Biomarker For Osteosarcoma Research Articles

Identification of UNC5B as a novel aggressive biomarker for osteosarcoma based on basement membrane genes

BackgroundThe prognosis of patients with metastatic osteosarcoma is poor, and the variation of basement membrane genes (BMGs) is associated with cancer metastasis. However, the role of BMGs in osteosarcoma has been poorly studied. MethodsBMGs were collected and differentially expressed BMGs (DE-BMGs) were found through difference analysis. DE-BMGs were further screened by univariate Cox regression and Lasso regression analyses, and six key BMGs were identified and defined as basement membrane genes signatures (BMGS). Then, BMGS was used to construct the osteosarcoma BMGS risk score system, and the osteosarcoma patients were divided into high- and low-risk groups based on the median risk score. Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE scores were used to investigate the differences in immune infiltration between the two scoring groups. Additionally, we investigated whether UNC5B affects various features in tumors by bioinformatic analysis and whether UNC5B was involved in multiple biological functions of osteosarcoma cells by wound healing assay, transwell assay, and western blot. ResultsThe osteosarcoma BMGS risk score reliably predicts the risk of metastasis, patient prognosis, and immunity. UNC5B expression was elevated in osteosarcoma, and correlated with various characteristics such as immune infiltration, prognosis, and drug sensitivity. In vitro assays showed that UNC5B knockdown reduced osteosarcoma cells’ capacity for migration and invasion, and EMT process. ConclusionA novel BMGS risk score system that can effectively predict the prognosis of osteosarcoma was developed and validated. The UNC5B gene in this system is one of the key aggressive biomarkers of osteosarcoma.

Comprehensive investigation of tumor immune microenvironment and prognostic biomarkers in osteosarcoma through integrated bulk and single-cell transcriptomic analysis.

Osteosarcoma (OS) is an aggressive and highly lethal bone tumor, highlighting the urgent need for further exploration of its underlying mechanisms. In this study, we conducted analyses utilizing bulk transcriptome sequencing data of OS and healthy control samples, as well as single cell sequencing data, obtained from public databases. Initially, we evaluated the differential expression of four tumor microenvironment (TME)-related gene sets between tumor and control groups. Subsequently, unsupervised clustering analysis of tumor tissues identified two significantly distinct clusters. We calculated the differential scores of the four TME-related gene sets for Clusters 1 (C1) and 2 (C2), using Gene Set Variation Analysis (GSVA, followed by single-variable Cox analysis. For the two clusters, we performed survival analysis, examined disparities in clinical-pathological distribution, analyzed immune cell infiltration and immune evasion prediction, assessed differences in immune infiltration abundance, and evaluated drug sensitivity. Differentially expressed genes (DEGs) between the two clusters were subjected to Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA). We conducted Weighted Gene Co-expression Network Analysis (WGCNA) on the TARGET-OS dataset to identify key genes, followed by GO enrichment analysis. Using LASSO and multiple regression analysis we conducted a prognostic model comprising eleven genes (ALOX5AP, CD37, BIN2, C3AR1, HCLS1, ACSL5, CD209, FCGR2A, CORO1A, CD74, CD163) demonstrating favorable diagnostic efficacy and prognostic potential in both training and validation cohorts. Using the model, we conducted further immune, drug sensitivity and enrichment analysis. We performed dimensionality reduction and annotation of cell subpopulations in single cell sequencing analysis, with expression profiles of relevant genes in each subpopulation analyzed. We further substantiated the role of ACSL5 in OS through a variety of wet lab experiments. Our study provides new insights and theoretical foundations for the prognosis, treatment, and drug development for OS patients.

