The BET PROTAC inhibitor GNE-987 displays anti-tumor effects by targeting super-enhancers regulated gene in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is one of the most common primary malignant tumors of bone in children, which develops from osteoblasts and typically occurs during the rapid growth phase of the bone. Recently, Super-Enhancers(SEs)have been reported to play a crucial role in osteosarcoma growth and metastasis. Therefore, there is an urgent need to identify specific targeted inhibitors of SEs to assist clinical therapy. This study aimed to elucidate the role of BRD4 inhibitor GNE-987 targeting SEs in OS and preliminarily explore its mechanism. METHODS: We evaluated changes in osteosarcoma cells following treatment with a BRD4 inhibitor GNE-987. We assessed the anti-tumor effect of GNE-987 in vitro and in vivo by Western blot, CCK8, flow cytometry detection, clone formation, xenograft tumor size measurements, and Ki67 immunohistochemical staining, and combined ChIP-seq with RNA-seq techniques to find its anti-tumor mechanism. RESULTS: In this study, we found that extremely low concentrations of GNE-987(2-10 nM) significantly reduced the proliferation and survival of OS cells by degrading BRD4. In addition, we found that GNE-987 markedly induced cell cycle arrest and apoptosis in OS cells. Further study indicated that VHL was critical for GNE-987 to exert its antitumor effect in OS cells. Consistent with in vitro results, GNE-987 administration significantly reduced tumor size in xenograft models with minimal toxicity, and partially degraded the BRD4 protein. KRT80 was identified through analysis of the RNA-seq and ChIP-seq data. U2OS HiC analysis suggested a higher frequency of chromatin interactions near the KRT80 binding site. The enrichment of H3K27ac modification at KRT80 was significantly reduced after GNE-987 treatment. KRT80 was identified as playing an important role in OS occurrence and development. CONCLUSIONS: This research revealed that GNE-987 selectively degraded BRD4 and disrupted the transcriptional regulation of oncogenes in OS. GNE-987 has the potential to affect KRT80 against OS.

[Identification of key genes and functions in lung metastasis of osteosarcoma based on bioinformatics].

OBJECTIVE: To screen the differentially expressed genes of lung metastasis of osteosarcoma by bioinformatics, and explore their functions and regulatory networks. METHODS: The data set of GSE14359 was screened from GEO database(http://www.ncbi.nlm.nih.gov/gds) and the differentially expressed gene(DEG) was identified using GEO2R online tool. Download osteosarcoma disease related miRNAs from the online HMMD database(http://www.cuilab.cn/hmdd) and then FunRich software was used to predict the target gene, intersects with DEG to obtains the target gene. The miRNA-mRNA relationship pairs were formed according to the targeted joints, then the data was imported into Cytoscape for visualization, DAVID was used to performe GO and KEGG analysis on target genes, STRING was used to construct PPI network, Cytoscape visualization, CytoHubba plug-in screening central genes and online website for expression and survival analysis. RESULTS: Total 704 DEGs were identified, consisting of 477 up-regulated genes and 227 down regulated genes. FunRich predicted 7 888 mRNAs and 343 target genes were obtained through intersection of the two. KEGG analysis showed that it was mainly involved in focal adhesion, ECM receptor interaction, TNF signal pathway, PI3K-Akt signal pathway, IL-17 signal pathway and MAPK signal pathway. Ten central genes (CCNB1, CHEK1, AURKA, DTL, RRM2, MELK, CEP55, FEN1, KPNA2, TYMS) were identified as potential key genes. Among them, CCNB1, DTL, MELK were highly correlated with poor prognosis. CONCLUSION: The key genes and functional pathways identified in this study may be helpful to understand the molecular mechanism of the occurrence and progression of lung metastases from osteosarcoma, and provide potential therapeutic targets.

Prion-like domain mediated phase separation of ARID1A promotes oncogenic potential of Ewing's sarcoma.

