloproteinase activity in NnNV from 316.33 ± 20.84 U/mg to 177.33 ± 25.36 U/mg, while the inhibition of PLA2 activity in NnNV by 1 mg/mL fucoidan could reach 37.67 ± 3.42 %. Besides, external application of 3 mg/mL fucoidan can effectively alleviate the symptoms of jellyfish dermatitis. These observations suggest that fucoidan has considerable potential for treatment of jellyfish dermatitis and could be regarded as a novel medicine for jellyfish envenomation. This study provides new ideas for treatment of jellyfish envenomation and suggests evidence for the use of fucoidan in the treatment of jellyfish dermatitis as well as broadens the potential application of fucoidan in clinical practice.

Screening for Mild Cognitive Impairment with Speech Interaction Based on Virtual Reality and Wearable Devices.

Significant advances in sensor technology and virtual reality (VR) offer new possibilities for early and effective detection of mild cognitive impairment (MCI), and this wealth of data can improve the early detection and monitoring of patients. In this study, we proposed a non-invasive and effective MCI detection protocol based on electroencephalogram (EEG), speech, and digitized cognitive parameters. The EEG data, speech data, and digitized cognitive parameters of 86 participants (44 MCI patients and 42 healthy individuals) were monitored using a wearable EEG device and a VR device during the resting state and task (the VR-based language task we designed). Regarding the features selected under different modality combinations for all language tasks, we performed leave-one-out cross-validation for them using four different classifiers. We then compared the classification performance under multimodal data fusion using features from a single language task, features from all tasks, and using a weighted voting strategy, respectively. The experimental results showed that the collaborative screening of multimodal data yielded the highest classification performance compared to single-modal features. Among them, the SVM classifier using the RBF kernel obtained the best classification results with an accuracy of 87%. The overall classification performance was further improved using a weighted voting strategy with an accuracy of 89.8%, indicating that our proposed method can tap into the cognitive changes of MCI patients. The MCI detection scheme based on EEG, speech, and digital cognitive parameters proposed in this study provides a new direction and support for effective MCI detection, and suggests that VR and wearable devices will be a promising direction for easy-to-perform and effective MCI detection, offering new possibilities for the exploration of VR technology in the field of language cognition.

Synergy through integration of digital cognitive tests and wearable devices for mild cognitive impairment screening.

Introduction: Advances in mobile computing platforms and the rapid development of wearable devices have made possible the continuous monitoring of patients with mild cognitive impairment (MCI) and their daily activities. Such rich data can reveal more subtle changes in patients' behavioral and physiological characteristics, providing new ways to detect MCI anytime, anywhere. Therefore, we aimed to investigate the feasibility and validity of digital cognitive tests and physiological sensors applied to MCI assessment. Methods: We collected photoplethysmography (PPG), electrodermal activity (EDA) and electroencephalogram (EEG) signals from 120 participants (61 MCI patients, 59 healthy controls) during rest and cognitive testing. The features extracted from these physiological signals involved the time domain, frequency domain, time-frequency domain and statistics. Time and score features during the cognitive test are automatically recorded by the system. In addition, selected features of all modalities were classified by tenfold cross-validation using five different classifiers. Results: The experimental results showed that the weighted soft voting strategy combining five classifiers achieved the highest classification accuracy (88.9%), precision (89.9%), recall (88.2%), and F1 score (89.0%). Compared to healthy controls, the MCI group typically took longer to recall, draw, and drag. Moreover, during cognitive testing, MCI patients showed lower heart rate variability, higher electrodermal activity values, and stronger brain activity in the alpha and beta bands. Discussion: It was found that patients' classification performance improved when combining features from multiple modalities compared to using only tablet parameters or physiological features, indicating that our scheme could reveal MCI-related discriminative information. Furthermore, the best classification results on the digital span test across all tasks suggest that MCI patients may have deficits in attention and short-term memory that came to the fore earlier. Finally, integrating tablet cognitive tests and wearable sensors would provide a new direction for creating an easy-to-use and at-home self-check MCI screening tool.

Prognostic and immune implications of a novel 7-methylguanosine-related microRNA signature in breast invasive carcinoma: from exploration to validation.

