Glycan Structures in Osteosarcoma as Targets for Lectin-Based Chimeric Antigen Receptor Immunotherapy.

Osteosarcoma is a type of bone cancer that primarily affects children and young adults. The overall 5-year survival rate for localized osteosarcoma is 70-75%, but it is only 20-30% for patients with relapsed or metastatic tumors. To investigate potential glycan-targeting structures for immunotherapy, we stained primary osteosarcomas with recombinant C-type lectin CD301 (MGL, CLEC10A) and observed moderate to strong staining on 26% of the tumors. NK92 cells expressing a CD301-CAR recognized and eliminated osteosarcoma cells in vitro. Cytotoxic activity assays correlated with degranulation and cytokine release assays. Combination with an inhibitory antibody against the immune checkpoint TIGIT (T-cell immunoreceptor with lg and ITIM domains) showed promising additional effects. Overall, this study showed, for the first time, the expression of CD301 ligands in osteosarcoma tissue and demonstrated their use as potential target structures for lectin-based immunotherapy.

Analysis of the effects of M2 macrophage-derived PDE4C on the prognosis, metastasis and immunotherapy benefit of osteosarcoma.

Tumour-associated macrophages (TAMs), encompassing M1 and M2 subtypes, exert significant effects on osteosarcoma (OS) progression and immunosuppression. However, the impacts of TAM-derived biomarkers on the progression of OS remains limited. The GSE162454 profile was subjected to single-cell RNA (scRNA) sequencing analysis to identify crucial mediators between TAMs and OS cells. The clinical features, effects and mechanisms of these mediators on OS cells and tumour microenvironment were evaluated via biological function experiments and molecular biology experiments. Phosphodiesterase 4C (PDE4C) was identified as a pivotal mediator in the communication between M2 macrophages and OS cells. Elevated levels of PDE4C were detected in OS tissues, concomitant with M2 macrophage level, unfavourable prognosis and metastasis. The expression of PDE4C was observed to increase during the conversion process of THP-1 cells to M2 macrophages, which transferred the PDE4C mRNA to OS cells through exosome approach. PDE4C increased OS cell proliferation and mobility via upregulating the expression of collagens. Furthermore, a positive correlation was observed between elevated levels of PDE4C and increased TIDE score, decreased response rate following immune checkpoint therapy, reduced TMB and diminished PDL1 expression. Collectively, PDE4C derived from M2 macrophages has the potential to enhance the proliferation and mobility of OS cells by augmenting collagen expression. PDE4C may serve as a valuable biomarker for prognosticating patient outcomes and response rates following immunotherapy.

Inflammasome-related gene signatures as prognostic biomarkers in osteosarcoma.

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

Development of a Risk Model and Genotyping Patterns Based on Disulfidptosis-Related lncRNAs to Predict Prognosis and Immune Landscape in Osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is the most prevalent orthopedic malignancy with a dismal prognosis. Disulfidptosis-related lncRNAs (DRLncs) may be related to the progression of OS, but their potential molecular regulatory role is still unclear. METHODS: Based on the data collected from The Cancer Genome Atlas (TCGA), we conducted correlation analysis and the univariate Cox analysis to screen prognosis-related DRLncs, followed by developing genotyping patterns and corresponding classifier. Subsequently, the survival analysis, enrichment analysis, drug sensitivity analysis and immune infiltration analysis were performed. Afterward, multivariate Cox regression was used to construct a risk model, which was further validated by the receiver operating characteristic (ROC) curve. The aberrant expression of hub DRLncs in OS was validated using the Reverse Transcription Polymerase Chain Reaction (RT-qPCR) assay. RESULTS: We identified 262 DRLncs and eleven prognosis-related DRLncs through filtering. We then constructed two distinct expression patterns of prognosis-related DRLncs and developed a classifier. We obtained 393 differentially expressed genes (DEGs) between different subtypes, which were significantly enriched in biological processes related to the extracellular matrix, integrin binding, focal adhesion, and Wnt signaling pathways. Through immune infiltration analysis, the activated CD4 memory T cells, resting natural killer (NK) cells, M1 macrophages, and resting dendritic cells (DC) were observed to exhibit different abundance in distinct subtypes. In the drug sensitivity analysis, tamoxifen showed a promising effect for drug-resistant OS. Furthermore, we identified five hub DRLncs and constructed a risk model. The RT-qPCR confirmed the aberrant expression of five hub DRLncs in OS. CONCLUSIONS: The present study identified DRLncs in OS, and conducted a comprehensive investigation of DRLncs-related expression patterns, survival status, immune landscape and drug sensitivity to reveal the difference in prognostic, pharmacological and immunological phenotype characteristics between distinct subtypes. Additionally, we developed a risk model to predict the prognosis, and constructed a genotyping classifier to predict the above phenotype characteristics in OS.