Liquid-liquid phase separation (LLPS) facilitates the formation of membraneless organelles within cells, with implications in various biological processes and disease states. AT-rich interactive domain-containing protein 1A (ARID1A) is a chromatin remodeling factor frequently associated with cancer mutations, yet its functional mechanism remains largely unknown. Here, we find that ARID1A harbors a prion-like domain (PrLD), which facilitates the formation of liquid condensates through PrLD-mediated LLPS. The nuclear condensates formed by ARID1A LLPS are significantly elevated in Ewing's sarcoma patient specimen. Disruption of ARID1A LLPS results in diminished proliferative and invasive abilities in Ewing's sarcoma cells. Through genome-wide chromatin structure and transcription profiling, we identify that the ARID1A condensate localizes to EWS/FLI1 target enhancers and induces long-range chromatin architectural changes by forming functional chromatin remodeling hubs at oncogenic target genes. Collectively, our findings demonstrate that ARID1A promotes oncogenic potential through PrLD-mediated LLPS, offering a potential therapeutic approach for treating Ewing's sarcoma.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

[Prostate cancer with BRCA2 pathogenic mutation: a clinicopathological analysis].

Objective: To analyze the clinicopathological features of prostate cancers with BRCA2 pathogenic mutations, and the association between BRCA2 pathogenic mutation and clinicopathological characteristics. Patient survivals were also examined. Methods: Clinicopathological data of 249 prostate cancer patients who underwent genetic testing in West China Hospital of Sichuan University, Chengdu, China from June 2014 to August 2021 were collected. A retrospective analysis of histopathological morphology, clinicopathological characteristics, and patient survivals was conducted. Results: The genetic testing in the 249 prostate cancer patients showed a pathogenic mutation of DNA damage repair gene (DRG) in 73 cases (73/249, 29.3%), including 22 cases (8.8%) with BRCA2 pathogenic mutation and 51 cases with pathogenic mutations of other DRG. Among the 22 patients with BRCA2 pathogenic mutation, 14 patients (5.6%) harbored germline mutations and 8 patients (3.2%) somatic mutations. Their ages ranged from 48 to 91 years, with a median of 67 years. Seventeen patients (77.3%) had distant metastasis, including 16 cases with bone metastasis and 1 case with multiple metastases. Thirteen patients (59.1%) were castration-resistant prostate cancer. The histological type was mainly classical prostatic acinar adenocarcinoma, including 16 cases (72.7%) with intraductal carcinoma of the prostate (IDC-P). Six cases (27.3%) showed focal neuroendocrine differentiation. Perineural/vascular invasion and extraprostatic extension were seen in 11 cases (50.0%) and 8 cases (36.4%), respectively. The Gleason scores of 19 patients (86.4%) were≥8. IDC-P was more commonly found in patients with BRCA2 germline pathogenic mutation than those with BRCA2 somatic pathogenic mutation, other DRG pathogenic mutation or no-DRG pathogenic mutation (P=0.002). With a total follow-up time of 189 months, the median overall survival (OS) was 132.3 months. Patients with DRG pathogenic mutation had shorter OS than those with no-DRG pathogenic mutation (P=0.040). The OS of patients with BRCA2 germline pathogenic mutation did not significantly differ from that of patients with BRCA2 somatic pathogenic mutation, other DRG pathogenic mutation or no-DRG pathogenic mutation (P=0.216). Conclusions: The presence of BRCA2 gene pathogenic mutation is common in the prostate cancers with high Gleason grade, advanced clinical stage, and castration resistance. IDC-P is more commonly noted in cases with BRCA2 germline pathogenic mutation than those without. Patients with DRG pathogenic mutation have shorter OS than those with no-DRG pathogenic mutation, but there is no significant association between BRCA2 pathogenic mutations and OS.

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.

Assessment of MDM2 Gene Locus Amplification by Fluorescence In-Situ Hybridization in Juvenile Ossifying Fibroma.

