Metastasis In Osteosarcoma Patients Research Articles

Targeting nerve growth factor-mediated osteosarcoma metastasis: mechanistic insights and therapeutic opportunities using larotrectinib

Osteosarcoma (OS) therapy presents numerous challenges, due largely to a low survival rate following metastasis onset. Nerve growth factor (NGF) has been implicated in the metastasis and progression of various cancers; however, the mechanism by which NGF promotes metastasis in osteosarcoma has yet to be elucidated. This study investigated the influence of NGF on the migration and metastasis of osteosarcoma patients (88 cases) as well as the underlying molecular mechanisms, based on RNA-sequencing and gene expression data from a public database (TARGET-OS). In osteosarcoma patients, the expression of NGF was significantly higher than that of other growth factors. This observation was confirmed in bone tissue arrays from 91 osteosarcoma patients, in which the expression levels of NGF and matrix metallopeptidase-2 (MMP-2) protein were significantly higher than in normal bone, and strongly correlated with tumor stage. In summary, NGF is positively correlated with MMP-2 in human osteosarcoma tissue and NGF promotes osteosarcoma cell metastasis by upregulating MMP-2 expression. In cellular experiments using human osteosarcoma cells (143B and MG63), NGF upregulated MMP-2 expression and promoted wound healing, cell migration, and cell invasion. Pre-treatment with MEK and ERK inhibitors or siRNA attenuated the effects of NGF on cell migration and invasion. Stimulation with NGF was shown to promote phosphorylation along the MEK/ERK signaling pathway and decrease the expression of microRNA-92a-1-5p (miR-92a-1-5p). In in vivo experiments involving an orthotopic mouse model, the overexpression of NGF enhanced the effects of NGF on lung metastasis. Note that larotrectinib (a tropomyosin kinase receptor) strongly inhibited the effect of NGF on lung metastasis. In conclusion, it appears that NGF promotes MMP-2-dependent cell migration by inhibiting the effects of miR-92a-1-5p via the MEK/ERK signaling cascade. Larotrectinib emerged as a potential drug for the treatment of NGF-mediated metastasis in osteosarcoma.

The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients

Host immune dysregulation involves in the initiation and development of osteosarcoma (OS). However, the exact role of immune cells in OS remains unknown. We aimed to distinguish the molecular subtypes and establish a prognostic model in OS patients based on immunocyte infiltration. The gene expression profile and corresponding clinical feature of OS patients were obtained from TARGET and GSE21257 datasets. MCP-counter and univariate Cox regression analyses were applied to identify immune cell infiltration-related molecular subgroups. Functional enrichment analysis and immunocyte infiltration analysis were performed between two subgroups. Furthermore, Cox regression and LASSO analyses were performed to establish the prognostic model for the prediction of prognosis and metastasis in OS patients. The subgroup with low infiltration of monocytic lineage (ML) was related to bad prognosis in OS patients. 435 DEGs were screened between the two subgroups. Functional enrichment analysis revealed these DEGs were involved in immune- and inflammation-related pathways. Three important genes (including TERT, CCDC26, and IL2RA) were identified to establish the prognostic model. The risk model had good prognostic performance for the prediction of metastasis and overall survival in OS patients. A novel stratification system was established based on ML-related signature. The risk model could predict the metastasis and prognosis in OS patients. Our findings offered a novel sight for the prognosis and development of OS.

Chemokine Ligand 2 Promotes Migration in Osteosarcoma by Regulating the miR-3659/MMP-3 Axis.

Osteosarcoma is a common malignant tumor in children and adolescents, known for its aggressive invasion and distant metastasis, leading to a poor prognosis. Matrix metalloproteinases (MMPs) can degrade the extracellular matrix and basement membranes through their proteolytic activity, thereby promoting osteosarcoma metastasis. Chemokine ligand 2 (CCL2) is a well-studied chemokine that plays a significant role in the cell motility of many cancers. However, its specific involvement in osteosarcoma metastasis is not fully understood. The aim of this study is to examine the role of miRNAs in CCL2-mediated MMP expression and cell motility in human osteosarcoma. The analysis of immunohistochemistry data and databases associated a positive correlation between CCL2 or MMP-3 levels with the metastasis of osteosarcoma patients. The in vivo lung metastatic osteosarcoma model also demonstrated similar effects, showing higher levels of CCL2 and MMP-3 in lung metastatic osteosarcoma tissues. The stimulation of osteosarcoma cells with CCL2 enhanced migration and invasion abilities through the upregulation of MMP-3 synthesis. Our results also indicate that CCL2 enhances MMP-3-dependent cell motility by inhibiting miR-3659 synthesis. Therefore, CCL2 represents a promising therapeutic target for treating metastasis in osteosarcoma.

