Osteosarcoma Samples Research Articles

Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression

BackgroundOsteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease.MethodsFirstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene’s regulation on osteosarcoma development were in succession explored.ResultsBased on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene’s physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene’s association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored.ConclusionUsing multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene’s clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use.

Single-cell RNA datasets and bulk RNA datasets analysis demonstrated C1Q+ tumor-associated macrophage as a major and antitumor immune cell population in osteosarcoma.

Osteosarcoma is the most frequent primary bone tumor with a poor prognosis. Immune infiltration proved to have a strong impact on prognosis. We analyzed single-cell datasets and bulk datasets to confirm the main immune cell populations and their properties in osteosarcoma. The examples in bulk datasets GSE21257 and GSE32981 from the Gene Expression Omnibus database were divided into two immune infiltration level groups, and 34 differentially expressed genes were spotted. Then, we located these genes among nine major cell clusters and their subclusters identified from 99,668 individual cells in single-cell dataset GSE152048 including 11 osteosarcoma patients. Especially, the markers of all kinds of myeloid cells identified in single-cell dataset GSE152048 were set to gene ontology enrichment. We clustered the osteosarcoma samples in the TARGET-OS from the Therapeutically Applicable Research to Generate Effective Treatments dataset into two groups by complete component 1q positive macrophage markers and compared their survival. Compared with the low-immune infiltrated group, the high-immune infiltrated group showed a better prognosis. Almost all the 34 differentially expressed genes expressed higher or exclusively among myeloid cells. A group of complete component 1q-positive macrophages was identified from the myeloid cells. In the bulk dataset TARGET-OS, these markers and the infiltration of complete component 1q-positive macrophages related to longer survival. Complete component 1q-positive tumor-associated macrophages were the major immune cell population in osteosarcoma, which contributed to a better prognosis.

Loss of RanGAP1 drives chromosome instability and rapid tumorigenesis of osteosarcoma.

Chromothripsis is a catastrophic event of chromosomal instability that involves intensive fragmentation and rearrangements within localized chromosomal regions. However, its cause remains unclear. Here, we show that reduction and inactivation of Ran GTPase-activating protein 1 (RanGAP1) commonly occur in human osteosarcoma, which is associated with a high rate of chromothripsis. In rapidly expanding mouse osteoprogenitors, RanGAP1 deficiency causes chromothripsis in chr1q, instant inactivation of Rb1 and degradation of p53, consequent failure in DNA damage repair, and ultrafast osteosarcoma tumorigenesis. During mitosis, RanGAP1 anchors to the kinetochore, where it recruits PP1-γ to counteract the activity of the spindle-assembly checkpoint (SAC) and prevents TOP2A degradation, thus safeguarding chromatid decatenation. Loss of RanGAP1 causes SAC hyperactivation and chromatid decatenation failure. These findings demonstrate that RanGAP1 maintains mitotic chromosome integrity and that RanGAP1 loss drives tumorigenesis through its direct effects on SAC and decatenation and secondary effects on DNA damage surveillance.

LncRNA STK4 antisense RNA 1 (STK4-AS1) promoted osteosarcoma by inhibiting p53 expression.

LncRNA STK4 antisense RNA 1 (STK4-AS1) has been identified as a potential biomarker associated with multiple cancers. We proposed that STK4-AS1 plays a role in the proliferation of osteosarcoma by regulating the cell cycle. We compared the expression of STK4-AS1, p53, and p21 in osteosarcoma vs normal samples in clinical tissues and cell lines. We determined the effect of overexpression and knockdown of STK4-AS1 in p53 expressing osteosarcoma cells U2OS, p53 muted osteosarcoma cells MG63, and osteoblast cells hFOB on p53 and p21 expression and the cell viability. For U2OS and MG63, the cell cycle was analyzed and the expression of cyclin proteins was determined. We overexpressed p53 or p21 in STK4-AS1 overexpressed cells to explore the association of STK4-AS1 and p53 in U2OS. The STK4-AS1 expression was higher and p53 and p21 expression were lower in osteosarcoma tissue and cells than in their non-cancer counterparts. The expression of STK4-AS1 was negatively correlated with the expression of p53 or p21. Knockdown of STK4-AS1 in U2OS decreased the cell viability, increased cells in the G0/G1 phase, decreased cells in the S and G2/M phase, decreased expression of cyclin A and B, increased p53 and p21, and had no effect on cyclin D and cyclin E, while overexpression of STK4-AS1 did the opposes. Overexpression of p53 or p21 recovered some changes caused by STK4-AS1 overexpression in U2OS. MG63 expressed no p53 and the expression of p21, cyclin A, and cyclin B, cell viability, and cell cycle were not affected by altered STK4-AS1 levels. In hFOB cells, the expression of p53 and p21 was decreased and the cell viability was increased when STK4-AS1 was overexpressed, but they were not affected when STK4-AS1 was knocked down. LncRNA STK4-AS1 promoted the cell cycle of osteosarcoma cells by inhibiting p53 expression.