OBJECTIVES: This study aims to develop and validate a prognostic signature based on 7-methylguanosine-related (M7G-related) miRNAs for predicting prognosis and immune implications in breast invasive carcinoma (BRCA). MATERIALS AND METHODS: M7G-related miRNA data of BRCA were obtained from The Cancer Genome Atlas (TCGA). Least absolute shrinkage and selection operator (LASSO)-penalized, univariate, and multivariate Cox regression analyses were used to construct the prognostic signature. Furthermore, the predictive validity was verified using Kaplan-Meier (KM) survival risk and receiver operating characteristic (ROC) plots. Internal random sampling verification was used to simplify and validate the signature. RT-qPCR was used to quantify the expression level of transcriptional profiles. The independent prognostic role of the risk score was validated using univariate and multivariate regression. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used for functional and immune enrichment analysis. RESULTS: A total of 18 M7G-related miRNAs were identified to construct the prognostic signature in BRCA. The low-risk group exhibited significantly higher overall survival than the high-risk group in the KM survival plot (P < 0.001). The area under the curve (AUC) for 1-, 3-, and 5-year survivals in the ROC curve were 0.737, 0.724, and 0.702, respectively. The survival significance in the training and testing cohorts was confirmed by random sampling verification. The most prominent miRNAs in the signature were the miR-7, miR-139, miR-10b, and miR-4728. Furthermore, immune scores for B, mast, and Th1 cells varied between risk groups. Our research demonstrated that CD52 was the most positively correlated gene with immune cells and functions in BRCA. CONCLUSION: Our study presents a comprehensive and systematic analysis of M7G-related miRNAs to construct a prognostic signature in BRCA. The signature demonstrated excellent prognostic validity, with the risk score as an independent prognostic factor. These results provide critical evidence for further investigation of M7G miRNAs and offer new insights for BRCA patients in the context of effective immunotherapy.

CD24-associated ceRNA network reveals prognostic biomarkers in breast carcinoma.

Breast cancer is one of the most common cancer types which is described as the leading cause of cancer death in women. After competitive endogenous RNA (ceRNA) hypothesis was proposed, this triple regulatory network has been observed in various cancers, and increasing evidences reveal that ceRNA network plays a significant role in the migration, invasion, proliferation of cancer cells. In the current study, our target is to construct a CD24-associated ceRNA network, and to further identify key prognostic biomarkers in breast cancer. Using the transcriptom profiles from TCGA database, we performed a comprehensive analysis between CD24high tumor samples and CD24low tumor samples, and identified 132 DElncRNAs, 602 DEmRNAs and 26 DEmiRNAs. Through comprehensive analysis, RP1-228H13.5/miR-135a-5p/BEND3 and SIM2 were identified as key CD24-associated biomarkers, which exhibited highly significance with overall survival, immune microenvironment as well as clinical features. To sum up the above, the current study constructed a CD24-associated ceRNA network, and RP1-228H13.5/miR-135a-5p/BEND3 and SIM2 axis worked as a potential therapeutic target and a predictor for BRCA diagnosis and prognosis.

Identification and characterization of the key lethal toxin from jellyfish Cyanea nozakii.

Jellyfish Cyanea nozakii venom is a complex mixture of various toxins, most of which are proteinous biological macromolecules and are considered to be responsible for clinical symptoms or even death after a severe sting. Previous transcriptome and proteome analysis identified hundreds of toxins in the venom, including hemolysins, C-type lectin, phospholipase A2, potassium channel inhibitor, metalloprotease, etc. However, it is not clear which toxin in the venom plays the most important role in lethality. Herein, we isolated the key lethal toxin (Letoxcn) from jellyfish Cyanea nozakii using anion exchange chromatography, size-exclusion chromatography, and cation exchange chromatography. The molecular weight of Letoxcn is ∼50 kDa with the N-terminal sequences of QADAEKVNLPVGVCV. Peptide mass fingerprinting analysis of Letoxcn shows that it may have some motifs of phospholipase, metalloproteinase, thrombin-like enzyme, potassium channel toxin, etc. However, only metalloproteinase activity but no hemolytic, PLA2, or blood coagulation activity was observed from in vitro toxicity analysis. Overall, this study uncovered and characterized the key lethal toxin in the venom of jellyfish Cyanea nozakii, which will not only help to reveal the molecule mechanism of the lethality, but also develop effective treatment like antivenom for this jellyfish sting in the future.