Payload-delivering engineered γδ T cells display enhanced cytotoxicity, persistence, and efficacy in preclinical models of osteosarcoma.

T cell-based cancer immunotherapy has typically relied on membrane-bound cytotoxicity enhancers such as chimeric antigen receptors expressed in autologous αß T cells. These approaches are limited by tonic signaling of synthetic constructs and costs associated with manufacturing. γδ T cells are an emerging alternative for cellular therapy, having innate antitumor activity, potent antibody-dependent cellular cytotoxicity, and minimal alloreactivity. We present an immunotherapeutic platform technology built around the innate properties of the Vγ9Vδ2 T cell, harnessing specific characteristics of this cell type and offering an allocompatible cellular therapy that recruits bystander immunity. We engineered γδ T cells to secrete synthetic tumor-targeting opsonins in the form of an scFv-Fc fusion protein and a mitogenic IL-15Rα-IL-15 fusion protein (stIL15). Using GD2 as a model antigen, we show that GD2-specific opsonin-secreting Vγ9Vδ2 T cells (stIL15-OPS-γδ T cells) have enhanced cytotoxicity and promote bystander activity of other lymphoid and myeloid cells. Secretion of stIL-15 abrogated the need for exogenous cytokine supplementation and further mediated activation of bystander natural killer cells. Compared with unmodified γδ T cells, stIL15-OPS-γδ T cells exhibited superior in vivo control of subcutaneous tumors and persistence in the blood. Moreover, stIL15-OPS-γδ T cells were efficacious against patient-derived osteosarcomas in animal models and in vitro, where efficacy could be boosted with the addition of zoledronic acid. Together, the data identify stIL15-OPS-γδ T cells as a candidate allogeneic cell therapy platform combining direct cytolysis with bystander activation to promote tumor control.

Importance of CD8 Tex cell-associated gene signatures in the prognosis and immunology of osteosarcoma.

As a highly aggressive bone malignancy, osteosarcoma poses a significant therapeutic challenge, especially in the setting of metastasis or recurrence. This study aimed to investigate the potential of CD8-Tex cell-associated genes as prognostic biomarkers to reveal the immunogenomic profile of osteosarcoma and guide therapeutic decisions. mRNA expression data and clinical details of osteosarcoma patients were obtained from the TCGA database (TARGET-OS dataset). The GSE21257 dataset (from the GEO database) was used as an external validation set to provide additional information on osteosarcoma specimens. 84 samples from the TARGET-OS dataset were used as the training set, and 53 samples from the GSE21257 dataset served as the external validation cohort. Univariate Cox regression analysis was utilized to identify CD8 Tex cell genes associated with prognosis. The LASSO algorithm was performed for 1000 iterations to select the best subset to form the CD8 Tex cell gene signature (TRS). Final genes were identified using the multivariate Cox regression model of the LASSO algorithm. Risk scores were calculated to categorize patients into high- and low-risk groups, and clinical differences were explored by Kaplan-Meier survival analysis to assess model performance. Prediction maps were constructed to estimate 1-, 3-, and 5 year survival rates for osteosarcoma patients, including risk scores for CD8 Texcell gene markers and clinicopathologic factors. The ssGSEA algorithm was used to assess the differences in immune function between TRS-defined high- and low-risk groups. TME and immune cell infiltration were further assessed using the ESTIMATE and CIBERSORT algorithms. To explore the relationship between immune checkpoint gene expression levels and the two risk-defined groups. A CD8 Tex cell-associated gene signature was extracted from the TISCH database and prognostic markers including two genes were developed. The high-risk group showed lower survival, and model performance was validated by ROC curves and C-index. Predictive plots were constructed to demonstrate survival estimates, combining CD8 Tex cell gene markers and clinical factors. This study provides valuable insights into the molecular and immune characteristics of osteosarcoma and offers potential avenues for advances in therapeutic approaches.

