Circular RNA IARS modulates the progression and ferroptosis of osteosarcoma via sponging miR-188-5p from RAB14.

Osteosarcoma (OS) is a common primary bone tumor in children and adolescents. Circular RNA (circRNA)-IARS acts as an oncogene in multiple human tumors. However, the circ-IARS function in OS is unclear. This research aimed to elucidate the roles and mechanisms of circ-IARS in OS. In this study, circ-IARS expressions were raised in OS tissues and cells. circ-IARS expressions were closely related to clinical stage and distant metastasis. Furthermore, overall survival rates were reduced in OS patients with high circ-IARS levels. Also, silencing circ-IARS weakened OS cell proliferation and invasion, yet enhanced cell ferroptosis. Mechanistically, circ-IARS targeted miR-188-5p to regulate RAB14 expressions in OS cells. Moreover, circ-IARS knockdown repressed OS cell proliferation, invasion, and induced ferroptosis, yet these impacts were abolished by co-transfection with anti-miR-188-5p or pcDNA-RAB14. Meanwhile, interference with circ-IARS reduced OS cell proliferation, and decreased RAB14 (a member of the RAS oncogene family), GPX4, and xCT (crucial ferroptosis regulators) expressions in vivo. In conclusion, circ-IARS facilitated OS progression via miR-188-5p/RAB14.

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.

A case series of osseous metastases in patients with glioblastoma.

BACKGROUND: Extracranial metastases occur in <2% of cases of glioblastoma (GBM). When metastases do occur, bone is the most common destination. Herein, we review clinical characteristics of GBM patients with osseous metastases and evaluate both potential risk factors and prognostic significance. METHODS: Using an institutional database, we identified and retrospectively analyzed 6 patients with both GBM and osseous metastases. We collected data on patient demographics, tumor genetics, clinical courses, and outcomes. Given the rarity of metastatic GBM, we conducted historical comparisons using previously published literature. RESULTS: Five patients with osseous metastases (83%) were male, with a median age of 46 years at GBM diagnosis (range: 20-84). All patients had IDH-wildtype, MGMT promoter unmethylated GBM and 5 (83%) had alterations in TP53. All patients underwent surgical resection for GBM followed by radiation with concurrent and adjuvant temozolomide. Four patients (67%) received bevacizumab prior to bone metastasis diagnosis. Bone metastases were discovered at a median of 12.2 months (range: 5.3-35.2) after GBM diagnosis and 4.8 months after starting bevacizumab (range: 3.5-13.2). Three patients (50%) received immunotherapy. After osseous metastasis diagnosis, the median survival was 25 days (range: 13-225). CONCLUSION: In our cohort, most patients were male and young at the time of GBM diagnosis. All patients had IDH-wildtype, MGMT promoter unmethylated GBM, and most had alterations in TP53, which may be important for osseous metastasis. Most patients received bevacizumab, which has been associated with earlier metastasis. Osseous metastases of GBM occur and portend a dismal prognosis in an already aggressive malignancy.

Integrated machine learning algorithms reveal a bone metastasis-related signature of circulating tumor cells in prostate cancer.

Bone metastasis is an essential factor affecting the prognosis of prostate cancer (PCa), and circulating tumor cells (CTCs) are closely related to distant tumor metastasis. Here, the protein-protein interaction (PPI) networks and Cytoscape application were used to identify diagnostic markers for metastatic events in PCa. We screened ten hub genes, eight of which had area under the ROC curve (AUC) values > 0.85. Subsequently, we aim to develop a bone metastasis-related model relying on differentially expressed genes in CTCs for accurate risk stratification. We developed an integrative program based on machine learning algorithm combinations to construct reliable bone metastasis-related genes prognostic index (BMGPI). On the basis of BMGPI, we carefully evaluated the prognostic outcomes, functional status, tumor immune microenvironment, somatic mutation, copy number variation (CNV), response to immunotherapy and drug sensitivity in different subgroups. BMGPI was an independent risk factor for disease-free survival in PCa. The high risk group demonstrated poor survival as well as higher immune scores, higher tumor mutation burden (TMB), more frequent co-occurrence mutation, and worse efficacy of immunotherapy. This study highlights a new prognostic signature, the BMGPI. BMGPI is an independent predictor of prognosis in PCa patients and is closely associated with the immune microenvironment and the efficacy of immunotherapy.