DPY30 promotes the growth and survival of osteosarcoma cell by regulating the PI3K/AKT signal pathway

Osteosarcoma (OS) is characterized by aggressive features including invasiveness and high incidence of metastasis. OS patients with metastases are difficult to treat and suffer from a poor prognosis. DPY30 (protein dpy-30 homolog) is a key component of SET1/MLL family of H3K4 methyltransferases, which is implicated in the progression of multiple cancers. However, the potential functional engagement of DPY30 in OS remains to be unveiled. The objective of this study is to investigate the potential roles of DPY30 in the regulation of malignant phenotypes of OS cells. We examined DPY30 expression from a published dataset (GSE28424) as well as in OS tissues and adjacent normal tissues from OS patients. The association of DPY30 expression level and clinicopathologic parameters was assessed by Chi-square test. The role of DPY30 in regulating the malignant phenotype of OS cells and tumorigenesis was examined by in vitro functional assays and xenograft mouse model. We reported an upregulation of DPY30 in OS tumor tissues in both published dataset and clinical samples. A high level of DPY30 expression was associated with larger tumor size and more metastasis in OS patients, as well as poor overall survival. DPY30 knockdown in OS cells significantly impairs proliferation, migration and invasion, but induced cellular apoptosis. We further demonstrated that the agonist of PI3K/AKT pathway can rescue the inhibitory effects of DPY30 knockdown in OS cells. Together, our data indicate that DPY30 functions as an oncogene to promote the malignancy of OS cells possibly through PI3K/AKT pathway. The dependency of OS cells on DPY30 overexpression is a targetable vulnerability in OS cells.

The hexosamine biosynthesis pathway-related gene signature correlates with immune infiltration and predicts prognosis of patients with osteosarcoma.

ObjectivesOsteosarcoma is a malignant bone tumor with poor outcomes affecting the adolescents and elderly. In this study, we comprehensively assessed the metabolic characteristics of osteosarcoma patients and constructed a hexosamine biosynthesis pathway (HBP)-based risk score model to predict the prognosis and tumor immune infiltration in patients with osteosarcoma.MethodsGene expression matrices of osteosarcoma were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. GSVA and univariate Cox regression analysis were performed to screen the metabolic features associated with prognoses. LASSO regression analysis was conducted to construct the metabolism-related risk model. Differentially expressed genes (DEGs) were identified and enrichment analysis was performed based on the risk model. CIBERSORT and ESTIMATE algorithms were executed to evaluate the characteristics of tumor immune infiltration. Comparative analyses for immune checkpoints were performed and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict immunotherapeutic response. Finally, hub genes with good prognostic value were comprehensive analyzed including drug sensitivity screening and immunohistochemistry (IHC) experiments.ResultsThrough GSVA and survival analysis, the HBP pathway was identified as the significant prognostic related metabolism feature. Five genes in the HBP pathway including GPI, PGM3, UAP1, OGT and MGEA5 were used to construct the HBP-related risk model. Subsequent DEGs and enrichment analyses showed a strong correlation with immunity. Further, CIBERSORT and ESTIMATE algorithms showed differential immune infiltration characteristics correlated with the HBP-related risk model. TIDE algorithms and immune checkpoint analyses suggested poor immunotherapeutic responses with low expression of immune checkpoints in the high-risk group. Further analysis revealed that the UAP1 gene can predict metastasis. IHC experiments suggested that UAP1 expression correlated significantly with the prognosis and metastasis of osteosarcoma patients. When screening for drug sensitivity, high UAP1 expression was suggestive of great sensitivity to antineoplastic drugs including cobimetinib and selumetinib.ConclusionWe constructed an HBP-related gene signature containing five key genes (GPI, PGM3, UAP1, OGT, MGEA5) which showed a remarkable prognostic value for predicting prognosis and can guide immunotherapy and targeted therapy for osteosarcoma.

Application of interpretable machine learning algorithms to predict distant metastasis in osteosarcoma.