A novel molecular classification method for osteosarcoma based on tumor cell differentiation trajectories

Subclassification of tumors based on molecular features may facilitate therapeutic choice and increase the response rate of cancer patients. However, the highly complex cell origin involved in osteosarcoma (OS) limits the utility of traditional bulk RNA sequencing for OS subclassification. Single-cell RNA sequencing (scRNA-seq) holds great promise for identifying cell heterogeneity. However, this technique has rarely been used in the study of tumor subclassification. By analyzing scRNA-seq data for six conventional OS and nine cancellous bone (CB) samples, we identified 29 clusters in OS and CB samples and discovered three differentiation trajectories from the cancer stem cell (CSC)-like subset, which allowed us to classify OS samples into three groups. The classification model was further examined using the TARGET dataset. Each subgroup of OS had different prognoses and possible drug sensitivities, and OS cells in the three differentiation branches showed distinct interactions with other clusters in the OS microenvironment. In addition, we verified the classification model through IHC staining in 138 OS samples, revealing a worse prognosis for Group B patients. Furthermore, we describe the novel transcriptional program of CSCs and highlight the activation of EZH2 in CSCs of OS. These findings provide a novel subclassification method based on scRNA-seq and shed new light on the molecular features of CSCs in OS and may serve as valuable references for precision treatment for and therapeutic development in OS.

TAF1D Functions as a Novel Biomarker in Osteosarcoma.

Background: The most frequent primary bone cancer in teenagers, osteosarcoma (OS), is particularly aggressive with a high mortality rate. Methods: By combining public databases, OS and non-cancer samples were obtained. The Wilcoxon test and standardized mean difference (SMD) were utilized to evaluate the mRNA expression level of TATA-box binding protein associated factor, RNA polymerase 1 subunit D (TAF1D). The potential of TAF1D to discriminate OS samples from non-cancer samples was revealed by summary receiver operating characteristic curve (sROC). To investigate the prognostic significance, Kaplan‒Meier curve and univariate Cox analysis were performed. Immunohistochemistry (IHC) was used to determine the TAF1D protein expression level. ESTIMATE algorithm and TIMER2.0 database were used to reveal the association between TAF1D expression and the immune microenvironment. Enrichment analysis and potential drug prediction were performed to clarify the underlying molecular mechanisms and possible therapeutic directions of TAF1D. Ultimately, the transcription factors (TFs) and the TAF1D binding site were predicted based on the Cistrome and JASPAR databases. Results: TAF1D was upregulated in OS at the mRNA and protein levels and possessed robust discriminatory power. TAF1D upregulation was suggestive of worse prognosis and enhancement of tumor purity in OS patients. The cell cycle was the most significantly enriched pathway, and NU.1025 was considered to be the potential target agent. Finally, MYC was identified as a TF that regulates the expression of TAF1D. Conclusions: Altogether, TAF1D has the potential to serve as a biological marker and therapeutic target in OS, which could offer new perspectives for OS treatment.

Screening and identification of susceptibility genes for osteosarcoma based on bioinformatics analysis.

Gene play an important role in malignant tumors. However, there is still insufficient research on genetic variations in osteosarcoma (OS) patients. Therefore, we aimed to analyze the gene expression profile of OS using bioinformatics and to explore the pathogenesis of OS at the molecular level. The gene chip dataset of OS samples was downloaded from the Gene Expression Omnibus (GEO) database for screening differentially expressed genes (DEGs). The R language clusterProfiler software package was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs. The central node proteins of the protein interaction network were analyzed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, Cytoscape, and its plug-ins cytoHubba and NetworkAnalyzer to find the key genes. A total of 631 DEGs were obtained, including 362 upregulated genes and 269 downregulated genes. DEGs were mainly involved in the regulation of leukocyte chemotaxis and migration, vascular development, and other biological processes (BPs); mediation of receptor ligand activity, growth factor binding, growth factor activity, integrin binding, and other molecular functions (MFs); and were enriched in the extracellular matrix (ECM). DEGs in the ECM and growth factors play a key role in the development of OS. The leukocyte transendothelial migration pathway and the PI3K-AKT pathway are closely related to OS, and the related molecular mechanism is worthy of further study.