Classification of mild cognitive impairment based on handwriting dynamics and qEEG.

Subtle changes in fine motor control and quantitative electroencephalography (qEEG) in patients with mild cognitive impairment (MCI) are important in screening for early dementia in primary care populations. In this study, an automated, non-invasive and rapid detection protocol for mild cognitive impairment based on handwriting kinetics and quantitative EEG analysis was proposed, and a classification model based on a dual fusion of feature and decision layers was designed for clinical decision-marking. Seventy-nine volunteers (39 healthy elderly controls and 40 patients with mild cognitive impairment) were recruited for this study, and the handwritten data and the EEG signals were performed using a tablet and MUSE under four designed handwriting tasks. Sixty-eight features were extracted from the EEG and handwriting parameters of each test. Features selected from both models were fused using a late feature fusion strategy with a weighted voting strategy for decision making, and classification accuracy was compared using three different classifiers under handwritten features, EEG features and fused features respectively. The results show that the dual fusion model can further improve the classification accuracy, with the highest classification accuracy for the combined features and the best classification result of 96.3% using SVM with RBF kernel as the base classifier. In addition, this not only supports the greater significance of multimodal data for differentiating MCI, but also tests the feasibility of using the portable EEG headband as a measure of EEG in patients with cognitive impairment.

LncRNA XIST from the bone marrow mesenchymal stem cell derived exosome promotes osteosarcoma growth and metastasis through miR-655/ACLY signal.

BACKGROUND: Long non-coding RNA X-inactive specific transcript (XIST) regulates the progression of a variety of tumors, including osteosarcoma. Bone marrow mesenchymal stem cells (BMSCs) can be recruited into osteosarcoma tissue and affect the progression by secreting exosomes. However, whether BMSCs derived exosomes transmit XIST to regulate the growth and metastasis of osteosarcoma and the related mechanism are still unclear. METHOD: In this study, BMSCs derived exosomes were used to treat human osteosarcoma cells MG63 and 143B, and the level of XIST in BMSCs was intervened by siRNA. CCK-8, EdU, transwell assays were used to analyze the changes of cell proliferation, migration and invasion. Bioinformatics analysis, RNA pulldown and dual-luciferase reporter gene assays validated the targeted relationship of XIST with miR-655 and the interaction between miR-655 and ACLY 3'-UTR. 143B/LUC cell line was used to establish an animal model of in situ osteosarcoma to verify the found effects of XIST on osteosarcoma. Oil Red O staining, Western blot and so on were used to detect the changes of lipid deposition and protein expression. RESULTS: It was found that BMSCs derived exosomes promoted the proliferation, migration and invasion of osteosarcoma cells, and the down-regulation of XIST inhibited this effect. miR-655 mediated the role of BMSCs derived exosomal XIST in promoting the progression of osteosarcoma and down-regulation of miR-655 could reverse the effects of inhibiting XIST on the proliferation, migration and invasion of osteosarcoma cells. Meanwhile, animal level results confirmed that BMSCs derived exosomal XIST could promote osteosarcoma growth and lung metastasis by combining with miR-655. In-depth mechanism study showed that BMSCs derived exosomal XIST combined with miR-655 to increase the protein level of ACLY, which led to lipid deposition and activate ß-catenin signal to promote the proliferation, migration and invasion of osteosarcoma cells. CONCLUSION: This study showed that BMSCs derived exosomal XIST could enter osteosarcoma cells, bind and down-regulates the level of miR-655, resulting in an increase in the level of ACLY, thus increasing the lipid deposition and the activity of ß-catenin signal to promote the growth and metastasis of osteosarcoma.

Comprehensive analysis of GINS subunits prognostic value and ceRNA network in sarcoma.