Procollagen C-protein enhancer 1 (PCPE-1) as a potential serum biomarker for osteosarcoma.

e23518 Background: Osteosarcoma (OS) is the most common bone malignancy in children and young adults. Treatment with perioperative systemic chemotherapy has improved patient outcome but a third of patients will eventually develop incurable metastatic disease. Currently, there are no biomarkers for monitoring patients’ response to neo-adjuvant (NA) chemotherapy or for patients under active surveillance following treatments. Procollagen C-Proteinase Enhancer-1 (PCPE-1) is an extra-cellular matrix glycoprotein which promotes the maturation of pro-collagen into collagen in various tissues. Elevated serum levels of PCPE-1 are found in bone diseases such as Paget’s disease and Osteoporosis and in patients with breast cancer with bone metastases. Serum PCPE-1 has not been described in patients with OS. We aimed to describe PCPE-1 serum levels in patients with OS compared with healthy volunteers, and across different time points in their treatment and disease course. Methods: We collected serum samples from the Israeli national biobank of 18 adult OS patients. Serum samples were also collected from 6 healthy individuals. Additionally, we obtained serial samples from 4 OS patients prior to and after initiating NA therapy. Quantification of serum PCPE-1 levels was performed using a commercially available enzyme-linked immunosorbent assay (ELISA) kit. Results: We successfully analyzed serum PCPE-1 levels from all patients and healthy volunteers. Mean PCPE-1 levels of 553ng/ml (range 479-614ng/ml) were observed in OS patients, compared with 313ng/ml (285-339ng/ml) in healthy volunteers. Of 4 patients undergoing treatment who had serial samples, a decrease in serum levels was observed 2 responding patients, while an increase in PCPE-1 levels were observed in one patient after NA treatment who had no response to treatment at the time of surgery. Of notice, serum levels nearly doubled in a patient during active surveillance who experienced local disease recurrence (274ng/ml and 423ng/ml, respectively). Conclusions: This is the first study to show elevated PCPE-1 serum levels in patients with OS. Our study also demonstrates potential changes in PCPE-1 levels in response to treatment. We are expanding our study to include a pediatric population to investigate the role of PCPE-1 as a potential tumor biomarker for monitoring treatment and surveillance of OS.

Inflammasome-related gene signatures as prognostic biomarkers in osteosarcoma.

Osteosarcoma, the primary bone cancer in adolescents and young adults, is notorious for its aggressive growth and metastatic potential. Our study delved into the prognostic impact of inflammasome-related gene signatures in osteosarcoma patients, employing comprehensive genetic profiling to uncover signatures linked with patient outcomes. We identified three patient subgroups through consensus clustering, with one showing worse survival rates correlated with high FGFR3 and RARB expressions. Immune profiling revealed significant immune cell infiltration differences among these subgroups, affecting survival. Utilising advanced machine learning, including StepCox and gradient boosting machine algorithms, we developed a prognostic model with a notable c-index of 0.706, highlighting CD36 and MYD88 as key genes. Higher inflammasome risk scores from our model were associated with poorer survival, corroborated across datasets. Invitro experiments validated CD36 and MYD88's roles in promoting osteosarcoma cell proliferation, invasion and migration, emphasising their therapeutic potential. This research offers new insights into inflammasomes' role in osteosarcoma, introducing novel biomarkers for risk assessment and potential therapeutic targets. Our findings suggest a pathway towards personalised treatment strategies, potentially improving patient outcomes in osteosarcoma.

ZNF692 promotes osteosarcoma cell proliferation, migration, and invasion through TNK2-mediated activation of the MEK/ERK pathway