Juvenile ossifying fibroma (JOF) is an uncommon benign fibro-osseous lesion (BFOL) of the maxillofacial bones with a locally aggressive nature and a high recurrence rate. Murine Double Minute 2 (MDM2) is an oncogene located at chromosome 12 (12q13-15) that inhibits the tumor suppressor gene TP53. The presence of MDM2 gene locus amplification is a useful molecular adjunct in the evaluation of some sarcomas, including low-grade intramedullary osteosarcoma (LGIOS). JOF and LGIOS have some overlapping clinical and histopathological features. The aim of this study is to evaluate a series of JOF for the presence of MDM2 gene locus amplification using fluorescence in-situ hybridization (FISH). MATERIALS AND METHODS: With IRB approval, a search of the institutional files of the archives of the Oral Pathology and Surgical Pathology biopsy services at the University of Florida Health was performed. The cases were re-evaluated by an oral pathology resident, an oral and maxillofacial pathologist, and a bone and soft tissue pathologist. Cases with consensus in diagnosis were selected (n = 9) for MDM2 testing. Testing by FISH for MDM2 gene locus amplification was applied to all retrieved cases. RESULTS: The examined cases were all negative for MDM2 gene locus amplification via FISH testing. CONCLUSION: In our small series, JOF did not demonstrate MDM2 gene locus abnormality, a characteristic of LGIOS. This finding suggests that JOF has a distinct underlying pathogenesis. If confirmed in a larger series, these findings may be useful in distinguishing these two entities in cases with overlapping features or when minimal biopsy material is available.

Development and experimental validation of hypoxia-related gene signatures for osteosarcoma diagnosis and prognosis based on WGCNA and machine learning.

Osteosarcoma (OS) is the most common primary malignant tumour of the bone with high mortality. Here, we comprehensively analysed the hypoxia signalling in OS and further constructed novel hypoxia-related gene signatures for OS prediction and prognosis. This study employed Gene Set Enrichment Analysis (GSEA), Weighted correlation network analysis (WGCNA) and Least absolute shrinkage and selection operator (LASSO) analyses to identify Stanniocalcin 2 (STC2) and Transmembrane Protein 45A (TMEM45A) as the diagnostic biomarkers, which further assessed by Receiver Operating Characteristic (ROC), decision curve analysis (DCA), and calibration curves in training and test dataset. Univariate and multivariate Cox regression analyses were used to construct the prognostic model. STC2 and metastasis were devised to forge the OS risk model. The nomogram, risk score, Kaplan Meier plot, ROC, DCA, and calibration curves results certified the excellent performance of the prognostic model. The expression level of STC2 and TMEM45A was validated in external datasets and cell lines. In immune cell infiltration analysis, cancer-associated fibroblasts (CAFs) were significantly higher in the low-risk group. And the immune infiltration of CAFs was negatively associated with the expression of STC2 (P < 0.05). Pan-cancer analysis revealed that the expression level of STC2 was significantly higher in Esophageal carcinoma (ESCA), Head and Neck squamous cell carcinoma (HNSC), Kidney renal clear cell carcinoma (KIRC), Lung squamous cell carcinoma (LUSC), and Stomach adenocarcinoma (STAD). Additionally, the higher expression of STC2 was associated with the poor outcome in those cancers. In summary, this study identified STC2 and TMEM45A as novel markers for the diagnosis and prognosis of osteosarcoma, and STC2 was shown to correlate with immune infiltration of CAFs negatively.

MTF2 facilitates the advancement of osteosarcoma through mediating EZH2/SFRP1/Wnt signaling.

BACKGROUND: Osteosarcoma is a soft tissue neoplasm with elevated recurrence risk and highly metastatic potential. Metal response element binding transcriptional factor 2 (MTF2) has been revealed to exert multiple activities in human tissues. The present research was conducted to explore the functions and related response mechanism of MTF2 in osteosarcoma which have not been introduced yet. METHODS: Bioinformatics tools identified the differential MTF2 expression in osteosarcoma tissues. MTF2 expression in osteosarcoma cells was examined with Western blot. Cell Counting Kit-8 (CCK-8) assay, 5-Ethynyl-2'-deoxyuridine (EDU) staining, wound healing as well as transwell assays measured cell proliferation, migration and invasion, respectively. Flow cytometry assay detected the cellular apoptotic level. Western blot also measured the expressions of proteins associated with epithelial mesenchymal transition (EMT), apoptosis and enhancer of zeste homolog 2 (EZH2)/secreted frizzled-related protein 1 (SFRP1)/Wnt signaling. Co-immunoprecipitation (Co-IP) assay confirmed MTF2-EZH2 interaction. RESULTS: MTF2 expression was increased in osteosarcoma tissues and cells. MTF2 interference effectively inhibited the proliferation, migration and invasion of osteosarcoma cells and promoted the cellular apoptotic rate. MTF2 directly bound to EZH2 and MTF2 silence reduced EZH2 expression, activated SFRP1 expression and blocked Wnt signaling in osteosarcoma cells. EZH2 upregulation or SFRP1 antagonist WAY-316606 partly counteracted the impacts of MTF2 down-regulation on the SFRP1/Wnt signaling and the biological phenotypes of osteosarcoma cells. CONCLUSIONS: MTF2 might down-regulate SFRP1 to activate Wnt signaling and drive the progression of osteosarcoma via interaction with EZH2 protein.