Background: The GINS complex, composed of GINS1/2/3/4 subunits, is an essential structure of Cdc45-MCM-GINS (CMG) helicase and plays a vital role in establishing the DNA replication fork and chromosome replication. Meanwhile, GINS genes have been associated with the poor prognosis of various malignancies. However, the abnormal expression of GINS genes and their diagnostic and prognostic value in sarcomas (SARC) remain unclear. Methods: Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, Cancer cell line encyclopedia (CCLE), The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), R studio, and Tumor Immune Estimation Resource (TIMER) were used to analyze the expression profiles, prognostic value, biological function, ceRNA, and immune infiltration associated with GINS genes in sarcomas. Results: We found that GINS1/2/3/4 genes exhibited significantly upregulated transcription levels in SARC samples compared to non-tumor tissues and exhibited high expression levels in sarcoma cell lines. In addition, SARC patients with increased expression levels of GINS1/2/3/4 showed poorer survival rates. Immune infiltration analysis showed that GINS subunits were closely associated with the infiltration of immune cells in sarcomas. Conclusion: Our research identified GINS subunits as potential diagnostic and prognostic biological targets in SARC and elucidated their underlying effects in the genesis and progression of SARC. These results may provide new opportunities and research directions for targeted sarcoma therapy.

Characterization of the immune cell infiltration landscape in myxofibrosarcoma to aid immunotherapy.

Myxofibrosarcoma (MFS) is a highly malignant subtype of soft tissue sarcoma, accounting for 5% of cases. Immunotherapy guided by immune cell infiltration (ICI) is reportedly a promising treatment strategy. Here, MFS samples (n = 104) from two independent databases were classified as ICI clusters A/B/C and gene clusters A/B/C. Then, a close relationship between ICI and gene clusters was established. We found that the features of these clusters were consistent with the characteristics of immune-inflamed tumors (cluster C), immune-desert tumors (cluster B), and immune-excluded tumors (cluster A). Moreover, cluster C was sensitive to immunotherapy. Finally, an independent ICI score was established to predict the therapeutic effect, which has prospects for application in guiding immunotherapy during clinical practice.

Jellyfish Nemopilema nomurai causes myotoxicity through the metalloprotease component of venom.

Jellyfish envenomation is a common medical problem in many countries. However, the myotoxicity and effector molecules of scyphozoan venoms remain uninvestigated. Here, we present the myotoxicity of nematocyst venom from Nemopilema nomurai (NnNV), a giant venomous scyphozoan from China, for the first time, using in vivo models with inhibitors. NnNV was able to induce remarkable myotoxicity including significant muscle swelling, increasing the content of CK and LDH in serum, stimulating inflammation of muscle tissue, and destroying the structure of muscle tissue. In addition, the metalloproteinase inhibitors BMT and EDTA significantly reduced the myotoxicity induced by NnNV. Moreover, BMT and EDTA could decrease the inflammatory stimulation and necrosis of muscle tissue caused by the venom. These observations suggest that the metalloproteinase components of NnNV make a considerable contribution to myotoxicity. This study contributes to understanding the effector molecules of muscle injury caused by jellyfish stings and suggests a new idea for the treatment of scyphozoan envenomation.

Network Pharmacology and Molecular Docking to Elucidate the Potential Mechanism of Ligusticum Chuanxiong Against Osteoarthritis.