BackgroundOsteosarcoma is a diverse and aggressive bone tumor. Driver genes regulating osteosarcoma initiation and progression remains incompletely defined. Zinc finger protein 692 (ZNF692), a kind of Krüppel C2H2 zinc finger transcription factor, exhibited abnormal expression in different types of malignancies and showed a correlation with the clinical prognosis of patients as well as the aggressive characteristics of cancer cells. Nevertheless, its specific role in osteosarcoma is still not well understood.MethodsWe investigated the dysregulation and clinical significance of ZNF692 in osteosarcoma through bioinformatic method and experimental validation. A range of in vitro assays, including CCK-8, colony formation, EdU incorporation, wound healing, and transwell invasion tests, were conducted to assess the impact of ZNF692 on cell proliferation, migration, and invasion in osteosarcoma. A xenograft mouse model was established to evaluate the effect of ZNF692 on tumor growth in vivo. Western blot assay was used to measure the protein levels of MEK1/2, P-MEK1/2, ERK1/2, and P-ERK1/2 in cells that had been genetically modified to either reduce or increase the expression of ZNF692. The relationship between ZNF692 and tyrosine kinase non-receptor 2 (TNK2) were validated by qRT-PCR, chromatin immunoprecipitation and luciferase reporter assays.ResultsExpression of ZNF692 was increased in both human osteosarcoma tissues and cell lines. Furthermore, the expression of ZNF692 served as an independent predictive biomarker in osteosarcoma. The results of the survival analysis indicated that increased expression of ZNF692 was associated with worse outcome. Downregulation of ZNF692 inhibits the proliferation, migration, and invasion of osteosarcoma cells, whereas upregulation of ZNF692 has the opposite impact. Western blot assay indicates that reducing ZNF692 decreases phosphorylation of MEK1/2 and ERK1/2, whereas increasing ZNF692 expression enhances their phosphorylation. U0126, a potent inhibitor specifically targeting the MEK/ERK signaling pathway, partially counteracts the impact of ZNF692 overexpression on the proliferation, migration, and invasion of osteosarcoma cells. In addition, ZNF692 specifically interacts with the promoter region of TNK2 and stimulates the transcription of TNK2 in osteosarcoma cells. Forcing the expression of TNK2 weakens the inhibitory impact of ZNF692 knockdown on P-MEK1/2 and P-ERK1/2. Similarly, partly inhibiting TNK2 counteracts the enhancing impact of ZNF692 overexpression on the phosphorylation of MEK1/2 and ERK1/2. Functional tests demonstrate that the suppressive effects of ZNF692 knockdown on cell proliferation, migration, and invasion are greatly reduced when TNK2 is overexpressed. In contrast, the reduction of TNK2 hinders the ability of ZNF692 overexpression to enhance cell proliferation, migration, and invasion.ConclusionZNF692 promotes the proliferation, migration, and invasion of osteosarcoma cells via the TNK2-dependent stimulation of the MEK/ERK signaling pathway. The ZNF692-TNK2 axis might potentially function as a possible predictive biomarker and a promising target for novel therapeutics in osteosarcoma.

Identification of TNFRSF1A as a potential biomarker for osteosarcoma.

Osteosarcoma (OS) is a relatively rare malignant bone tumor in teenagers; however, its molecular mechanisms are not yet understood comprehensively. The study aimed to use necroptosis-related genes (NRGs) and their relationships with immune-related genes to construct a prognostic signature for OS. TARGET-OS was used as the training dataset, and GSE 16091 and GSE 21257 were used as the validation datasets. Univariate regression, survival analysis, and Kaplan-Meier curves were used to screen for hub genes. The immune-related targets were screened using immune infiltration assays and immune checkpoints. The results were validated using nomogram and decision curve analyses (DCA). Using univariate Cox regression analysis, TNFRSF1A was screened from 14 NRGs as an OS prognostic signature. Functional enrichment was analyzed based on the median expression of TNFRSF1A. The prognosis of the TNFRSF1A low-expression group in the Kaplan-Meier curve was notably worse. Immunohistochemistry analysis showed that the number of activated T cells and tumor purity increased considerably. Furthermore, the immune checkpoint lymphocyte activation gene 3 (LAG-3) is a possible target for intervention. The nomogram accurately predicted 1-, 3-, and 5-year survival rates. DCA validated the model (C = 0.669). TNFRSF1A can be used to elucidate the potential relationship between the immune microenvironment and NRGs in OS pathogenesis.

Identifying immune-related prognostic biomarkers in osteosarcoma: Development and validation of the tumor immune microenvironment risk model based on analysis of TCGA.