Analysis of scRNA-seq and bulk RNA-seq demonstrates the effects of EVI2B or CD361 on CD8+ T cells in osteosarcoma.

Osteosarcoma (OS) is a common primary malignant tumor of the bone in children and adolescents. The five-year survival rate is estimated to be ~70% based on the currently available treatment modalities. It is well known that tumor-infiltrating immune cells (TIICs) that are the most important components in the tumor microenvironment can exert a killing effect on tumor cells. Therefore, in the present study, 85 RNA-sequencing OS samples were categorized into high- and low-immune score groups with ESTIAMATE. Based on the immune score groups, 474 differentially expressed genes (DEGs) were acquired using the LIMMA package of R language. Subsequently, 86 DEGs were taken through univariate COX regression analysis, of which 14 were screened out by least absolute shrinkage and selection operator regression analysis. Furthermore, multivariate COX regression analysis was performed to obtain 4 DEGs. Finally, ecotropic virus integration site 2B (EVI2B) or CD361 gene was screened out via Kaplan-Meier analysis. In addition, CIBERSORT algorithm was used to evaluate the proportion of 22 kinds of TIICs in OS. Correlation analysis revealed that the high expression level of EVI2B can elevate the infiltrated proportion of CD8+ T cells. Moreover, analysis of single cell RNA-sequencing transcriptome datasets and immunohistochemical staining uncovered that EVI2B was mainly expressed on CD8+ T cells and that EVI2B could promote the expression of granzyme A and K of CD8+ T cells to exhibit a potent killing effect on tumor cells. Therefore, EVI2B was identified as a protective immune-related gene and contributed to good prognosis in OS patients.

Identification and verification of microRNA signature and key genes in the development of osteosarcoma with lung metastasis.

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor in children under the age of 20. This study aims to research the association between Solute Carrier Family 7 Member 8 (SLC7A8) as well as related genes and OS. OS and normal samples (GSE38698 and GSE85537) were downloaded from Gene Expression Omnibus dataset. The bioinformatics analysis was performed to distinguish 2 differentially expressed genes, prognostic candidate genes and functional enrichment pathway. Immunohistochemistry and quantitative real-time PCR were utilized for further study. There were 5 DEMs and 10 differentially expressed genes in cancer tissues compared to normal tissues. According to the km-plot software, ARHGEF3, BSN, PQLC3, and SLC7A8 were significantly related to the overall survival of patients with OS. Furthermore, Multivariate analysis included that SLC7A8 was independent risk factors for OS patients. Furthermore, immunohistochemistry and quantitative real-time PCR outcomes indicated that the expression level of SLC7A8 and hsa-miR-506 was differentially expressed in lung metastasis OS tissues and non-metastasis tissues. The prognostic model based on the miRNA-mRNA network could provide predictive significance for prognosis of OS patients, which would be worthy of clinical application. Our results concluded that SLC7A8 may play a key role in the development of OS.

A mitochondria-related signature for predicting immune microenvironment and therapeutic response in osteosarcoma.

Osteosarcoma remains to be the most devastating malignant tumor in children and teenagers. Mitochondria have also been proven to play critical roles in osteosarcoma. However, a mitochondria-related signature has been established in osteosarcoma to comprehensively evaluate the pathogenic roles and regulatory roles of mitochondria in osteosarcoma. In this study, osteosarcoma samples' transcriptome data and clinical information were collected from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. A comprehensive bioinformatics analysis was performed on the samples at the bulk RNA sequencing level and single-cell RNA sequencing (scRNA-seq) level. EdU, Transwell, and immunohistochemistry (IHC) were performed on PCCB. A mitochondria-related signature was constructed in osteosarcoma patients. The prognostic value of the mitochondria-related signature was explored. The predictive value of the mitochondria-related signature in the immune microenvironment and chemotherapy agents was explored. The association between mitochondria and immunity in the tumor microenvironment of osteosarcoma at the scRNA-seq level was investigated. The tumorigenic role of the critical mitochondria-related gene, PCCB, was verified by in vitro validation. In conclusion, a mitochondria-related signature was developed in osteosarcoma with solid predictive values in the immune microenvironment, chemotherapy agents, and prognosis.