NUCB2 inhibition antagonizes osteosarcoma progression and promotes anti-tumor immunity through inactivating NUCKS1/CXCL8 axis.

The oncogenic properties of Nucleobindin2 (NUCB2) have been observed in various cancer types. Nevertheless, the precise understanding of the biological functions and regulatory mechanisms of NUCB2 in osteosarcoma remains limited. This investigation reported that NUCB2 was significantly increased upon glucose deprivation-induced metabolic stress. Elevated NUCB2 suppressed glucose deprivation-induced cell death and reactive oxygen species (ROS) increase. Depletion of NUCB2 resulted in a reduction in osteosarcoma cell proliferation as well as metastatic potential in vitro and in vivo. Mechanically, NUCB2 ablation suppressed C-X-C Motif Chemokine Ligand 8 (CXCL8) expression which then reduced programmed cell death 1 ligand 1 (PD-L1) expression and stimulated anti-tumor immunity mediated through cytotoxic T cells. Importantly, a combination of NUCB2 depletion with anti-PD-L1 treatment improved anti-tumor T-cell immunity in vivo. Moreover, we further demonstrated that NUCB2 interacted with NUCKS1 to inhibit its degradation, which is responsible for the transcriptional regulation of CXCL8 expression. Altogether, the outcome emphasizes the function of NUCB2 in osteosarcoma and indicates that NUCB2 elevates osteosarcoma progression and immunosuppressive microenvironment through the NUCKS1/CXCL8 pathway.

Single-cell RNA sequencing reveals the cellular and molecular heterogeneity of treatment-naïve primary osteosarcoma in dogs.

Osteosarcoma (OS) is a heterogeneous, aggressive malignancy of the bone that disproportionally affects children and adolescents. Therapeutic interventions for OS are limited, which is in part due to the complex tumor microenvironment (TME). As such, we used single-cell RNA sequencing (scRNA-seq) to describe the cellular and molecular composition of the TME in 6 treatment-naïve dogs with spontaneously occurring primary OS. Through analysis of 35,310 cells, we identified 41 transcriptomically distinct cell types including the characterization of follicular helper T cells, mature regulatory dendritic cells (mregDCs), and 8 tumor-associated macrophage (TAM) populations. Cell-cell interaction analysis predicted that mregDCs and TAMs play key roles in modulating T cell mediated immunity. Furthermore, we completed cross-species cell type gene signature homology analysis and found a high degree of similarity between human and canine OS. The data presented here act as a roadmap of canine OS which can be applied to advance translational immuno-oncology research.

Stabilizing Tumor-Resident Mast Cells Restores T-Cell Infiltration and Sensitizes Sarcomas to PD-L1 Inhibition.