Osteosarcoma is a rare and aggressive malignancy with limited effective therapeutic options. This study aimed to identify immune-related prognostic biomarkers and develop a prognostic model for osteosarcoma. We performed integrated analysis of transcriptomic data and immune cell infiltration profiles of 84 osteosarcoma samples from the Cancer Genome Atlas (TCGA) database. Time-dependent receiver operating characteristic (ROC) curve analysis was used to assess the prognostic value of the TIMErisk model. We also performed functional annotation and pathway enrichment analyses to explore the potential mechanisms underlying the TIMErisk model. We identified a seven-gene TIMErisk model (C2, APBB1IP, BST2, TRPV2, CCL5, GBP1, and F13A1) that was independently associated with overall survival of osteosarcoma patients. The TIMErisk model showed significant associations with immune cell infiltration and immunosuppressive gene expression. In addition, the TIMErisk model was associated with drug sensitivity, and we found that several immune checkpoint genes were significantly differentially expressed between high- and low-TIMErisk groups. Functional annotation and pathway enrichment analyses revealed that the TIMErisk model was associated with multiple immune-related pathways, including antigen processing and presentation, cytokine-cytokine receptor interaction, and T cell receptor signaling pathway. Our study identified a novel TIME-based prognostic model for osteosarcoma that incorporates immune-related genes and can be used to predict patient prognosis and response to immunotherapy. Our findings highlight the importance of the TIME microenvironment in osteosarcoma progression and suggest that immune-related biomarkers may have clinical significance in the management of osteosarcoma.

Deciphering chemoresistance in osteosarcoma: Unveiling regulatory mechanisms and function through the lens of noncoding RNA.

Osteosarcoma (OS) is a primary malignant bone tumor and is prevalent in children, adolescents, and elderly individuals. It has the characteristics of high invasion and metastasis. Neoadjuvant chemotherapy combined with surgical resection is the most commonly used treatment for OS. However, the efficacy of OS is considerably diminished by chemotherapy resistance. In recent years, noncoding RNAs (ncRNAs), including microRNAs, long noncoding RNAs, and circular RNAs, are hot topics in the field of chemotherapy resistance research. Several studies have demonstrated that ncRNAs are substantially associated with chemoresistance in OS. Thus, the present study overviews the abnormally expressed ncRNAs in OS and the molecular mechanisms involved in chemoresistance, with an emphasis on their function in promoting or inhibiting chemoresistance. ncRNAs are expected to become potential therapeutic targets for overcoming drug resistance and predictive biomarkers in OS, which are of great significance for enhancing the therapeutic effect and improving the prognosis.

LncRNA SNHG25 Predicts Poor Prognosis and Promotes Progression in Osteosarcoma via the miR-497-5p/SOX4 Axis.

Osteosarcoma is a disease that primarily affects adolescents with skeletal immaturity. LncRNAs are abnormally expressed and correlated with osteosarcoma patients' prognosis. We identified aberrant expression of LncRNA SNHG25 (small nucleolar RNA host gene 25) in osteosarcoma and analyzed the molecular mechanisms by which it regulates osteosarcoma progression. The expression levels of SNHG25 in tumour specimens and cells were measured by RTqPCR. Loss-of-function assays were conducted to investigate the functional role of SNHG25 in vitro and in vivo. Bioinformatic predictions, dual-luciferase reporter assays, and western blotting were performed to explore the possible underlying mechanisms. SNHG25 was highly expressed in osteosarcoma cells and tissues. The Kaplan-Meier curve showed that the survival rate of patients with high SNHG25 expression was significantly lower than those with low SNHG25 expression. Functional studies have indicated that inhibition of SNHG25 suppresses cell proliferation, migration, and invasion, while promoting apoptosis. SNHG25 knockdown suppresses osteosarcoma tumour growth in vivo. SNHG25 functions as a sponge for miR-497-5p in osteosarcoma cells. The level of SNHG25 was negatively correlated with that of miR-497-5p. The proliferation, invasion, and migration of osteosarcoma cells were restored by transfection of the miR-497-5p inhibitor in the SNHG25 knockdown group. SNHG25 was determined to function as an oncogene by promoting osteosarcoma cell proliferation, invasion, and migration through the miR-497-5p/SOX4 axis. Upregulation of SNHG25 expression indicated poor prognosis in patients with osteosarcoma, which showed that SNHG25 may serve as a potential therapeutic target and prognostic biomarker in osteosarcoma.

Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers.