Hsa_circ_0097271 Knockdown Attenuates Osteosarcoma Progression via Regulating miR-640/MCAM Pathway.

The dysregulation of circular RNAs (circRNAs) participates in the malignant progression of multiple cancers, including osteosarcoma (OS). However, the role of circ_0097271 in OS development remains unclear. We thus aimed at unveiling the functional role and mechanism of circ_0097271 in OS. The expressions of circ_0097271, miR-640, and MCAM in OS were analyzed by qPCR. Cell proliferation and migration were inspected by CCK-8 assay, colony formation assay, and Transwell assay. Circ_0097271's role in vivo was assayed by establishing animal models. The predicted binding relationship between miR-640 and circ_0097271 or MCAM was verified by dual-luciferase reporter or RIP assay. Circ_0097271's expression was enhanced in OS samples and cells. The knockdown of circ_0097271 restrained OS cell growth and migration, and its downregulation also blocked solid tumor growth in vivo. Circ_0097271 targeted miR-640 and negatively modulated miR-640 expression. MiR-640 was poorly expressed in OS, and its depletion recovered OS cell growth and migration that were repressed by circ_0097271 knockdown. MiR-640 bound to MCAM 3'UTR and thus suppressed MCAM expression. MCAM knockdown repressed OS cell growth and migration, while additional miR-640 depletion partially abolished the anticancer effects of MCAM knockdown in OS cells. Circ_0097271 is an oncogenic driver and contributes to OS development via targeting the miR-640/MCAM pathway, which provides a potential opinion for OS treatment.

Combining bulk RNA-sequencing and single-cell RNA-sequencing data to reveal the immune microenvironment and metabolic pattern of osteosarcoma

Background: Osteosarcoma (OS) is a kind of solid tumor with high heterogeneity at tumor microenvironment (TME), genome and transcriptome level. In view of the regulatory effect of metabolism on TME, this study was based on four metabolic models to explore the intertumoral heterogeneity of OS at the RNA sequencing (RNA-seq) level and the intratumoral heterogeneity of OS at the bulk RNA-seq and single cell RNA-seq (scRNA-seq) level. Methods: The GSVA package was used for single-sample gene set enrichment analysis (ssGSEA) analysis to obtain a glycolysis, pentose phosphate pathway (PPP), fatty acid oxidation (FAO) and glutaminolysis gene sets score. ConsensusClusterPlus was employed to cluster OS samples downloaded from the Target database. The scRNA-seq and bulk RNA-seq data of immune cells from GSE162454 dataset were analyzed to identify the subsets and types of immune cells in OS. Malignant cells and non-malignant cells were distinguished by large-scale chromosomal copy number variation. The correlations of metabolic molecular subtypes and immune cell types with four metabolic patterns, hypoxia and angiogenesis were determined by Pearson correlation analysis. Results: Two metabolism-related molecular subtypes of OS, cluster 1 and cluster 2, were identified. Cluster 2 was associated with poor prognosis of OS, active glycolysis, FAO, glutaminolysis, and bad TME. The identified 28608 immune cells were divided into 15 separate clusters covering 6 types of immune cells. The enrichment scores of 5 kinds of immune cells in cluster-1 and cluster-2 were significantly different. And five kinds of immune cells were significantly correlated with four metabolic modes, hypoxia and angiogenesis. Of the 28,608 immune cells, 7617 were malignant cells. The four metabolic patterns of malignant cells were significantly positively correlated with hypoxia and negatively correlated with angiogenesis. Conclusion: We used RNA-seq to reveal two molecular subtypes of OS with prognosis, metabolic pattern and TME, and determined the composition and metabolic heterogeneity of immune cells in OS tumor by bulk RNA-seq and single-cell RNA-seq.

Dissecting the effect of sphingolipid metabolism gene in progression and microenvironment of osteosarcoma to develop a prognostic signature.