IBSP Promotes Breast Cancer Bone Metastasis and Proliferation via BMP-SMAD Signaling Pathway.

BACKGROUND: Integrin-Binding Sialoprotein (IBSP) has been implicated in tumor progression across various cancers. However, the specific role of IBSP in breast cancer remains underexplored. There is a need to investigate the mechanisms by which IBSP influences breast cancer progression and its potential as a therapeutic target. AIMS: This study aims to elucidate the role of IBSP in breast cancer, particularly its impact on tumor progression and its relationship with prognosis. We also seek to understand the underlying mechanisms, including the involvement of the BMP-SMAD signaling pathway, and to explore the potential of targeting IBSP for therapeutic interventions. METHODS AND RESULTS: Overexpression of IBSP in breast cancer cells led to increased migration and invasion, whereas IBSP interference reduced these behaviors, indicating its role in enhancing tumor progression. Differentially expressed genes were significantly enriched in the BMP-SMAD signaling pathway, a critical pathway for osteogenic differentiation. Transcription Factor Binding: Dual luciferase reporter assays demonstrated that SMAD4 specifically binds to the IBSP promoter, establishing a regulatory link between SMAD4 and IBSP expression. Silencing IBSP (si-IBSP) mitigated the effects of SMAD4-induced tumor proliferation, confirming that IBSP acts as a downstream target of SMAD4 in the BMP signaling pathway. CONCLUSION: Our study reveals that IBSP plays a significant role in breast cancer progression through the BMP-SMAD4 signaling pathway. Targeting IBSP could be a promising therapeutic strategy for breast cancer treatment. Further research into IBSP inhibitors may offer new avenues for improving treatment outcomes and managing breast cancer more effectively.

RNF135 Promotes Human Osteosarcoma Cell Growth and Inhibits Apoptosis by Upregulating the PI3K/AKT Pathway.

BACKGROUND: Ring finger protein 135 (RNF135) is an E3 ubiquitin ligase that has been implicated in the tumorigenesis of multiple human malignancies. However, whether RNF135 plays a role in the development of human osteosarcoma (OS) remains unknown. METHODS: RNF135 expression in 20 human OS and 20 human osteochondroma specimens were evaluated by means of immunohistochemistry staining. The effects of shRNA-mediated RNF135 knockdown on human OS cell growth and apoptosis were evaluated through a panel of in vitro studies on cell proliferation, colony formation, exposure of phosphatidylserine on the cell surface, and caspase 3/7 activation. The protein levels of PI3K, AKT, and p-AKT were determined by western blot analysis. RESULTS: We detected significantly higher RNF135 levels in human OS tissues than human osteochondroma tissues. In in vitro studies, shRNA-mediated RNF135 knockdown in human OS cells inhibited proliferation and induced apoptosis. In addition, RNF135 knockdown reduced PI3K and p-AKT protein levels and activated caspase 3 and 7. CONCLUSIONS: These results supported that RNF135 contributes to human OS development through PI3K/AKT-dependent mechanisms. Targeting RNF135 may provide a new therapeutic approach for treating this human malignancy.

Comprehensive transcriptomic analysis of prostate cancer lung metastases.