Osteosarcoma is well-established as the most common bone cancer in children and adolescents. Patients with localized disease have different prognoses and management than those with metastasis at the time of diagnosis. The purpose of this study was to explore potential risk factors for metastatic disease. The Surveillance, Epidemiology, and End Results (SEER) Program database was used to identify patients diagnosed with osteosarcoma between 2004 and 2015. We developed prediction models for distant metastasis using six machine learning (ML) techniques, including logistic regression (LR), support vector machine (SVM), Gaussian Naive Bayes (GaussianNB), Extreme Gradient Boosting (XGBoost), random forest (RF), and k-nearest neighbor algorithm (kNN). The adaptive synthetic (ADASYN) technique was used to deal with imbalanced data. The Shapley Additive Explanation (SHAP) analysis generated visualized explanations for each patient. Finally, the average precision (AP), sensitivity, specificity, accuracy, F1 score, precision-recall curves, calibration plots, and decision curve analysis (DCA) were conducted to evaluate the models' effectiveness. The six machine learning algorithms achieved AP of 0.661-0.781 for predicting distant metastasis. The RF model yielded the best performance with an accuracy of 71.8 percent and an AP of 0.781 and was highly dependent on tumor size, primary surgery, and age. SHAP analysis provided model-independent interpretation, highlighting significant clinical factors associated with the risk of metastasis in osteosarcoma patients. An accurate machine learning-based prediction model was established for metastasis in osteosarcoma patients to help clinicians during clinical decision-making.

Nectin-4 promotes osteosarcoma progression and metastasis through activating PI3K/AKT/NF-κB signaling by down-regulation of miR-520c-3p

PurposeNectin-4 is specifically up-regulated in various tumors, exert crucial effects on tumor occurrence and development. Nevertheless, the role and molecular mechanism of Nectin-4 in osteosarcoma (OS) are rarely studied.MethodsThe expression of Nectin-4 and its relationship with clinical characteristics of OS were investigated using OS clinical tissues, tissue microarrays, TCGA, and GEO databases. Moreover, the effect of Nectin-4 on cell growth and mobility was detected by CCK-8, colony formation, transwell, and wound-healing assays. The RT-qPCR, Western blotting, and luciferase reporter assays were performed to explore molecular mechanisms through which Nectin-4 mediates the expression of miR-520c-3p, thus modulating PI3K/AKT/NF-κB signaling. In vivo mice models constructed by subcutaneous transplantation and tail vein injection were used to validate the functional roles of Nectin-4 and miR-520c-3p.ResultsNectin-4 displayed a higher expression in OS tumor tissues compared with normal tissues, and its overexpression was positively associated with tumor stage and metastasis in OS patients. Functionally, Nectin-4 enhanced OS cells growth and mobility in vitro. Mechanistically, Nectin-4 down-regulated the levels of miR-520c-3p that directly targeted AKT-1 and P65, thus leading to the stimulation of PI3K/AKT/NF-κB signaling. In addition, the expression of miR-520c-3p was apparently lower in OS tissues than in normal tissues, and its low expression was significantly related to tumor metastasis. Furthermore, ectopic expression of miR-520c-3p markedly blocked the effect of Nectin-4 on OS cell growth and mobility. Knockdown of Nectin-4 could suppress the tumorigenesis and metastasis in vivo, which could be remarkably reversed by miR-520c-3p silencing.ConclusionsNectin-4 as an oncogene can promote OS progression and metastasis by activating PI3K/AKT/NF-κB signaling via down-regulation of miR-520c-3p, which could represent a novel avenue for identifying a potential therapeutic target for improving patient outcomes.

Siglec-15-induced autophagy promotes invasion and metastasis of human osteosarcoma cells by activating the epithelial–mesenchymal transition and Beclin-1/ATG14 pathway