Sphingolipid metabolism (SM) fuels tumorigenesis and the malignant progression of osteosarcoma (OS), which leads to an unfavorable prognosis. Elucidating the molecular mechanisms underlying SM in osteosarcoma and developing a SM-based prognostic signature could be beneficial in the clinical setting. This study included 88 frozen OS samples to recognize the vital SM-relevant genes in the development of OS utilizing univariate Cox regression. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was conducted on the SM- relevant genes to minimize the risk of overfitting. The prognostic signature was generate utilizing the multivariable Cox regression analysis and was verified in the validation cohort. Moreover, cellular and molecular mechanisms associated with SM have an unfavorable prognosis for OS patients and have been widely studied. Resultantly, an SM-based prognostic risk model was established according to critical prognostic genes (CBS, GLB1, and HACD1), which had an excellent ability to predict the prognosis of OS patients (AUC for the train cohort was 0.887 and AUC for validation cohort was 0.737). The high-risk OS patients identified based on this prognostic signature had significantly poor immune microenvironment, indicated by significantly low immune score (mean=216.290 ± 662.463), reduced infiltrations of 25 immune cells, including NK cells (LogFC= -0.3597), CD8+T cells ((LogFC=-0.2346), Cytolytic activity ((LogFC=-0.1998), etc. The immunosuppressive microenvironment could be due to dysregulated SM of glycolipids. Further, a nomogram was constructed by integrating the SM-based prognostic signature and clinical paraments to facilitate clinical application. The nomogram could accurately predict the prognosis of OS invalids. Collectively, this study clarified the function of SM in the development of OS and helped develop a tool for risk stratification based on SM-related genes with application in clinical settings. The results of our study will aid in identifying high-risk patients and provide individualized treatments.

Subtype Classification and Prognosis Signature Construction of Osteosarcoma Based on Cellular Senescence-Related Genes

Background Cellular senescence (CS) is an alternative procedure that replaces or reinforces inadequate apoptotic responses and is used as an influencing factor for a variety of cancers. The value of CS gene in evaluating the immunotherapy response and clinical outcome of osteosarcoma (OS) has not been reported, and an accurate risk model based on CS gene has not been developed for OS patients. Methods 279 CS genes were obtained from CellAge. Univariate Cox regression analysis was used to screen the CS gene which was significantly related to the prognosis of OS samples in TARGET data set. The prognosis, clinicopathological features, immune infiltration, gene expression at immune checkpoints, tumor immune dysfunction and exclusion (TIDE) score, and chemotherapy resistance of OS were analyzed among clusters. Least absolute shrinkage and selection operator (Lasso) Cox regression analysis to build cellular senescence-related gene signature (CSRS). Univariate and multivariate Cox regression analysis of CSRS and clinical parameters were carried out, and the parameters with independent prognostic value were used to construct nomogram. Results Based on 30 CS genes related to OS prognosis, OS samples were divided into three clusters: C1, C2, and C3. C3 showed the lowest survival rate and metastasis rate and the highest immune score and stromal score and was more likely to respond to immune checkpoint blockade (ICB) treatment. A CSRS scoring system including four CS genes (MYC, DLX2, EPHA3, and LIMK1) was constructed, which could distinguish the survival outcome, tumor microenvironment (TME) status, and ICB treatment response of patients with different CSRS score. Nomogram constructed by CSRS score and metastatic has a high prognostic value for OS. Conclusions Our study identified a molecular classification determined by CS-related genes and developed a new CSRS that has potential value in OS immunotherapy response and clinical outcome prediction.

Down-Regulation of Ubiquitin-Specific Peptidase 9X Inhibited Proliferation, Migration and Invasion of Osteosarcoma via ERK1/2 and PI3K/Akt Signaling Pathways.

Ubiquitin-specific peptidase 9X (USP9X) has been reported to be closely associated with the formation and progression of a variety of malignant tumors. However, the mechanism by which USP9X is involved in osteosarcoma and development has not been clearly studied. This work aimed to probe the influence of USP9X on osteosarcoma cell proliferation, migration and invasion. This study recruited sixty-seven patients with histologically definited osteosarcoma. Osteosarcoma samples and cell-line were used to reflect the expression level of USP9X. Analysis of cell proliferation by thiazolium blue (MTT) assays. Transwell experiments and wound healing were used to verify cell migration and invasion capabilities. The effect of USP9X was investigated through in vivo experiments. USP9X-related pathway proteins were detected by Western blot and quantitative real-time PCR (qRT-PCR). The expression of USP9X in osteosarcoma was higher than that in adjacent tissues. The overall survival of patients with USP9X-negative patients was better than that of patients with USP9X-positive. The growth of osteosarcoma cells in vivo and in vitro was inhibited by USP9X inhibitor. Cell migration and invasion were significantly inhibited by down-regulation of USP9X. USP9X was involved in extracellular signal-regulated kinase 1/2 (ERK1/2) and phosphatidylinositol-3-kinases/protein-serine-threonine kinase (PI3K/Akt) pathway in osteosarcoma cells. Proliferation, migration and invasion of osteosarcoma cells were inhibited by down-regulation of USP9X, and were related to the ERK1/2 and PI3K/Akt signaling pathways, therefore, it might probably become a new target for the prevention and treatment of osteosarcoma.