Cadherin-11 contributes to the heterogenous and dynamic Wnt-Wnt-ß-catenin pathway activation in Ewing sarcoma.

Ewing sarcoma is the second most common bone cancer in children, and while patients who present with metastatic disease at the time of diagnosis have a dismal prognosis. Ewing sarcoma tumors are driven by the fusion gene EWS/Fli1, and while these tumors are genetically homogenous, the transcriptional heterogeneity can lead to a variety of cellular processes including metastasis. In this study, we demonstrate that in Ewing sarcoma cells, the canonical Wnt/ß-Catenin signaling pathway is heterogeneously activated in vitro and in vivo, correlating with hypoxia and EWS/Fli1 activity. Ewing sarcoma cells predominantly express ß-Catenin on the cell membrane bound to CDH11, which can respond to exogenous Wnt ligands leading to the immediate activation of Wnt/ß-Catenin signaling within a tumor. Knockdown of CDH11 leads to delayed and decreased response to exogenous Wnt ligand stimulation, and ultimately decreased metastatic propensity. Our findings strongly indicate that CDH11 is a key component of regulating Wnt//ß-Catenin signaling heterogeneity within Ewing sarcoma tumors, and is a promising molecular target to alter Wnt//ß-Catenin signaling in Ewing sarcoma patients.

MATN4 as a target gene of HIF-1α promotes the proliferation and metastasis of osteosarcoma.

BACKGROUND: Osteosarcoma is a highly malignant bone tumor that exhibits rapid growth and early metastasis. Hypoxia plays a pivotal role in promoting the proliferation and metastasis of osteosarcoma through a series of molecular events, which are partially mediated and regulated by HIF-1α. However, the regulatory network associated with HIF-1α in osteosarcoma remains limited. Therefore, the objective of this study was to identify critical hypoxia-associated genes and investigate their effects and molecular mechanisms in osteosarcoma cells. METHODS: Through bioinformatics analysis, matrilin-4 (MATN4) was identified as a crucial gene associated with hypoxia. The expression of MATN4 and HIF-1α was assessed using immunohistochemistry, RT-qPCR, and western blotting. The proliferative capacity of osteosarcoma cells was assessed through the utilization of CCK-8, EDU staining, and colony formation assays. The effects of MATN4 on the mobility of OS cells were evaluated using wound-healing assays and transwell assays. The interaction between MATN4 and HIF-1α was detected through chromatin immunoprecipitation. RESULTS: MATN4 is overexpressed in osteosarcoma tissue and cells, particularly in osteosarcoma cells with high metastatic potential. Knockdown of MATN4 inhibits the proliferation, migration, and invasion abilities of osteosarcoma cells and reverses the promoting effects of hypoxia on these functions. Additionally, HIF-1α binds to MATN4 and upregulates its expression. Interestingly, knockdown of HIF-1α reduces the stimulatory effects of MATN4 overexpression on the proliferation, migration, and invasion of osteosarcoma cells under hypoxic conditions. CONCLUSIONS: Taken together, our results suggest that MATN4 is regulated by HIF-1α and confers a more aggressive phenotype on OS cells. This evidence suggests that MATN4 may act as a potential target for OS diagnosis and treatment.

DNA-PKcs Inhibition Sensitizes Human Chondrosarcoma Cells to Carbon Ion Irradiation via Cell Cycle Arrest and Telomere Capping Disruption.