The principal aim of this investigation is to identify pivotal biomarkers linked to the prognosis of osteosarcoma (OS) through the application of artificial intelligence (AI), with an ultimate goal to enhance prognostic prediction. Expression profiles from 88 OS cases and 396 normal samples were procured from accessible public databases. Prognostic models were established using univariate COX regression analysis and an array of AI methodologies including the XGB method, RF method, GLM method, SVM method, and LASSO regression analysis. Multivariate COX regression analysis was also employed. Immune cell variations in OS were examined using the CIBERSORT software, and a differential analysis was conducted. Routine blood data from 20,679 normal samples and 437 OS cases were analyzed to validate lymphocyte disparity. Histological assessments of the study's postulates were performed through immunohistochemistry and hematoxylin and eosin (HE) staining. AI facilitated the identification of differentially expressed genes, which were utilized to construct a prognostic model. This model discerned that the survival rate in the high-risk category was significantly inferior compared to the low-risk cohort (p < 0.05). SERPINE2 was found to be positively associated with memory B cells, while CPT1B correlated positively with CD8 T cells. Immunohistochemical assessments indicated that SERPINE2 was more prominently expressed in OS tissues relative to adjacent non-tumorous tissues. Conversely, CPT1B expression was elevated in the adjacent non-tumorous tissues compared to OS tissues. Lymphocyte counts from routine blood evaluations exhibited marked differences between normal and OS groups (p < 0.001). The study highlights SERPINE2 and CPT1B as crucial biomarkers for OS prognosis and suggests that dysregulation of lymphocytes plays a significant role in OS pathogenesis. Both SERPINE2 and CPT1B have potential utility as prognostic biomarkers for OS.

Combined bioinformatics and machine learning methodologies reveal prognosis-related ceRNA network and propose ABCA8, CAT, and CXCL12 as independent protective factors against osteosarcoma.

Aberrant circular RNA (circRNA) acts as an oncogene or suppressor during neoplasm initiation and development. However, the functions of most circRNAs in osteosarcoma (OS) remain unclear. We aimed to investigate the expression, molecular functions and mechanisms underlying circRNAs in OS. Network interaction, pathway enrichment and regression analyses were performed to determine differentially expressed (DE) circRNAs, microRNAs (miRNAs) and messenger RNAs (mRNAs). We constructed competitive endogenous RcodeNA (ceRNA) networks and integrated patient clinical data to analyze the relationship between the networks and prognosis. The circRNA, miRNA and mRNA data were retrieved from Gene Expression Omnibus (GEO) microarray datasets. A circRNA-miRNA-mRNA interaction network was established and visualized using miRNet. Protein interactions were investigated using STRING and Cytoscape, and hub genes were identified using the MCODE plug-in. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway analyses were performed to determine the DEmRNAs. LIMMA and RobustRankAggreg were used to screen for DERNAs. Node genes in the interaction network were analyzed using least absolute shrinkage and selection operator (LASSO) and Cox regression to obtain OS-related ceRNA networks. We identified 9 DEcircRNAs, 243 DEmiRNAs and 211 DEmRNAs. We found that a ceRNA subnetwork, based on 1 circRNA, 1 miRNA and 8 mRNAs, was closely associated with OS prognosis. Integrating the proportional hazards model and survival analysis revealed 3 independent protective factors: adenosine triphosphate (ATP)-binding cassette sub-family A member 8 (ABCA8), catalase (CAT) and C-X-C motif chemokine ligand 12 (CXCL12). Our study provides novel insights into circRNA-related ceRNA networks and identifies potential prognostic biomarkers of OS.

RARRES2 is involved in the “lock-and-key” interactions between osteosarcoma stem cells and tumor-associated macrophages