The mitotic regulator polo-like kinase 1 as a potential therapeutic target for c-Myc-overexpressing canine osteosarcomas.

Osteosarcoma is the most common primary malignant bone tumour in dogs, characterized by a locally aggressive and highly metastatic behaviour. Despite the current standards of care, most dogs succumb to the disease, indicating the need for novel treatment strategies. Polo-like kinase 1 (PLK1) is dysregulated in a variety of human cancer types, including osteosarcoma, and induces c-Myc accumulation. The crosstalk between the two molecules coordinates cell proliferation, differentiation, self-renewal and apoptosis. Therefore, PLK1 has recently emerged as a potential therapeutic target, mainly in tumours overexpressing c-Myc. BI 2536 is a selective PLK1 inhibitor promoting mitotic arrest and apoptosis in a variety of cancer cells. This research aimed at evaluating PLK1 and c-Myc protein expression in 53 appendicular canine osteosarcoma (cOSA) samples and the in vitro effects of BI 2536 on a c-Myc and PLK1-overexpressing cOSA cell line (D17). PLK1 and c-Myc expression in cOSA samples showed no correlation with clinicopathological data. However, c-Myc overexpression was associated with a significantly reduced overall survival (p= .003). Western Blot and RT-qPCR assays revealed that D17 expressed high protein and transcript levels of both PLK1 and MYC. When treated with BI 2536 (range 2.5-15 nM) for 24 h, D17 showed a substantial decrease in cell growth, inducing apoptosis and G2 /M cell cycle arrest. Interestingly, under BI 2536 treatment, D17 showed decreased c-Myc protein levels. Consistent with human OSA, these preliminary data outline the prognostic value of c-Myc expression in cOSA and highlight the potential role of PLK1 as an antiproliferative therapeutic target for tumours overexpressing c-Myc.

Circular RNA circFIRRE drives osteosarcoma progression and metastasis through tumorigenic-angiogenic coupling

BackgroundDisappointing clinical efficacy of standard treatment has been proven in refractory metastatic osteosarcoma, and the emerging anti-angiogenic regimens are still in the infantile stage. Thus, there is an urgent need to develop novel therapeutic approach for osteosarcoma lung metastasis.MethodscircFIRRE was selected from RNA-sequencing of 4 matched osteosarcoma and adjacent samples. The expression of circFIRRE was verified in clinical osteosarcoma samples and cell lines via quantitative real-time polymerase chain reaction (RT-qPCR). The effect of circFIRRE was investigated in cell lines in vitro models, ex vivo models and in vivo xenograft tumor models, including proliferation, invasion, migration, metastasis and angiogenesis. Signaling regulatory mechanism was evaluated by RT-qPCR, Western blot, RNA pull-down and dual-luciferase reporter assays.ResultsIn this article, a novel circular RNA, circFIRRE (hsa_circ_0001944) was screened out and identified from RNA-sequencing, and was upregulated in both osteosarcoma cell lines and tissues. Clinically, aberrantly upregulated circFIRRE portended higher metastatic risk and worse prognosis in osteosarcoma patients. Functionally, in vitro, ex vivo and in vivo experiments demonstrated that circFIRRE could drive primary osteosarcoma progression and lung metastasis by inducing both tumor cells and blood vessels, we call as “tumorigenic-angiogenic coupling”. Mechanistically, upregulated circFIRRE was induced by transcription factor YY1, and partially boosted the mRNA and protein level of LUZP1 by sponging miR-486-3p and miR-1225-5p.ConclusionsWe identified circFIRRE as a master regulator in the tumorigenesis and angiogenesis of osteosarcoma, which could be purposed as a novel prognostic biomarker and therapeutic target for refractory osteosarcoma.