PURPOSE: To explore the cellular cross-talk of tumor-resident mast cells (MC) in controlling the activity of cancer-associated fibroblasts (CAF) to overcome tumor microenvironment (TME) abnormalities, enhancing the efficacy of immune-checkpoint inhibitors in sarcoma. EXPERIMENTAL DESIGN: We used a coculture system followed by further validation in mouse models of fibrosarcoma and osteosarcoma with or without administration of the MC stabilizer and antihistamine ketotifen. To evaluate the contribution of ketotifen in sensitizing tumors to therapy, we performed combination studies with doxorubicin chemotherapy and anti-PD-L1 (B7-H1, clone 10F.9G2) treatment. We investigated the ability of ketotifen to modulate the TME in human sarcomas in the context of a repurposed phase II clinical trial. RESULTS: Inhibition of MC activation with ketotifen successfully suppressed CAF proliferation and stiffness of the extracellular matrix accompanied by an increase in vessel perfusion in fibrosarcoma and osteosarcoma as indicated by ultrasound shear wave elastography imaging. The improved tissue oxygenation increased the efficacy of chemoimmunotherapy, supported by enhanced T-cell infiltration and acquisition of tumor antigen-specific memory. Importantly, the effect of ketotifen in reducing tumor stiffness was further validated in sarcoma patients, highlighting its translational potential. CONCLUSIONS: Our study suggests the targeting of MCs with clinically administered drugs, such as antihistamines, as a promising approach to overcome resistance to immunotherapy in sarcomas.

Identification of TNFRSF1A as a potential biomarker for osteosarcoma.

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

ALOX5AP is an Indicator for High CD8 Lymphocyte Infiltration and "Hot" Tumor Microenvironment in Osteosarcoma: A Bioinformatic Study.

Little progress has been made in the treatment and prognosis of osteosarcoma in the past 40 years. Tumor microenvironment (TME) plays a critical role in the progression of osteosarcoma. This study aims to determine immune-associated prognostic biomarkers for osteosarcoma patients. With the help of analytical tools including ESTIMATE, differential gene expression, LASSO, and univariate cox and multivariate cox regression analysis, osteosarcoma gene expression data from Gene Expression Omnibus (GEO) databases were investigated. Following the establishment of a prognostic risk score model, internal and external validations using the GEO and TARGET databases were carried out. A total of 44 and 55 samples respectively in the GSE21257 and the TARGET databases were included. Our analysis found 93 differentially expressed genes (DEGs) between the high and low-ImmuneScore groups. Through univariate cox and LASSO analysis, ALOX5AP was identified as an indicator of TME in osteosarcomas. ALOX5AP was then used to construct a prognostic risk model. Internal and external verification revealed that higher expression of ALOX5AP was correlated with lower risk. Through the CIBERSORT algorithm, the level of CD8 T cells was found to negatively correlate with the risk score. This study revealed that ALOX5AP is an indicator for predicting high CD8 lymphocyte infiltration and "hot" tumor microenvironment in osteosarcomas. Thus, ALOX5AP has the potential to act as a biomarker for effective immunotherapies in osteosarcoma patients.

[Bioinformatics Analysis on Key Genes and Immune Infiltration of Osteosarcoma].

Objective To screen the potential key genes of osteosarcoma by bioinformatics methods and analyze their immune infiltration patterns. Methods The gene expression profiles GSE16088 and GSE12865 associated with osteosarcoma were obtained from the Gene Expression Omnibus(GEO),and the differentially expressed genes(DEGs)related to osteosarcoma were screened by bioinformatics tools.Gene Ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment,and analysis of immune cell infiltration were then carried out for the DEGs.The potential Hub genes of osteosarcoma were identified by protein-protein interaction network,and the expression of Hub genes in osteosarcoma and normal tissue samples was verified via the Cancer Genome Atlas(TCGA). Results A total of 108 DEGs were screened out.GO annotation and KEGG pathway enrichment revealed that the DEGs were mainly involved in integrin binding,extracellular matrix (ECM) structural components,ECM receptor interactions,and phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt)signaling pathway.Macrophages were the predominant infiltrating immune cells in osteosarcoma.Secreted phosphoprotein 1(SPP1),matrix metallopeptidase 2(MMP2),lysyl oxidase(LOX),collagen type V alpha(II)chain(COL5A2),and melanoma cell adhesion molecule(MCAM)presented differential expression between osteosarcoma and normal tissue samples(all P<0.05). Conclusions SPP1,MMP2,LOX,COL5A2,and MCAM are all up-regulated in osteosarcoma,which may serve as potential biomarkers of osteosarcoma.Macrophages are the key infiltrating immune cells in osteosarcoma,which may provide new perspectives for the treatment of osteosarcoma.