In order to overcome the resistance to radiotherapy in human chondrosarcoma cells, the prevention from efficient DNA repair with a combined treatment with the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) inhibitor AZD7648 was explored for carbon ion (C-ion) as well as reference photon (X-ray) irradiation (IR) using gene expression analysis, flow cytometry, protein phosphorylation, and telomere length shortening. Proliferation markers and cell cycle distribution changed significantly after combined treatment, revealing a prominent G2/M arrest. The expression of the G2/M checkpoint genes cyclin B, CDK1, and WEE1 was significantly reduced by IR alone and the combined treatment. While IR alone showed no effects, additional AZD7648 treatment resulted in a dose-dependent reduction in AKT phosphorylation and an increase in Chk2 phosphorylation. Twenty-four hours after IR, the key genes of DNA repair mechanisms were reduced by the combined treatment, which led to impaired DNA repair and increased radiosensitivity. A time-dependent shortening of telomere length was observed in both cell lines after combined treatment with AZD7648 and 8 Gy X-ray/C-ion IR. Our data suggest that the inhibition of DNA-PKcs may increase sensitivity to X-rays and C-ion IR by impairing its functional role in DNA repair mechanisms and telomere end protection.

High expression of DEC2 distinguishes chondroblastic osteosarcoma and promotes tumour growth by activating the VEGFC/VEGFR2 signalling pathway.

Osteosarcoma (OS) is the most common primary malignant bone tumour in children and young adults. Account for 80% of all OS cases, conventional OS are characterized by the presence of osteoblastic, chondroblastic and fibroblastic cell types. Despite this heterogeneity, therapeutic treatment and prognosis of OS are essentially the same for all OS subtypes. Here, we report that DEC2, a transcriptional repressor, is expressed at higher levels in chondroblastic OS compared with osteoblastic OS. This difference suggests that DEC2 is disproportionately involved in the progression of chondroblastic OS, and thus, DEC2 may represent a possible molecular target for treating this type of OS. In the human chondroblastic-like OS cell line MNNG/HOS, we found that overexpression of DEC2 affects the proliferation of the cells by activating the VEGFC/VEGFR2 signalling pathway. Enhanced expression of DEC2 increased VEGFR2 expression, as well as increased the phosphorylation levels at sites Y951 and Y1175 of VEGFR2. On the one hand, activation of VEGFR2Y1175 enhanced cell proliferation through VEGFR2Y1175-PLCγ1-PKC-SPHK-MEK-ERK signalling. On the other hand, activation of VEGFR2Y951 decreased mitochondria-dependent apoptosis rate through VEGFR2Y951-VARP-PI3K-AKT signalling. Activation of these two signalling pathways resulted in enhanced progression of chondroblastic OS. In conclusion, DEC2 plays a pivotal role in cell proliferation and apoptosis-resistance in chondroblastic OS via the VEGFC/VEGFR2 signalling pathway. These findings lay the groundwork for developing focused treatments that target specific types of OS.

METTL3 promotes the progression of osteosarcoma through the N6-methyladenosine modification of MCAM via IGF2BP1.

BACKGROUND: The molecular mechanisms of osteosarcoma (OS) are complex. In this study, we focused on the functions of melanoma cell adhesion molecule (MCAM), methyltransferase 3 (METTL3) and insulin like growth factor 2 mRNA binding protein 1 (IGF2BP1) in OS development. METHODS: qRT-PCR assay and western blot assay were performed to determine mRNA and protein expression of MCAM, METTL3, IGF2BP1 and YY1. MTT assay and colony formation assay were conducted to assess cell proliferation. Cell apoptosis, invasion and migration were evaluated by flow cytometry analysis, transwell assay and wound-healing assay, respectively. Methylated RNA Immunoprecipitation (MeRIP), dual-luciferase reporter, Co-IP, RIP and ChIP assays were performed to analyze the relationships of MCAM, METTL3, IGF2BP1 and YY1. The functions of METTL3 and MCAM in tumor growth were explored through in vivo experiments. RESULTS: MCAM was upregulated in OS, and MCAM overexpression promoted OS cell growth, invasion and migration and inhibited apoptosis. METTL3 and IGF2BP1 were demonstrated to mediate the m6A methylation of MCAM. Functionally, METTL3 or IGF2BP1 silencing inhibited OS cell progression, while MCAM overexpression ameliorated the effects. Transcription factor YY1 promoted the transcription level of METTL3 and regulated METTL3 expression in OS cells. Additionally, METTL3 deficiency suppressed tumor growth in vivo, while MCAM overexpression abated the effect. CONCLUSION: YY1/METTL3/IGF2BP1/MCAM axis aggravated OS development, which might provide novel therapy targets for OS.