Identification and validation of miR-509-5p as a prognosticator for favorable survival in osteosarcoma.

Osteosarcoma (OS) is the most common primary bone cancer diagnosed in children. This study aims to explore the aberrantly expressed miRNAs that are prognostically related and to provide potential biomarkers for the prognosis prediction of OS. The miRNA profiles of OS and adjacent normal controls were obtained from 2 gene expression omnibus cohorts (i.e., GSE28423 and GSE65071). GSE39058 and Therapeutically Applicable Research to Generate Effective Treatments cohorts, which respectively contained 91 and 85 OS samples with both miRNA expression and clinical characteristics, were employed to perform survival and multivariate Cox regression analyses. Lymphocyte infiltration abundance between distinct subgroups was evaluated with the CIBERSORT algorithm and a previously proposed method. Gene set enrichment analysis was used to infer the dysregulated signaling pathways within each subgroup. Of the 31 differentially expressed miRNAs, miR-509-5p (miR-509) was the most significantly prognostic miRNA in the GSE39058 cohort and its high expression was associated with the better OS prognosis (Log-rank P = .008). In the Therapeutically Applicable Research to Generate Effective Treatments validation cohort, the association of high miR-509 expression with favorable survival was also observed (Log-rank P = .014). The results remained still significant even adjusted for clinical confounding factors in multivariate Cox regression models. Further immunology analyses demonstrated that elevated infiltration of lymphocytes, decreased infiltration of immune-suppressive cells, and immune response-related pathways were significantly enriched in patients with miR-509 high expression. Our study suggests that miR-509 may serve as a potential biomarker for evaluating OS prognosis and provides clues for tailoring OS immunotherapy strategies.

Developing a 5-Gene Signature Related to Pyroptosis for Osteosarcoma Patients.

Although the incidence of osteosarcoma (OS) is relatively low compared with other cancer types, the overall survival of metastatic OS was less than 30%. This study aimed to reveal the role of pyroptosis in osteosarcoma and develop a prognostic model related to pyroptosis. Weighted correlation network analysis (WGCNA) was applied to identify key gene modules related to pyroptosis. Univariate Cox regression analysis was used to screen prognostic genes related to pyroptosis. The least absolute shrinkage and selection operator (LASSO) and stepwise Akaike information criterion (stepAIC) were employed to optimize and construct a prognostic model. Five prognostic genes (COL13A1, TNFRSF1A, LILRA6, CTNNBIP1, and CD180) related to pyroptosis were identified. According to the 5-gene signature, OS samples were divided into high- and low-PPRS groups with differential prognosis. Immune-related pathways were more activated in the low-PPRS group. The 5-gene signature was effective and robust to predict OS prognosis. These five prognostic genes were involved in OS development and may serve as new targets for developing therapeutic drugs.

Integrated DNA Copy Number and Expression Profiling Identifies IGF1R as a Prognostic Biomarker in Pediatric Osteosarcoma.

Osteosarcoma is a primary malignant bone tumor arising from bone-forming mesenchymal cells in children and adolescents. Despite efforts to understand the biology of the disease and identify novel therapeutics, the survival of osteosarcoma patients remains dismal. We have concurrently profiled the copy number and gene expression of 226 osteosarcoma samples as part of the Strategic Partnering to Evaluate Cancer Signatures (SPECS) initiative. Our results demonstrate the heterogeneous landscape of osteosarcoma in younger populations by showing the presence of genome-wide copy number abnormalities occurring both recurrently among samples and in a high frequency. Insulin growth factor receptor 1 (IGF1R) is a receptor tyrosine kinase which binds IGF1 and IGF2 to activate downstream pathways involved in cell apoptosis and proliferation. We identify prevalent amplification of IGF1R corresponding with increased gene expression in patients with poor survival outcomes. Our results substantiate previously tenuously associated copy number abnormalities identified in smaller datasets (13q34+, 20p13+, 4q35-, 20q13.33-), and indicate the significance of high fibroblast growth factor receptor 2 (FGFR2) expression in distinguishing patients with poor prognosis. FGFR2 is involved in cellular proliferation processes such as division, growth and angiogenesis. In summary, our findings demonstrate the prognostic significance of several genes associated with osteosarcoma pathogenesis.