BackgroundPulmonary metastasis is the main cause of poor prognosis in osteosarcoma. Sialic acid-bound immunoglobulin lectin 15 (Siglec-15) has been demonstrated to be obviously correlated with pulmonary metastasis in osteosarcoma patients. However, the effect of Siglec-15 on autophagy in osteosarcoma remains unclear, while the role and mechanism of Siglec-15-related autophagy in lung metastasis also remain unknown.MethodsThe expression levels of Siglec-15 and Beclin-1 were detected in osteosarcoma tissues using immunohistochemistry (IHC). The effect of Siglec-15 on metastasis was investigated using Transwell, wound healing and animal experiments with osteosarcoma cells. Corresponding proteins were confirmed using Western blotting when Siglec-15 or Beclin-1 was silenced or overexpressed. Changes in autophagy and the cytoskeleton were detected using immunofluorescence and transmission electron microscopy.ResultsSiglec-15 and Beclin-1 expression was evaluated both in lung metastases and in patients who presented with pulmonary metastasis of osteosarcoma. Immunoprecipitation experiments revealed that Siglec-15 interacts directly with Beclin-1, an important autophagic protein. Moreover, loss of Siglec-15 distinctly inhibited autophagy and reduced Beclin-1/ATG14 expression. The decreased invasion and migration caused by Siglec-15 silencing could be reversed by Beclin-1 overexpression. Additionally, autophagy can promote the epithelial–mesenchymal transition (EMT) and affect cytoskeletal rearrangement, which was confirmed by overexpression or silencing of Beclin-1.ConclusionsThese findings confirmed the role of Siglec-15 in the regulation of autophagy and elaborated the relationship and mechanisms between autophagy and the metastasis of osteosarcoma cells.

Lung Immune Prognostic Index Could Predict Metastasis in Patients With Osteosarcoma.

BackgroundThe lung immune prognostic index (LIPI), composed of serum lactate dehydrogenase (LDH) and the derived neutrophil to lymphocyte ratio (dNLR), is a novel prognostic factor of lung cancer. The prognostic effect of the LIPI has never been verified in osteosarcoma.MethodsWe retrospectively reviewed the osteosarcoma patients with metachronous metastasis from January 2016 to January 2021 in West China Hospital. We collected and analyzed the clinical data and constructed the LIPI for osteosarcoma. The correlation between the LIPI and metastasis was analyzed according to the Kaplan–Meier method and Cox regression analysis with hazard ratios (HRs) and 95% confidence intervals (CIs). Univariate analysis and multivariate analysis were conducted to clarify the independent risk factors of metastasis. The nomogram model was established by R software, version 4.1.0.ResultsThe area under the curve (AUC) and best cutoff value were 0.535 and 91, 0.519, and 5.02, 0.594 and 2.77, 0.569 and 227.14, 0.59 and 158, and 0.607 and 2.05 for ALP, LMR, NLR, PLR, LDH, and dNLR, respectively. The LIPI was composed of LDH and dNLR and showed a larger AUC than other hematological factors in the time-dependent operator curve (t-ROC). In total, 184 patients, 42 (22.8%), 96 (52.2%), and 46 (25.0%) patients had LIPIs of good, moderate, and poor, respectively (P < 0.0001). Univariate analysis revealed that pathological fracture, the initial CT report of suspicious nodule, and the NLR, PLR, ALP, and the LIPI were significantly associated with metastasis, and multivariate analysis showed that the initial CT report of suspicious nodule and the PLR, ALP, and LIPI were dependent risk factors for metastasis. Metastatic predictive factors were selected and incorporated into the nomogram construction, including the LIPI, ALP, PLR, initial CT report, and pathological fracture. The C-index of our model was 0.71. According to the calibration plot, this predictive nomogram could accurately predict 3- and 5-year metachronous metastasis. Based on the result of decision curve and clinical impact curve, this predictive nomogram could also help patients obtain significant net benefits.ConclusionWe first demonstrated the metastatic predictive effect of the LIPI on osteosarcoma. This LIPI-based model is useful for clinicians to predict metastasis in osteosarcoma patients and could help conduct timely intervention and facilitate personalized management of osteosarcoma patients.

A Novel Predictive Model Associated with Osteosarcoma Metastasis.

PurposeLong non-coding RNAs (lncRNAs) have diverse roles in modulating gene expression on both transcriptional and translational levels, but their involvement in osteosarcoma (OS) metastasis remains unknown.Patients and MethodsTranscriptional and clinical data were downloaded from TARGET datasets. A total of seven lncRNAs screened by univariate cox regression, lasso regression, and multivariate cox regression analysis were used to establish the OS metastasis model. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model.ResultsThe established model showed exceptional predictive performance (1 year: AUC = 0.92, 95% Cl = 0.83–0.99; 3 years: AUC = 0.87, 95% Cl = 0.79–0.96; 5 years: AUC = 0.86, 95% Cl = 0.76–0.96). Patients in the high group had a poor survival outcome than those in the low group (p < 0.0001). GSEA analysis revealed that “NOTCH_SIGNALING” and “WNT_BETA_CATENIN_SIGNALING” were significantly enriched and that resting dendritic cells were associated with AL512422.1, AL357507.1, and AC006033.2 (p < 0.05).ConclusionBased on seven prognosis-related lncRNAs, we constructed a novel model with high reliability and accuracy for predicting metastasis in OS patients.