Osteosarcoma (OS) is a type of tumor. Osteosarcoma stem cells (OSCs) are responsible for drug resistance, recurrence, and immunosuppression in OS. We aimed to determine the heterogeneity of OSCs and the immunosuppression mechanisms underlying the interactions between OSCs and tumor-associated macrophages (TAMs). The cell components, trajectory changes, and cell communication profiles of OS cells were analyzed by transcriptomics at the single-cell level. The intercellular communication patterns of OSCs were verified, and the role of the cell hub genes was revealed. Hub geneS are genes that play important roles in regulating certain biological processes; they are often defined as the genes with the strongest regulatory effect on differentially expressed gene sets. Moreover, various cellular components of the OS microenvironment were identified. Malignant cells were grouped, and OSCs were identified. Further regrouping and communication analysis revealed that the genes in the stemness maintenance and differentiation subgroups were involved in communication with macrophages. Key receptor–ligand pairs and target gene sets for cell communication were obtained. Transcriptome data analysis revealed the key gene RARRES2, which is involved in intercellular communication between OSCs and TAMs. In vitro studies confirmed that macrophages promote RARRES2-mediated stemness maintenance in OSCs via the TAM-secreted cytokine insulin-like growth factor 1. Patient studies confirmed that RARRES2 could be a biomarker of OS. OSCs are highly heterogeneous, and different subgroups are responsible for proliferation and communication with other cells. The IGF-RARRES2 axis plays a key role in maintaining OSC stemness through communication with TAMs.

Single-Cell Spatial-Temporal Analysis of ZNF451 in Mediating Drug Resistance and CD8+ T Cell Dysfunction.

Cisplatin is widely used to treat osteosarcoma, but recurrent cases often develop resistance, allowing the disease to progress and complicating clinical management. This study aimed to elucidate the immune microenvironment of osteosarcoma, providing insights into the mechanisms of recurrence and identifying potential therapeutic strategies. By analyzing multiple single-cell and bulk RNA-sequencing datasets, we discovered that the SUMOylation-related gene ZNF451 promotes osteosarcoma recurrence and alters its immune microenvironment. ZNF451 was found to importantly enhance the growth, migration, and invasion of resistant cells while also reducing their sensitivity to cisplatin and lowering their apoptosis rate. Moreover, our data indicated that ZNF451 plays a crucial role in bone resorption and epithelial-mesenchymal transition. ZNF451 also regulates CD8+ T cell function, leading to their exhaustion and transition to the CD8T.EXH state. Additionally, β-cryptoxanthin has been identified as a potential therapeutic agent that inhibits osteosarcoma progression by targeting ZNF451. In summary, these findings highlight the critical role of ZNF451 in promoting osteosarcoma progression and underscore its potential as a therapeutic target and biomarker for osteosarcoma.

Comprehensive analysis of the clinical significance and molecular mechanism of T-box transcription factor 3 in osteosarcoma.

Background: T-box transcription factor 3 (TBX3) has been implicated in various malignant tumors, while its exact involvement in osteosarcoma (OS) remains unknown. Methods: Utilizing microarray data and bulk and single-cell RNA-seq data and qRT-PCR, we compared TBX3 mRNA expression levels in different stages of OS. Diagnostic ability testing and prognosis analysis were conducted to better understand the clinical importance of TBX3. Enrichment analysis was performed using gene groups with biological functions similar to TBX3 in different stages of OS to investigate the potential role of TBX3 in OS progression. In addition, we predicted medications targeted at TBX3 and identified downstream target genes to gain a comprehensive understanding of its therapeutic direction and regulatory mechanism. Results: TBX3 expression was highly upregulated in OS and was predominantly expressed in osteoblastic OS cells, with higher expression levels in metastatic tissues. TBX3 expression appeared somewhat suitable for discriminating between OS and normal samples, as well as different stages of OS. We found that TBX3 increased the malignant development of OS by altering cell cycle and cell adhesion molecules; exisulind and tacrolimus, which are targeted small-molecule medicines, were anticipated to counteract this dysregulation. The expression of CCNA2 could potentially be regulated by TBX3, contributing to OS advancement. Conclusion: TBX3 emerges as a potential biomarker for OS. In-depth research into its underlying molecular processes may offer new perspectives on treating OS.

High expression of integrin-binding sialoprotein (IBSP) is associated with poor prognosis of osteosarcoma.