Background: Osteoarthritis (OA) is a degenerative disease which serious affects patients. Ligusticum chuanxiong (CX) has been shown to have a certain curative effect on osteoarthritis in traditional Chinese medicine therapy. This study is based on network pharmacology and molecular docking technology to explore the potential mechanism of CX. Methods: Components of CX to treat osteoarthritis were screened in the TCMSP database and targets were predicted by the PharmMapper database, the osteoarthritis targets were collected from the GeneCards database, and intersection genes were found to be the possible targets of CX anti-OA. The STRING database and Cytoscape software were utilized for protein-protein interaction analysis and further screening of core targets. The Metascape database was used for KEGG and GO enrichment analyses. Then, the top 10 pathways were selected to construct "drug-compound-target-pathway-disease" network analysis. Finally, molecular docking was used to analyze the binding affinity of seven compounds with core targets and TNF-α. Results: Seven compounds with 253 non-repetitive targets of CX were screened from the TCMSP database and 60 potential intersection targets of CX anti-OA were found. PPI network analysis showed that the core targets were ALB, AKT1, IGF1, CASP3, MAPK1, ANXA5, and MAPK14, while GO and KEGG pathway enrichment analyses showed that the relevant biological processes involved in the treatment of osteoarthritis by CX might include the MAPK cascade and reactive oxygen species metabolic process. The KEGG pathway analysis result was mainly associated with the MAPK signaling pathway and PI3K-AKT signaling pathway. We further docked seven ingredients with MAPK1 and MAPK14 enriched in the MAPK pathway, and TNF-α as the typical inflammatory cytokine. The results also showed good binding affinity, especially FA, which may be the most important component of CX anti-OA. Conclusion: Our research revealed the potential mechanism of CX in the treatment of OA, and our findings can also pave the way for subsequent basic experimental verification and a new research direction.

Refinement and Neutralization Evaluation of the F(ab')2 Type of Antivenom against the Deadly Jellyfish Nemopilema nomurai Toxins.

Jellyfish stings threaten people's health and even life in coastal areas worldwide. Nemopilema nomurai is one of the most dangerous jellyfish in the East Asian Marginal Seas, which not only stings hundreds of thousands of people every year but also is assumed to be responsible for most deaths by jellyfish stings in China. However, there is no effective first-aid drug, such as antivenoms, for the treatment of severe stings by N. nomurai to date. In this study, we prepared a N. nomurai antiserum from rabbits using inactivated N. nomurai toxins (NnTXs) and isolated the IgG type of antivenom (IgG-AntiNnTXs) from the antiserum. Subsequently, IgG-AntiNnTXs were refined with multiple optimizations to remove Fc fragments. Finally, the F(ab')2 type of antivenom (F(ab')2-AntiNnTXs) was purified using Superdex 200 and protein A columns. The neutralization efficacy of both types of antivenom was analyzed in vitro and in vivo, and the results showed that both IgG and F(ab')2 types of antivenom have some neutralization effect on the metalloproteinase activity of NnTXs in vitro and could also decrease the mortality of mice in the first 4 h after injection. This study provides some useful information for the development of an effective antivenom for N. nomurai stings in the future.

The miR-4739/DLX3 Axis Modulates Bone Marrow-Derived Mesenchymal Stem Cell (BMSC) Osteogenesis Affecting Osteoporosis Progression.

Osteoporosis is a complex multifactorial disorder linked to various risk factors and medical conditions. Bone marrow-derived mesenchymal stem cell (BMSC) dysfunction potentially plays a critical role in osteoporosis pathogenesis. Herein, the study identified that miR-4739 was upregulated in BMSC cultures harvested from osteoporotic subjects. BMSCs were isolated from normal and osteoporotic bone marrow tissues and identified for their osteogenic differentiation potential. In osteoporotic BMSCs, miR-4739 overexpression significantly inhibited cell viability, osteoblast differentiation, mineralized nodule formation, and heterotopic bone formation, whereas miR-4739 inhibition exerted opposite effects. Through direct binding, miR-4739 inhibited distal-less homeobox 3 (DLX3) expression. In osteoporotic BMSCs, DLX3 knockdown also inhibited BMSC viability and osteogenic differentiation. Moreover, DLX3 knockdown partially attenuated the effects of miR-4739 inhibition upon BMSCs. Altogether, the miR-4739/DLX3 axis modulates the capacity of BMSCs to differentiate into osteoblasts, which potentially plays a role in osteoporosis pathogenesis. The in vivo and clinical functions of the miR-4739/DLX3 axis require further investigation.

A Novel Overall Survival Prediction Signature Based on Cancer Stem Cell-Related Genes in Osteosarcoma.