Chloroquine suppresses proliferation and invasion and induces apoptosis of osteosarcoma cells associated with inhibition of phosphorylation of STAT3.

Background: Osteosarcoma (OS) is characterized by a high rate of metastasis. It has been found that tumor cells can bypass apoptosis which leads to an uncontrolled proliferation, but chloroquine (CQ) can have an effect on the tumors by inducing apoptosis. We aimed to explore the effects and the hypothetical mechanism of CQ effects on OS.Methods: We first estimated the CQ effects on proliferation, apoptosis, migration, invasion, and lamellipodia formation of OS cells. Mice bearing xenograft model were used to test the anti-tumor growth and lung metastasis effects of CQ in OS. Western blot and immunohistochemistry were used to explore the mechanism of CQ effects and the association between p-STAT3 expression and lung metastasis of OS patients.Results: CQ induces the apoptosis and suppressed the viability, proliferation, migration, invasion, and lamellipodia formation of OS cells in vitro. In vivo experiments demonstrated that CQ inhibited tumor growth and lung metastasis. CQ induced apoptosis was dependent on the lysosomal inhibition and inhibition of protein turnover. The lung metastasis was associated with the p-STAT3 expression in OS patients.Conclusion: CQ inhibited progression of OS cells in vitro, and suppressed tumor growth and lung metastasis in vivo. p-STAT3 can be a predictive biomarker for lung metastasis in osteosarcoma patients.

Machine learning-based CT radiomics features for the prediction of pulmonary metastasis in osteosarcoma.

This study aims to build machine learning-based CT radiomic features to predict patients developing metastasis after osteosarcoma diagnosis. This retrospective study has included 81 patients with a histopathological diagnosis of osteosarcoma. The entire dataset was divided randomly into training (60%) and test sets (40%). A data augmentation technique for the minority class was performed in the training set, along with feature's selection and model's training. The radiomic features were extracted from CT's image of the local osteosarcoma. Three frequently used machine learning models tried to predict patients with lung metastases (MT) and those without lung metastases (non-MT). According to the higher area under the curve (AUC), the best classifier was chosen and applied in the testing set with unseen data to provide an unbiased evaluation of the final model. The best classifier for predicting MT and non-MT groups used a Random Forest algorithm. The AUC and accuracy results of the test set were bulky (accuracy of 73% [ 95% coefficient interval (CI): 54%; 87%] and AUC of 0.79 [95% CI: 0.62; 0.96]). Features that fitted the model (radiomics signature) derived from Laplacian of Gaussian and wavelet filters. Machine learning-based CT radiomics approach can provide a non-invasive method with a fair predictive accuracy of the risk of developing pulmonary metastasis in osteosarcoma patients. Models based on CT radiomic analysis help assess the risk of developing pulmonary metastases in patients with osteosarcoma, allowing further studies for those with a worse prognosis.

Patrolling monocytes inhibit osteosarcoma metastasis to the lung.

Immune infiltration is associated with osteosarcoma metastasis. However, previous studies have not accounted for the functional diversity of the cells involved in the immune response. We conducted a comprehensive comparative analysis of the tumor-infiltrating immune cells in metastatic and non-metastatic osteosarcoma tissues based on a deconvolution algorithm (CIBERSORT). Twenty-two immune cell subsets were evaluated for their association with the presence or absence of metastasis in osteosarcoma patients. A lack of monocytes was associated with osteosarcoma metastasis; however, the levels of M1 macrophages, M2 macrophages and other immune cell subsets did not differ between the metastatic and non-metastatic groups. Additionally, a higher proportion of monocytes was associated with a better prognosis in osteosarcoma patients. Animal experiments demonstrated that the number of metastatic nodules was higher in mice lacking patrolling monocytes than in control mice. Our data indicated that the cellular composition of the immune infiltrate may subtly differ among osteosarcoma patients, and that patrolling monocytes inhibit osteosarcoma metastasis to the lungs of mice. Thus, the composition of the immune infiltrate and the level of patrolling monocytes may be important determinants of whether metastasis occurs in osteosarcoma patients.