Osteosarcoma is a malignant tumor, accounting for 20% of primary malignant bone tumors worldwide. However, the role of IBSP as a biomarker in osteosarcoma progression has not been studied yet. 85 cases of IBSP expression and clinical characteristics were obtained from TARGET database. Through the Kaplan-Meier curve, subgroup analysis, and univariate and multivariate Cox analysis, we further assessed the independent predictive capacity of IBSP expression for overall survival (OS) and relapse-free survival (RFS). The mRNA expression of IBSP was higher in osteosarcoma than normal tissue (P < 0.0001). IBSP expression grouped by vital status showed statistical differences (P = 0.042). The race (P = 0.0183), vital status (P = 0.0034), and sample type (P = 0.0020) showed significant differences. IBSP expression exhibited satisfied diagnostic ability for osteosarcoma. The univariate and multivariate analysis confirmed that IBSP expression was an independent risk factor for OS (HR = 3.425, 95% CI: 1.604-7.313, P = 0.002) and RFS (HR = 3.377, 95% CI: 1.775-6.424, P < 0.001) in osteosarcoma patients. High IBSP expression was significantly associated with poor OS and RFS (P < 0.0001). The higher IBSP expression was observed in osteosarcoma (P < 0.001), confirmed by the IHC staining. The CCK-8 and colony formation assay showed that IBSP knockdown inhibits cell proliferation while overexpression promotes cell proliferation (P < 0.05). High expression of IBSP was associated with poor OS and RFS. IBSP could serve as a potential biomarker for osteosarcoma, which could aid in early detection and disease monitoring.

Retraction: SMARCB1 expression is a novel diagnostic and prognostic biomarker for osteosarcoma.

Retraction: SMARCB1 expression is a novel diagnostic and prognostic biomarker for osteosarcoma.

Anti-cancer targets and molecular mechanisms of formononetin in treating osteosarcoma based on network pharmacology.

Osteosarcoma (OS) is a multifactorial bone malignancy that accounts for most cancers in children and adolescents. Formononetin has been proven to exhibit various pharmacological effects including anti-tumor, anti-obesity, anti-inflammation, and neuroprotective effects. Few studies have examined the pharmacological activities of formononetin in OS treatment, but the mechanism has not yet been completely elucidated. Network pharmacology is a new method based on the theory of system biology for analyzing the network of biological systems and selecting specific signal nodes for multi-target drug molecular design. Here, we used network pharmacology to explore the possible mechanism of formononetin in OS treatment. Human OS cell line MG63 was processed with four concentrations (0, 2, 5, 8 μg/mL) of formononetin. Subsequently, an MTT assay was performed to test cell proliferation and a scratch test was used to evaluate the migration ability of cancer cells. Caspase-3, p53, p21, and bcl-2 expression levels incubated with different concentrations of formononetin in MG63 cells were determined using Western blotting. After treated with formononetin for 48 h, MG63 cells exhibited marked apoptosis. The results revealed that certain concentrations of formononetin significantly exerted inhibitory effects on MG63 cell proliferation. Furthermore, formononetin decreased the bcl-2 level in MG63 cells but increased caspase-3, p21, and p53 levels in a concentration-dependent manner. Additionally, formononetin suppressed the expression of SATB2. Therefore, formononetin could dose-dependently inhibit MG63 cell proliferation and induce apparent cell apoptosis, providing a candidate treatment for OS, whereas SATB2 could be a potential prognostic biomarker for screening OS and therapeutic target of formononetin.

SERPINH1 enhances the malignancy of osteosarcoma via PI3K-Akt signaling pathway

BackgroundSerpin Family H Member 1 (SERPINH1) may be involved in the regulation of occurrence and development of tumors. However, the role and mechanism of SERPINH1 in osteosarcoma remain poorly understood. The aim of this study is to investigate the expression and role of SRPINH1 in osteosarcoma and to elucidate its underlying mechanisms. MethodsFirst, we examined the expression of SERPINH1 in osteosarcoma and analyzed publicly available datasets to investigate whether SERPINH1 expression was associated with the prognosis of osteosarcoma. Then we constructed SERPINH1 overexpression and knockdown systems in osteosarcoma cells, and examined the proliferation, migration and invasion ability of osteosarcoma cells after SERPINH1 expression changes using CCK-8 assay, wound healing assay and transwell invasion assay. In addition, we constructed a subcutaneous xenograft tumor model to study the function of SERPINH1 in vivo. We also examined the downstream pathways of SERPINH1 by functional analysis and performed subsequent validation. ResultsSERPINH1 was upregulated and associated with poor survival in patients with osteosarcoma. SERPINH1 promoted the proliferation, migration and invasion of osteosarcoma cells and promotes the growth of osteosarcoma in vivo by activating the PI3K-Akt signaling pathway. ConclusionSERPINH1 partakes in the biological process of osteosarcoma as a tumor promotor and may be an emerging biomarker in osteosarcoma.