Metastatic prostate cancer (mPCa) is a widespread disease with high mortality. Unraveling molecular mechanisms of disease progression is of utmost importance. The microenvironment in visceral organs and the skeletal system is of particular interest as a harbinger of metastatic spread. Therefore, we performed a comprehensive transcriptomic analysis of prostate cancer lung metastases with a special focus on differentially expressed genes attributable to the microenvironment. Digital gene expression analysis using the NanoString nCounter analysis system was performed on formalin-fixed, paraffin-embedded (FFPE) tissue from prostate cancer (PCa) lung metastases (n = 24). Data were compared to gene expression data from primary PCa and PCa bone metastases. Bioinformatic analysis was performed using several publicly available tools. In comparison to prostate cancer bone metastases, 209 genes were significantly upregulated, and 100 genes were significantly downregulated in prostate cancer lung metastases. Among the up-regulated genes, the top 10 genes with the most significant P-value were HLA-DPB1, PTPRC, ITGB7, C3, CCL21, CCL5, ITGAM, SERPINA1, MFAP4, ARAP2 and among the down-regulated genes, the top 10 genes with the most significant P-value were FOXC2, TWIST1, CDK14, CHAD, IBSP, EPN3, VIT, HAPLN1, SLC44A4, TBX1. In PCa lung metastases genes associated with immunogenic responses were upregulated while genes associated with epithelial-mesenchymal transition were down-regulated. We also showed that CXCR3/CXCL10 axis plays a significant role in prostate cancer lung metastases in comparison to bone metastases. In this study, we comprehensively explored transcriptomic alterations in PCa lung metastases in comparison to primary PCa and PCa bone metastases. In PCa lung metastases genes associated with immunogenic responses are upregulated while genes associated with epithelial-mesenchymal transition are down-regulated. This points to a more immunogenic phenotype of PCa lung metastases thus potentially making patients more susceptible to immunotherapeutic approaches.

The expression and clinical significance of ARHGAP25 in osteosarcoma based on bioinformatics analysis.

ARHGAP25, a member of the ARHGAP family, encodes a negative regulator of Rho-GTPase that is important for actin remodeling, cell polarity, and cell migration. ARHGAP25 is down-regulated in a variety of solid tumors and promotes cancer cell growth, migration, and invasion. However, nothing is understood about ARHGAP25's biological function in osteosarcoma. This work used qPCR and WB to confirm the expression of ARHGAP25 in osteosarcoma following the initial analysis of its expression in pan-cancer. For GO and KEGG analysis, we have chosen 300 genes from the TARGET osteosarcoma data that had the strongest positive correlation with ARHGAP25, and we created nomogram and calibration charts. We simultaneously overexpressed ARHGAP25 in osteosarcoma cells to examine its impact on apoptosis and proliferation. By using MSP, we determined their methylation status in osteosarcoma cells and normal bone cells. We observed that ARHGAP25 was significantly downregulated in a range of malignancies, including osteosarcoma, and was associated with poor patient outcomes. The decrease of ARHGAP25 expression in osteosarcoma is related to DNA methylation. Overexpression of ARHGAP25 induced apoptosis and inhibited the proliferation of osteosarcoma cells in vitro. In addition, ARHGAP25 is also associated with immune-related pathways in osteosarcoma. These findings suggest that ARHGAP25 is a valuable prognostic biomarker in osteosarcoma patients.

Multi-omic validation of the cuproptosis-sphingolipid metabolism network: modulating the immune landscape in osteosarcoma.

Background: The current understanding of the mechanisms by which metal ion metabolism promotes the progression and drug resistance of osteosarcoma remains incomplete. This study aims to elucidate the key roles and mechanisms of genes involved in cuproptosis-related sphingolipid metabolism (cuproptosis-SPGs) in regulating the immune landscape, tumor metastasis, and drug resistance in osteosarcoma cells. Methods: This study employed multi-omics approaches to assess the impact of cuproptosis-SPGs on the prognosis of osteosarcoma patients. Lasso regression analysis was utilized to construct a prognostic model, while multivariate regression analysis was applied to identify key core genes and generate risk coefficients for these genes, thereby calculating a risk score for each osteosarcoma patient. Patients were then stratified into high-risk and low-risk groups based on their risk scores. The ESTIMATE and CIBERSORT algorithms were used to analyze the level of immune cell infiltration within these risk groups to construct the immune landscape. Single-cell analysis was conducted to provide a more precise depiction of the expression patterns of cuproptosis-SPGs among immune cell subtypes. Finally, experiments on osteosarcoma cells were performed to validate the role of the cuproptosis-sphingolipid signaling network in regulating cell migration and apoptosis. Results: In this study, seven cuproptosis-SPGs were identified and used to construct a prognostic model for osteosarcoma patients. In addition to predicting survival, the model also demonstrated reliability in forecasting the response to chemotherapy drugs. The results showed that a high cuproptosis-sphingolipid metabolism score was closely associated with reduced CD8 T cell infiltration and indicated poor prognosis in osteosarcoma patients. Cellular functional assays revealed that cuproptosis-SPGs regulated the LC3B/ERK signaling pathway, thereby triggering cell death and impairing migration capabilities in osteosarcoma cells. Conclusion: The impact of cuproptosis-related sphingolipid metabolism on the survival and migration of osteosarcoma cells, as well as on CD8 T cell infiltration, highlights the potential of targeting copper ion metabolism as a promising strategy for osteosarcoma patients.