Research progress on the role of lncRNA, circular RNA, and microRNA networks in regulating ferroptosis in osteosarcoma.

Noncoding RNAs (ncRNAs) do not participate in protein-coding. Ferroptosis is a newly discovered form of cell death mediated by reactive oxygen species and lipid peroxidation. Recent studies have shown that ncRNAs such as microRNAs, long noncoding RNAs, circular RNAs, and ferroptosis are involved in the occurrence and development of osteosarcoma (OS). Studies have confirmed that ncRNAs participate in the development of OS by regulating the ferroptosis. However, systematic summary on this topic are still lacking. This review summarises the potential role of ncRNAs in the diagnosis, treatment, drug resistance, and prognosis of OS and the basis for diagnosing, preventing, and treating clinical OS and developing effective drugs. This review summarises the latest research progress on ncRNAs that regulate ferroptosis in OS, attempts to clarify the molecular mechanisms by which ncRNAs regulate ferroptosis in the pathogenesis of OS, and elaborates on the involvement of ferroptosis in OS from the perspective of ncRNAs.

PDE1B, a potential biomarker associated with tumor microenvironment and clinical prognostic significance in osteosarcoma.

PDE1B had been found to be involved in various diseases, including tumors and non-tumors. However, little was known about the definite role of PDE1B in osteosarcoma. Therefore, we mined public data on osteosarcoma to reveal the prognostic values and immunological roles of the PDE1B gene. Three osteosarcoma-related datasets from online websites were utilized for further data analysis. R 4.3.2 software was utilized to conduct difference analysis, prognostic analysis, gene set enrichment analysis (GSEA), nomogram construction, and immunological evaluations, respectively. Experimental verification of the PDE1B gene in osteosarcoma was conducted by qRT-PCR and western blot, based on the manufacturer's instructions. The PDE1B gene was discovered to be lowly expressed in osteosarcoma, and its low expression was associated with poor OS (all P < 0.05). Experimental verifications by qRT-PCR and western blot results remained consistent (all P < 0.05). Univariate and multivariate Cox regression analyses indicated that the PDE1B gene had independent abilities in predicting OS in the TARGET osteosarcoma dataset (both P < 0.05). GSEA revealed that PDE1B was markedly linked to the calcium, cell cycle, chemokine, JAK STAT, and VEGF pathways. Moreover, PDE1B was found to be markedly associated with immunity (all P < 0.05), and the TIDE algorithm further shed light on that patients with high-PDE1B expression would have a better immune response to immunotherapies than those with low-PDE1B expression, suggesting that the PDE1B gene could prevent immune escape from osteosarcoma. The PDE1B gene was found to be a tumor suppressor gene in osteosarcoma, and its high expression was related to a better OS prognosis, suppressing immune escape from osteosarcoma.

DNA Mutational and Copy Number Variation Profiling of Primary Craniofacial Osteosarcomas by Next-Generation Sequencing.

BACKGROUND: Craniofacial osteosarcomas (CFOS) are uncommon malignant neoplasms of the head and neck with different clinical presentation, biological behavior and prognosis from conventional osteosarcomas of long bones. Very limited genetic data have been published on CFOS. METHODS: In the current study, we performed comprehensive genomic studies in 15 cases of high-grade CFOS by SNP array and targeted next generation sequencing. RESULT: Our study shows high-grade CFOS demonstrate highly complex and heterogenous genomic alterations and harbor frequently mutated tumor suppressor genes TP53, CDKN2A/B, and PTEN, similar to conventional osteosarcomas. Potentially actionable gene amplifications involving CCNE1, AKT2, MET, NTRK1, PDGFRA, KDR, KIT, MAP3K14, FGFR1, and AURKA were seen in 43% of cases. GNAS hotspot activating mutations were also identified in a subset of CFOS cases, with one case representing malignant transformation from fibrous dysplasia, suggesting a role for GNAS mutation in the development of CFOS. CONCLUSION: High-grade CFOS demonstrate highly complex and heterogenous genomic alterations, with amplification involving receptor tyrosine kinase genes, and frequent mutations involving tumor suppressor genes.

Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.

Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poor prognosis. The existence of tumor heterogeneity leads to different molecular subtypes and survival outcomes. Recently, lipid metabolism has been identified as a critical characteristic of cancer. Therefore, our study aims to identify osteosarcoma's lipid metabolism molecular subtype and develop a signature for survival outcome prediction. Four multicenter cohorts-TARGET-OS, GSE21257, GSE39058, and GSE16091-were amalgamated into a unified Meta-Cohort. Through consensus clustering, novel molecular subtypes within Meta-Cohort patients were delineated. Subsequent feature selection processes, encompassing analyses of differentially expressed genes between subtypes, univariate Cox analysis, and StepAIC, were employed to pinpoint biomarkers related to lipid metabolism in TARGET-OS. We selected the most effective algorithm for constructing a Lipid Metabolism-Related Signature (LMRS) by utilizing four machine-learning algorithms reconfigured into ten unique combinations. This selection was based on achieving the highest concordance index (C-index) in the test cohort of GSE21257, GSE39058, and GSE16091. We identified two distinct lipid metabolism molecular subtypes in osteosarcoma patients, C1 and C2, with significantly different survival rates. C1 is characterized by increased cholesterol, fatty acid synthesis, and ketone metabolism. In contrast, C2 focuses on steroid hormone biosynthesis, arachidonic acid, and glycerolipid and linoleic acid metabolism. Feature selection in the TARGET-OS identified 12 lipid metabolism genes, leading to a model predicting osteosarcoma patient survival. The LMRS, based on the 12 identified genes, consistently accurately predicted prognosis across TARGET-OS, testing cohorts, and Meta-Cohort. Incorporating 12 published signatures, LMRS showed robust and significantly superior predictive capability. Our results offer a promising tool to enhance the clinical management of osteosarcoma, potentially leading to improved clinical outcomes.

Identification of hub genes related to metastasis and prognosis of osteosarcoma and establishment of a prognostic model with bioinformatic methods.

Osteosarcoma (OS) is the most common primary malignant bone tumor occurring in children and adolescents. Improvements in our understanding of the OS pathogenesis and metastatic mechanism on the molecular level might lead to notable advances in the treatment and prognosis of OS. Biomarkers related to OS metastasis and prognosis were analyzed and identified, and a prognostic model was established through the integration of bioinformatics tools and datasets in multiple databases. 2 OS datasets were downloaded from the Gene Expression Omnibus database for data consolidation, standardization, batch effect correction, and identification of differentially expressed genes (DEGs); following that, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs; the STRING database was subsequently used for protein-protein interaction (PPI) network construction and identification of hub genes; hub gene expression was validated, and survival analysis was conducted through the employment of the TARGET database; finally, a prognostic model was established and evaluated subsequent to the screening of survival-related genes. A total of 701 DEGs were identified; by gene ontology and KEGG pathway enrichment analyses, the overlapping DEGs were enriched for 249 biological process terms, 13 cellular component terms, 35 molecular function terms, and 4 KEGG pathways; 13 hub genes were selected from the PPI network; 6 survival-related genes were identified by the survival analysis; the prognostic model suggested that 4 genes were strongly associated with the prognosis of OS. DEGs related to OS metastasis and survival were identified through bioinformatics analysis, and hub genes were further selected to establish an ideal prognostic model for OS patients. On this basis, 4 protective genes including TPM1, TPM2, TPM3, and TPM4 were yielded by the prognostic model.

Osteosarcoma in a ceRNET perspective.