Decreased long non-coding RNA lincFOXF1 indicates poor progression and promotes cell migration and metastasis in osteosarcoma.

Long non‐coding RNAs have been demonstrated to be important regulators of various cancers, though the precise mechanisms remain unclear. Although lincFOXF1 has been reported to act as a tumour suppressor, its function and underlying mechanisms in osteosarcoma have not yet been explored. We employed quantitative real‐time polymerase chain reaction (qRT‐PCR) to evaluate the expression of lincFOXF1 and GAPDH in osteosarcoma tissues and cell lines, and colony‐formation, CCK8, wound‐healing, and transwell assays were conducted to analyse the proliferation, migration, and invasion capacity of osteosarcoma cells. Subcellular localization analysis by fractionation and RNA immunoprecipitation assays were performed to elucidate the mechanism responsible for lincFOXF1‐mediated phenotypes of osteosarcoma cells. The results revealed that lincFOXF1 expression is significantly decreased and strongly related to Enneking stage as well as metastasis in osteosarcoma patients. Further experiments showed that lincFOXF1 inhibits the migration, invasion and metastasis of cells in vitro and vivo. Mechanistic investigation demonstrated that lincFOXF1 physically binds to EZH2, a polycomb repressive complex 2 (PRC2) component, and a search for downstream targets suggested that G‐protein‐coupled receptor kinase‐interacting protein 1 (GIT1) is involved in the lincFOXF1‐mediated repression of osteosarcoma cells migration and invasion. Moreover, GIT1 expression is inversely correlated with lincFOXF1 in osteosarcoma. The present findings indicate that lincFOXF1 is involved in the progression of osteosarcoma through binding with EZH2, further regulating GIT1 expression. Our results suggest that lincFOXF1 may serve as a biomarker and therapeutic target for osteosarcoma patients.

URG4 mediates cell proliferation and cell cycle in osteosarcoma via GSK3\u03b2/\u03b2-catenin/cyclin D1 signaling pathway

BackgroundOsteosarcoma is one of the most common malignant bone tumors with the annual global incidence of approximately four per million. Upregulated gene 4 (URG4) expression in the osteosarcoma tissue is closely associated with recurrence, metastasis, and poor prognosis of osteosarcoma. However, the biological function and underlying mechanisms of URG4 in osteosarcoma have not been elucidated. This study aimed to explore the expression and underlying mechanism of URG4 in osteosarcoma.MethodsThe expression level of URG4 in osteosarcoma and normal tissues was compared using immunohistochemistry (IHC). PCR and western blotting (WB) techniques are used to detect URG4 mRNA and protein levels. Wound healing and Transwell analysis to assess the effect of URG4 on osteosarcoma cell migration and invasion. Cell Counting Kit-8 assay and colony proliferation assay were performed to evaluate the effects of silencing URG4 on the inhibition of cell proliferation. The cell cycle distribution was detected by flow cytometry, and a xenograft mouse model was used to verify the function of URG4 in vivo.ResultsURG4 was found to be highly expressed in osteosarcoma tissues and cells, and its high expression was correlated with advanced Enneking stage, large tumor size, and tumor metastasis in osteosarcoma patients. The proliferation in osteosarcoma cell lines and cell cycle in the S phase was suppressed when siRNA was used to downregulate URG4. URG4 promoted cell proliferation and tumorigenesis in vitro and in vivo. WB verified that URG4 promotes cell proliferation in osteosarcoma via pGSK3β/β-catenin/cyclinD1 signaling.ConclusionURG4, which is high-expressed in osteosarcoma, promotes cell cycle progression via GSK3β/β-catenin/cyclin D1 signaling pathway and may be a novel biomarker and potential target for the treatment of osteosarcoma.