The whole transcriptome analysis using FFPE and fresh tissue samples identifies the molecular fingerprint of osteosarcoma.

Osteosarcoma is a form of bone cancer that predominantly impacts osteoblasts, the cells responsible for creating fresh bone tissue. Typical indications include bone pain, inflammation, sensitivity, mobility constraints, and fractures. Utilising imaging techniques such as X-rays, MRI scans, and CT scans can provide insights into the size and location of the tumour. Additionally, a biopsy is employed to confirm the diagnosis. Analysing genes with distinct expression patterns unique to osteosarcoma can be valuable for early detection and the development of effective treatment approaches. In this research, we comprehensively examined the entire transcriptome and pinpointed genes with altered expression profiles specific to osteosarcoma. The study mainly aimed to identify the molecular fingerprint of osteosarcoma. In this study, we processed 90 FFPE samples from PathWest with an almost equal number of osteosarcoma and healthy tissues. RNA was extracted from Paraffin-embedded tissue; RNA was sequenced, the sequencing data was analysed, and gene expression was compared to the healthy samples of the same patients. Differentially expressed genes in osteosarcoma-derived samples were identified, and the functions of those genes were explored. This result was combined with our previous studies based on FFPE and fresh samples to perform a meta-analysis. We identified 1,500 identical differentially expressed genes in PathWest osteosarcoma samples compared to normal tissue samples of the same patients. Meta-analysis with combined fresh tissue samples identified 530 differentially expressed genes. IFITM5, MMP13, PANX3, and MAGEA6 were some of the most overexpressed genes in osteosarcoma samples, while SLC4A1, HBA1, HBB, AQP7 genes were some of the top downregulated genes. Through the meta-analysis, 530 differentially expressed genes were identified to be identical among FFPE (105 FFPE samples) and 36 fresh bone samples. Deconvolution analysis with single-cell RNAseq data confirmed the presence of specific cell clusters in FFPE samples. We propose these 530 DEGs as a molecular fingerprint of osteosarcoma.

LncRNAs as potential prognosis/diagnosis markers and factors driving drug resistance of osteosarcoma, a review.

Osteosarcoma is a common malignancy that often occurs in children, teenagers and young adults. Although the treatment strategy has improved, the results are still poor for most patients with metastatic or recurrent osteosarcomas. Therefore, it is necessary to identify new and effective prognostic biomarkers and therapeutic targets for diseases. Human genomes contain lncRNAs, transcripts with limited or insufficient capacity to encode proteins. They have been implicated in tumorigenesis, particularly regarding the onset, advancement, resistance to treatment, recurrence and remote dissemination of malignancies. Aberrant lncRNA expression in osteosarcomas has been reported by numerous researchers; lncRNAs have the potential to exhibit either oncogenic or tumor-suppressing behaviors and thus, to govern the advancement of this skeletal cancer. They are suspected to influence osteosarcoma cell growth, replication, invasion, migration, remote dissemination and programmed cell death. Additionally, they have been recognized as clinical markers, and may participate in the development of multidrug resistance. Therefore, the study of lncRNAs in the growth, metastasis, treatment and prognosis of osteosarcoma is very important for the active prevention and treatment of osteosarcoma. Consequently, this work reviews the functions of lncRNAs.

A novel prognostic signature related to programmed cell death in osteosarcoma.