Background: Osteosarcoma is the most general bone malignancy that mostly affects children and adolescents. Numerous stem cell-related genes have been founded in distinct forms of cancer. This study aimed at identifying a stem cell-related gene model for the expected assessment of the prognosis of osteosarcoma patients. Methods: We obtained the genes expression data and relevant clinical materials from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We identified differentially expressed genes (DEGs) from the GEO dataset, whereas prognostic stem cell-related genes were obtained from the TARGET database. Subsequently, univariate, LASSO and multivariate Cox regression analyses were applied to establish the stem cell-related signature. Finally, the prognostic value of the signature was validated in the GEO dataset. Results: Twenty-five genes were prognostic ferroptosis-related DEGs. Consequently, we identified eight stem cell-related genes as a signature of prognosis of osteosarcoma patients. Then, the Kaplan-Meier (K-M) curve, the AUC value of ROC, and Cox regression analysis verified that the eight stem cell-related gene model were a new and substantial prognostic marker independent of other clinical traits. Moreover, the nomogram on the foundation of risk score and other clinical traits was established for predicting the survival rate of osteosarcoma patients. Biological function analyses displayed that tumor related pathways were affluent. Conclusion: The expression level of stem cell-related genes offers novel prognostic markers as well as underlying therapeutic targets for the therapy and prevention of osteosarcoma.

Identification and validation of immune-related lncRNA prognostic signatures for melanoma.

INTRODUCTION: Melanoma is a highly aggressive malignant skin tumor as well as the primary reason for skin cancer-specific deaths. We first identified immune-related long noncoding RNA (lncRNA) prognostic signature and found potential immunotherapeutic targets for melanoma cancer. METHODS: RNA-seq data and clinical features of melanoma samples were obtained from The Cancer Genome Atlas. Samples of melanoma were randomly assigned to the training and testing cohort. The immune-related lncRNA signature was then obtained via using univariate, LASSO, and multivariate Cox analysis of patients in the training cohort. Eight significant immune-related lncRNA signature was then subsequently obtained through correlation analysis between immune-related genes and lncRNAs. The association between risk score and immune cell infiltration was finally assessed using TIMER and CIBERSORT. RESULTS: Three hundred and fifty-six immune-related lncRNAs were obtained. Among them, eight immune-related lncRNAs were identified to build a prognostic risk signature model. The model's performance was then confirmed using the Kaplan-Meier curves, risk plots, and time-dependent receiver-operating characteristic curves in the training cohort. The risk score was identified and confirmed as an independent prognostic factor through univariate and multivariate Cox regression analyses. These results were further verified in the testing and whole cohorts. CIBERSORT algorithm showed that the infiltration levels of T cells CD8, M1 macrophages, plasma cells, T cells CD4 memory activated, T cells gamma delta, and mast cells activated were significantly lower in the high-risk group while the infiltration level of macrophages M0 was significantly lower in the low-risk group. CONCLUSION: The immune-related lncRNA signature offers prognostic markers and potential immunotherapeutic targets for melanoma.

Identification of Epithelial-Mesenchymal Transition-Related Prognostic lncRNAs Biomarkers Associated With Melanoma Microenvironment.

Melanoma is the most common cancer of the skin, associated with a worse prognosis and distant metastasis. Epithelial-mesenchymal transition (EMT) is a reversible cellular biological process that plays significant roles in diverse tumor functions, and it is modulated by specific genes and transcription factors. The relevance of EMT-related lncRNAs in melanoma has not been determined. Therefore, RNA expression data and clinical features were collected from the TCGA database (N = 447). Melanoma samples were randomly assigned into the training (315) and testing sets (132). An EMT-related lncRNA signature was constructed via comprehensive analyses of lncRNA expression level and corresponding clinical data. The Kaplan-Meier analysis showed significant differences in overall survival in patients with melanoma in the low and high-risk groups in two sets. Receiver operating characteristic (ROC) curves were used to measure the performance of the model. Cox regression analysis indicated that the risk score was an independent prognostic factor in two sets. Besides, a nomogram was constructed based on the independent variables. Gene Set Enrichment Analysis (GSEA) was applied to evaluate the potential biological functions in the two risk groups. Furthermore, the melanoma microenvironment was evaluated using ESTIMATE and CIBERSORT algorithms in the risk groups. This study indicates that EMT-related lncRNAs can function as potential independent prognostic biomarkers for melanoma survival.