Correlation of Serum Alkaline Phosphatase, Lactate Dehydrogenase, C-Reactive Protein, Blood Deposition Rate, ?-Hcg Expression and Tumor Volume to Lung Metastasis Risk in Osteosarcoma Patients

Osteosarcoma is the most common type of sarcoma that found in bone. The survival rate in osteosarcoma patients was less than 20.00% at the end of 1980 but is currently increasing to over 70.00% for nonmetastatic patients. The objective to analyze the correlation between Lactate Dehydrogenase (LDH), Alkaline Phosphatase (ALP), C-Reactive Protein (CRP), Blood Deposition Rate (LED) , hCG expression and tumor volume with pulmonary metastases in osteosarcoma patients. The subjects were osteosarcoma patients that the data taken from January 2015 to December 2016. The subjects will be clinical, radiological (plain, CT scan thorax, MRI) examinations, serum marker tests consisting of ALP, LDH, CRP and LED and histopathologic staining IHC ?-hCG. The study design was cross-sectional, while the statistical analysis used was normality test, Spearman correlation, chi-square test and logistic regression. The results majority of subjects were male (52.00%) and aged 11-20 years (85.00%). The tumor volume (p = 0.07), LDH levels (p = 0.07), and ALP levels (p = 0.016) were statistically significant for pulmonary metastases with moderate correlation (r = 0.587; 0.587; 0.53). The tumor volume was the most sensitive biomarker to diagnose lung metastasis in osteosarcoma patients (p = 0.171). Conclusion among other protein biomarkers, tumor volume was most sensitive in diagnosing pulmonary metastases. The volume of the tumor will increase the risk of pulmonary metastases in osteosarcoma patients.

MicroRNA-761 targets FGFR1 to suppress the malignancy of osteosarcoma by deactivating PI3K/Akt pathway.

PurposeMicroRNA-761 (miR-761) has been reported to be deregulated in many types of human cancers and play important roles in cancer genesis and progression. However, the biological roles of miR-761 in osteosarcoma (OS) and the underlying mechanisms remain largely unknown.MethodsThe expression of miR-761 in OS tissues and cell lines was analyzed using RT-qPCR. A series of gain-of-function tests were performed, and status of malignancy was evaluated on basis of proliferation, migration, invasion, and apoptosis using different assays to determine the regulatory roles of miR-761 in OS cells in vivo and in vitro. Notably, the mechanisms underlying the action of miR-761 in the pathogenesis of OS were investigated using bioinformatic analysis, luciferase reporter assay, RT-qPCR and Western blotting.ResultsThe results showed that miR-761 expression was decreased in OS tissues and cell lines and is closely correlated with clinical stage and distant metastasis in OS patients. Patients with OS having low miR-761 expression showed worse prognosis compared to OS patients with high miR-761 expression. Restoring the miR-761 expression level decreased OS cell proliferation, migration, and invasion in vitro; promoted cell apoptosis in vitro; and impaired tumor growth in vivo. In addition, fibroblast growth factor receptor 1 (FGFR1) was found as a direct target gene of miR-761 in OS cells. Furthermore, silencing FGFR1 expression stimulated the tumor-suppressing roles of miR-761 upregulation in OS cells, whereas the activity of miR-761 overexpression in OS cells was abolished by the restoration of FGFR1 expression. Moreover, restoration of miR-761 expression deactivated the PI3K/Akt pathway in vitro and in vivo.ConclusionThese results suggest that miR-761 plays anti-cancer roles in OS by directly targeting FGFR1 and deactivating the PI3K/Akt pathway. The newly identified miR-761/FGFR1/PI3K/Akt pathway partially illustrates the mechanism of OS pathogenesis and presents a novel candidate therapeutic target for antitumor therapy.