Background: Osteosarcoma primarily affects children and adolescents, with current clinical treatments often resulting in poor prognosis. There has been growing evidence linking programmed cell death (PCD) to the occurrence and progression of tumors. This study aims to enhance the accuracy of OS prognosis assessment by identifying PCD-related prognostic risk genes, constructing a PCD-based OS prognostic risk model, and characterizing the function of genes within this model. Method: We retrieved osteosarcoma patient samples from TARGET and GEO databases, and manually curated literature to summarize 15 forms of programmed cell death. We collated 1621 PCD genes from literature sources as well as databases such as KEGG and GSEA. To construct our model, we integrated ten machine learning methods including Enet, Ridge, RSF, CoxBoost, plsRcox, survivalSVM, Lasso, SuperPC, StepCox, and GBM. The optimal model was chosen based on the average C-index, and named Osteosarcoma Programmed Cell Death Score (OS-PCDS). To validate the predictive performance of our model across different datasets, we employed three independent GEO validation sets. Moreover, we assessed mRNA and protein expression levels of the genes included in our model, and investigated their impact on proliferation, migration, and apoptosis of osteosarcoma cells by gene knockdown experiments. Result: In our extensive analysis, we identified 30 prognostic risk genes associated with programmed cell death (PCD) in osteosarcoma (OS). To assess the predictive power of these genes, we computed the C-index for various combinations. The model that employed the random survival forest (RSF) algorithm demonstrated superior predictive performance, significantly outperforming traditional approaches. This optimal model included five key genes: MTM1, MLH1, CLTCL1, EDIL3, and SQLE. To validate the relevance of these genes, we analyzed their mRNA and protein expression levels, revealing significant disparities between osteosarcoma cells and normal tissue cells. Specifically, the expression levels of these genes were markedly altered in OS cells, suggesting their critical role in tumor progression. Further functional validation was performed through gene knockdown experiments in U2OS cells. Knockdown of three of these genes-CLTCL1, EDIL3, and SQLE-resulted in substantial changes in proliferation rate, migration capacity, and apoptosis rate of osteosarcoma cells. These findings underscore the pivotal roles of these genes in the pathophysiology of osteosarcoma and highlight their potential as therapeutic targets. Conclusion: The five genes constituting the OS-PCDS model-CLTCL1, MTM1, MLH1, EDIL3, and SQLE-were found to significantly impact the proliferation, migration, and apoptosis of osteosarcoma cells, highlighting their potential as key prognostic markers and therapeutic targets. OS-PCDS enables accurate evaluation of the prognosis in patients with osteosarcoma.

The Variable Genomic Landscape During Osteosarcoma Progression: Insights From a Longitudinal WGS Analysis.

Osteosarcoma is a primary bone tumor that exhibits a complex genomic landscape characterized by gross chromosomal abnormalities. Osteosarcoma patients often develop metastatic disease, resulting in limited therapeutic options and poor survival rates. To gain knowledge on the mechanisms underlying osteosarcoma heterogeneity and metastatic process, it is important to obtain a detailed profile of the genomic alterations that accompany osteosarcoma progression. We performed WGS on multiple tissue samples from six patients with osteosarcoma, including the treatment naïve biopsy of the primary tumor, resection of the primary tumor after neoadjuvant chemotherapy, local recurrence, and distant metastases. A comprehensive analysis of single-nucleotide variants (SNVs), structural variants, copy number alterations (CNAs), and chromothripsis events revealed the genomic heterogeneity during osteosarcoma progression. SNVs and structural variants were found to accumulate over time, contributing to an increased complexity of the genome of osteosarcoma during disease progression. Phylogenetic trees based on SNVs and structural variants reveal distinct evolutionary patterns between patients, including linear, neutral, and branched patterns. The majority of osteosarcomas showed variable copy number profiles or gained whole-genome doubling in later occurrences. Large proportions of the genome were affected by loss of heterozygosity (LOH), although these regions remain stable during progression. Additionally, chromothripsis is not confined to a single early event, as multiple other chromothripsis events may appear in later occurrences. Together, we provide a detailed analysis of the complex genome of osteosarcomas and show that five of six osteosarcoma genomes are highly dynamic and variable during progression.