RAMP1 as a novel prognostic biomarker in pan-cancer and osteosarcoma.

Receptor activity modifying protein 1 (RAMP1) facilitates the localization of the calcitonin-like receptor (CLR) to the plasma membrane, but its role in osteosarcoma (OS) remains unclear. We evaluated the RAMP1 expression and prognostic value across different cancers, studying tumor immune infiltration. The prognostic value was analyzed using the GSE39058 and TARGET datasets. Differential gene expression was evaluated. a protein-protein interaction network was constructed, and gene set enrichment analysis was performed. The function of RAMP1 in the tumor microenvironment was analyzed, and its expression in OS cell lines was validated using quantitative real-time PCR. High RAMP1 expression correlated with poor prognosis relative to low RAMP1 expression (p < 0.05). Low RAMP1 expression correlated with an abundance of CD4+ memory-activated T cells. whereas a high expression level correlated with a high proportion of gamma-delta T cells (γδ T cells). Differentially expressed genes from TARGET was enriched in olfactory transduction pathways (normalized enrichment scores [NES] = 1.6998, p < 0.0001). RAMP1 expression negatively correlated with CD44 expression but positively correlated with TNFSF9 expression. The RAMP1 gene is substantially expressed in OS cells compared to the normal osteoblast cell line hFOB1.19. Thus, RAMP1 may be a prognostic biomarker and potential therapeutic target in OS.

Long intergenic non-coding RNA DIO3OS promotes osteosarcoma metastasis via activation of the TGF-β signaling pathway: a potential diagnostic and immunotherapeutic target for osteosarcoma

BackgroundThe aim of this study was to determine the underlying potential mechanisms and function of DIO3OS, a lincRNA in osteosarcoma and clarify that DIO3OS can be used as a potential diagnostic biomarker and immunotherapeutic target.MethodsThe expression matrix data and clinical information were obtained from XENA platform of UCSC and GEO database as the test cohorts. The external validation cohort was collected from our hospital. Bioinformatics analysis was used to annotate the biological function of DIO3OS. Immune infiltration and immune checkpoint analysis were applied to evaluate whether DIO3OS can be used as an immunotherapeutic target. ROC curves and AUC were established to assess the diagnostic value of DIO3OS for differentiating patients from other subtypes sarcoma. The expression analysis was detected by qRT-PCR, western blot, and immunohistochemical. Wound healing assay and Transwell assay were applied to determine the migration and invasion function of DIO3OS in osteosarcoma cell lines. The tail vein injection osteosarcoma cells metastases model was used in this research.ResultsHigh expression of DIO3OS was identified as a risk lincRNA for predicting overall survival of osteosarcoma in test cohort. The outcomes of experiments in vitro and in vivo showed that low expression of DIO3OS limited osteosarcoma tumor metastasis with inhibiting TGF-β signaling pathway. Immune checkpoint genes (CD200 and TNFRSF25) expressions were inhibited in the low DIO3OS expression group. The DIO3OS expression can be applied to reliably distinguish osteosarcoma from lipomatous neoplasms, myomatous neoplasms, nerve sheath tumors, and synovial-like neoplasms. This result was further validated in the validation cohort.ConclusionsIn conclusion, our outcomes indicated that DIO3OS is a potential diagnostic and prognostic biomarker of osteosarcoma, emphasizing its potential as a target of immunotherapy to improve the treatment of osteosarcoma through TGF-β signaling pathway.Trial registration number: The present retrospectively study was approved by the Ethics Committee of The Second Affiliated Hospital of Nanchang University [Review (2020) No. (115)].