Osteosarcoma (OS) is the most prevalent and fatal type of bone tumor. It is characterized by great heterogeneity of genomic aberrations, mutated genes, and cell types contribution, making therapy and patients management particularly challenging. A unifying picture of molecular mechanisms underlying the disease could help to transform those challenges into opportunities.This review deeply explores the occurrence in OS of large-scale RNA regulatory networks, denominated "competing endogenous RNA network" (ceRNET), wherein different RNA biotypes, such as long non-coding RNAs, circular RNAs and mRNAs can functionally interact each other by competitively binding to shared microRNAs. Here, we discuss how the unbalancing of any network component can derail the entire circuit, driving OS onset and progression by impacting on cell proliferation, migration, invasion, tumor growth and metastasis, and even chemotherapeutic resistance, as distilled from many studies. Intriguingly, the aberrant expression of the networks components in OS cells can be triggered also by the surroundings, through cytokines and vesicles, with their bioactive cargo of proteins and non-coding RNAs, highlighting the relevance of tumor microenvironment. A comprehensive picture of RNA regulatory networks underlying OS could pave the way for the development of innovative RNA-targeted and RNA-based therapies and new diagnostic tools, also in the perspective of precision oncology.

Co-targeting JAK1/STAT6/GAS6/TAM signaling improves chemotherapy efficacy in Ewing sarcoma.

Ewing sarcoma is a pediatric bone and soft tissue tumor treated with chemotherapy, radiation, and surgery. Despite intensive multimodality therapy, ~50% patients eventually relapse and die of the disease due to chemoresistance. Here, using phospho-profiling, we find Ewing sarcoma cells treated with chemotherapeutic agents activate TAM (TYRO3, AXL, MERTK) kinases to augment Akt and ERK signaling facilitating chemoresistance. Mechanistically, chemotherapy-induced JAK1-SQ phosphorylation releases JAK1 pseudokinase domain inhibition allowing for JAK1 activation. This alternative JAK1 activation mechanism leads to STAT6 nuclear translocation triggering transcription and secretion of the TAM kinase ligand GAS6 with autocrine/paracrine consequences. Importantly, pharmacological inhibition of either JAK1 by filgotinib or TAM kinases by UNC2025 sensitizes Ewing sarcoma to chemotherapy in vitro and in vivo. Excitingly, the TAM kinase inhibitor MRX-2843 currently in human clinical trials to treat AML and advanced solid tumors, enhances chemotherapy efficacy to further suppress Ewing sarcoma tumor growth in vivo. Our findings reveal an Ewing sarcoma chemoresistance mechanism with an immediate translational value.

PSMD14 is a novel prognostic marker and therapeutic target in osteosarcoma.

BACKGROUND: Osteosarcoma is a bone tumor that is characterized by high malignancy and a high mortality rate, and that originates from primitive osteoblastic mesenchymal cells and is most common in rapidly growing long bones. PSMD14, also known as RPN11 or POH1, is a member of the JAMM isopeptidase family, which is able to remove the substrate protein ubiquitination label, thereby regulating the stability and function of the substrate protein. In this study, we explored the expression and potential biological significance of the PSMD14 deubiquitinating enzyme in osteosarcoma. METHODS: Immunohistochemical methods were used to detect the expression of PSMD14 in biopsies of 91 osteosarcoma patients, and the specimens were classified into high and low PSMD14 expression groups. The correlation between PSMD14 expression and clinical indicators and prognosis was compared.SiRNA was used to downregulate PSMD14 in two osteosarcoma cell lines (HOS and SJSA-1), and the effects of downregulation of PSMD14 on the viability, proliferation, and invasion ability of osteosarcoma cells were analyzed. RESULTS: We identified significant differences in recurrence, metastasis, and survival time of the osteosarcoma patients on the basis of PSMD14 expression. High expression of PSMD14 in osteosarcoma patients was associated with a low survival rate and high risk of metastasis and recurrence. Down-regulation of PSMD14 inhibited the viability, proliferation, and invasiveness of osteosarcoma cell lines. CONCLUSIONS: PSMD14 may be a new prognostic marker and therapeutic target for osteosarcoma.

Emerging Treatments Targeting the Tumor Microenvironment for Advanced Chondrosarcoma.