Issue Highlights

IUBMB LifeVolume 71, Issue 7 p. 770-770 Issue HighlightsFree Access Issue Highlights First published: 20 June 2019 https://doi.org/10.1002/iub.2106AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat 845 LncRNA MIAT Facilitates Osteosarcoma Progression by Regulating miR-128-3p/VEGFC Axis Chunyan Zhang, Linsen Xie, Huiling Liang and Yuanbo Cui In this study, the results display that lncRNA MIAT is highly expressed in osteosarcoma (OS) tissues and cell lines. High expression of MIAT is closely associated with large tumor size and distant metastasis in OS patients. Knockdown of MIAT inhibits cell proliferation and metastasis, and promotes apoptosis in OS cells in vitro. MIAT promotes OS progression by functioning as a ceRNA via sponging miR-128-3p to up-regulate VEGFC in vitro. These findings may provide new insight into the roles of MIAT in the tumorigenesis of OS. 908 MicroRNA-365 Promotes the Contractile Phenotype of Venous Smooth Muscle Cells and Inhibits Neointimal Formation in Rat Vein Grafts Bo-Jun Cao, Lei Zhu, Xiao-Wen Wang, Rong-Jiang Zou and Zhi-Qian Lu MicroRNA-365 (miR-365) levels are substantially reduced in rat vein grafts at 7, 14, and 28 days post-grafting. Overexpression of miR-365 promoted smooth muscle-specific gene expression and inhibited venous SMC proliferation and migration. Consistent with this, overexpression of miR-365 in a rat vein graft model significantly reduced graftinginduced neointimal formation and effectively improved the hemodynamics of the vein grafts, suggesting its potential therapeutic application for prevention of vein graft failure. REFERENCES 1Zhang C., Xie L., Liang H. and Cui Y. LncRNA MIAT Facilitates Osteosarcoma Progression by Regulating miR-128-3p/VEGFC Axis. IUBMB Life. 2019, 71, 845– 853. 2Cao B.-J., Zhu L., Wang X.-W., Zou R.-J. and Z.-Q. Lu. MicroRNA-365 Promotes the Contractile Phenotype of Venous Smooth Muscle Cells and Inhibits Neointimal Formation in Rat Vein Grafts. IUBMB Life. 2019, 71, 908– 916. Volume71, Issue7July 2019Pages 770-770 ReferencesRelatedInformation

High Expression of PQBP1 and Low Expression of PCK2 are Associated with Metastasis and Recurrence of Osteosarcoma and Unfavorable Survival Outcomes of the Patients.

Osteosarcoma (OS) is the most common primary bone malignancy, predominately affecting children and adolescents. Due to the introduction of chemotherapy, the 5-year survival rate of OS patients has dramatically improved to 60-70%. Unfortunately, OS patients with recurrence or metastatic disease have less than a 20% chance of long-term survival, despite aggressive therapies. In this study, we aimed to identify gene expression patterns associated with metastasis and recurrence in order to identify potential biomarkers with prognostic power. We found that high expression of polyglutamine tract-binding protein 1 (PQBP1) and low expression of phosphoenolpyruvate carboxykinase 2 (PCK2) were related to a high probability of recurrence and metastasis in OS patients and also predicted shorter recurrence-free survival (RFS) and metastasis-free survival (MFS) after adjustment for other clinical variables. Prediction models based on the combination of PQBP1 and PCK2 expression had good and robust predictive power for recurrence and metastasis. A PQBP1 and PCK2-centered protein interaction network was built, and the hypothetical regulatory path between them was identified and termed the PQBP1-SF3A2-UBA52-PCK2 axis. Gene enrichment analysis indicated that aberrations of metabolism might play an important role in recurrence and metastasis in OS patients. Accordingly, PQBP1 and PCK2 are crucial for recurrence and metastasis in OS, and these findings provide a molecular basis for the exploitation of diagnostic and therapeutic strategies for overcoming recurrence and metastasis in OS.

Circular RNA circNASP modulates the malignant behaviors in osteosarcoma via miR-1253/FOXF1 pathway

Increasing evidences demonstrate that circular RNAs (circRNAs) serve as essential regulators in various human diseases, including cancer. However, the study on circRNA function in osteosarcoma (OS) is just emerging. In the present study, we screened out a novel circRNA termed circNASP which was significantly upregulated in OS tissues compared to adjacent normal tissues. We found that circNASP knockdown dramatically inhibited the proliferation, cell cycle progression and invasion of OS cells. Moreover, we showed that circNASP expression was positively correlated with tumor size and metastasis in OS patients. In terms of mechanism, we found that circNASP acts as a sponge of miR-1253 targeting FOXF1 in OS cells. By inhibiting miR-1253 availability, circNASP promoted FOXF1 expression. Rescue assays indicated that inhibition of miR-1253 could significantly reverse the effects of circNASP knockdown on OS cell proliferation and invasion while restoration of FOXF1 rescued the proliferation and invasion of OS cells transfected with miR-1253 mimics. Taken together, our findings demonstrated that circNASP contributes to malignant behaviors of OS cells by miR-1253/FOXF1 pathway, which suggested circNASP/miR-1253/FOXF1axis might be a potential therapeutic target.