Chondrosarcoma (ChS), a malignant cartilage-producing tumor, is the second most frequently diagnosed osseous sarcoma after osteosarcoma. It represents a very heterogeneous group of malignant chemo- and radiation-resistant neoplasms, accounting for approximately 20% of all bone sarcomas. The majority of ChS patients have a good prognosis after a complete surgical resection, as these tumors grow slowly and rarely metastasize. Conversely, patients with inoperable disease, due to the tumor location, size, or metastases, represent a great clinical challenge. Despite several genetic and epigenetic alterations that have been described in distinct ChS subtypes, very few therapeutic options are currently available for ChS patients. Therefore, new prognostic factors for tumor progression as well as new treatment options have to be explored, especially for patients with unresectable or metastatic disease. Recent studies have shown that a correlation between immune infiltrate composition, tumor aggressiveness, and survival does exist in ChS patients. In addition, the intra-tumor microvessel density has been proven to be associated with aggressive clinical behavior and a high metastatic potential in ChS. This review will provide an insight into the ChS microenvironment, since immunotherapy and antiangiogenic agents are emerging as interesting therapeutic options for ChS patients.

An immune-related eleven-RNA signature-drived risk score model for prognosis of osteosarcoma metastasis.

This study aimed to determine an immune-related RNA signature as a prognostic marker, in this study, we developed a risk score model for predicting the prognosis of osteosarcoma metastasis. We first downloaded the clinical information and expression data of osteosarcoma samples from the UCSC Xena and GEO databases, of which the former was the training set and the latter was the validation set. Immune infiltration was assessed using the ssGSEA and ESTIMATE algorithms, and the osteosarcoma samples were divided into the Immunity_L and Immunity_H groups. Then, eleven RNAs were identified as the optimal prognostic RNA signatures using LASSO Cox regression analysis for establishing a risk score (RS) model. Kaplan-Meier approach indicated the high-risk group exhibited a shorter survival. Furthermore, we analyzed the tumor metastasis, age, and RS model status were determined to be independent clinical prognostic factors using Cox regression analysis. Decision curve analysis (DCA) indicated that the prognostic factor + RS model had the best net benefit. Finally, nine tumor-infiltrating immune cells (TIICs) showed significant differences in abundance between high- and low-risk groups via CIBERSORT deconvolution algorithm. In conclusion, the immune-related eleven-RNA signature be could served as a potential prognostic biomarker for osteosarcoma metastasis.

System analysis based on Anoikis-related genes identifies MAPK1 as a novel therapy target for osteosarcoma with neoadjuvant chemotherapy.

BACKGROUND: Osteosarcoma (OS) is the most common bone malignant tumor in children, and its prognosis is often poor. Anoikis is a unique mode of cell death.However, the effects of Anoikis in OS remain unexplored. METHOD: Differential analysis of Anoikis-related genes was performed based on the metastatic and non-metastatic groups. Then LASSO logistic regression and SVM-RFE algorithms were applied to screen out the characteristic genes. Later, Univariate and multivariate Cox regression was conducted to identify prognostic genes and further develop the Anoikis-based risk score. In addition, correlation analysis was performed to analyze the relationship between tumor microenvironment, drug sensitivity, and prognostic models. RESULTS: We established novel Anoikis-related subgroups and developed a prognostic model based on three Anoikis-related genes (MAPK1, MYC, and EDIL3). The survival and ROC analysis results showed that the prognostic model was reliable. Besides, the results of single-cell sequencing analysis suggested that the three prognostic genes were closely related to immune cell infiltration. Subsequently, aberrant expression of two prognostic genes was identified in osteosarcoma cells. Nilotinib can promote the apoptosis of osteosarcoma cells and down-regulate the expression of MAPK1. CONCLUSIONS: We developed a novel Anoikis-related risk score model, which can assist clinicians in evaluating the prognosis of osteosarcoma patients in clinical practice. Analysis of the tumor immune microenvironment and chemotherapeutic drug sensitivity can provide necessary insights into subsequent mechanisms. MAPK1 may be a valuable therapeutic target for neoadjuvant chemotherapy in osteosarcoma.