CAR T targets and microenvironmental barriers of osteosarcoma.

Osteosarcoma (OS) is one of the most common malignancies in children and adolescents. Multimodal chemotherapy and aggressive surgical resection have improved the prognosis of patients with osteosarcoma. However, the prognosis of OS patients with unresectable advanced tumors, distant metastasis or chemotherapy is still poor. Chimeric antigen receptor (CAR) T cells have achieved remarkable success in the treatment of hematologic malignancies, injecting new vitality into the field of adoptive cell therapy. However, the efficacy in solid tumors has been largely limited. The reason for the poor curative effect of solid tumors is mainly the heterogeneity of solid tumor antigen, immune escape, tumor microenvironment barrier, resistance of immunosuppressive cells and inhibitory factors, which lead to the obstruction of CAR T cell infiltration and the aggravation of failure. Potential antigenic targets for osteosarcoma CAR T cell therapy are under continuous exploration. Some of the antigenic targets, such as anti-HER2-CAR T cells, have achieved good results in preclinical studies, and some of them have entered clinical studies and achieved certain clinical effects. In this review, we discuss the research progress of potential antigen targets and osteosarcoma microenvironment of CAR T cells in the treatment of osteosarcoma.

In vivo imaging of nanoparticle-labeled CAR T cells.

Metastatic osteosarcoma has a poor prognosis with a 2-y, event-free survival rate of ∼15 to 20%, highlighting the need for the advancement of efficacious therapeutics. Chimeric antigen receptor (CAR) T-cell therapy is a potent strategy for eliminating tumors by harnessing the immune system. However, clinical trials with CAR T cells in solid tumors have encountered significant challenges and have not yet demonstrated convincing evidence of efficacy for a large number of patients. A major bottleneck for the success of CAR T-cell therapy is our inability to monitor the accumulation of the CAR T cells in the tumor with clinical-imaging techniques. To address this, we developed a clinically translatable approach for labeling CAR T cells with iron oxide nanoparticles, which enabled the noninvasive detection of the iron-labeled T cells with magnetic resonance imaging (MRI), photoacoustic imaging (PAT), and magnetic particle imaging (MPI). Using a custom-made microfluidics device for T-cell labeling by mechanoporation, we achieved significant nanoparticle uptake in the CAR T cells, while preserving T-cell proliferation, viability, and function. Multimodal MRI, PAT, and MPI demonstrated homing of the T cells to osteosarcomas and off-target sites in animals administered with T cells labeled with the iron oxide nanoparticles, while T cells were not visualized in animals infused with unlabeled cells. This study details the successful labeling of CAR T cells with ferumoxytol, thereby paving the way for monitoring CAR T cells in solid tumors.

The activity level of follicular helper T cells in the peripheral blood of osteosarcoma patients is associated with poor prognosis.

Osteosarcoma (OS) is solid tumors with high malignancy and incidence starting in the bones. OS pathogenesis has been proved to be closely associated with immune imbalance, and follicular helper T cells (Tfh) significantly affect host humoral immune homeostasis. However, there are few reports on the effect of Tfh cell activation on the prognosis of OS patients. Hence, this investigation on the changes in the proportion of peripheral blood Tfh cells in OS patients, and the relationship between their activity level and OS prognosis. We collected peripheral blood from patients with OS, benign bone tumor (BT group) and healthy subjects (Healthy group), respectively. The number of CD4+CXCR5+ Tfh cell in peripheral blood was measured by flow cytometry and correlation analysis between its activity and OS clinicopathological characteristics was carried out. The data showed that in comparison with the BT and Healthy groups, higher proportion and activation level of peripheral blood CD4+CXCR5+ Tfh cells in CD4+ T cells were found in the OS group. In OS patients, increases of the proportion and activity level of Tfh cells were associated with poorly differentiated OS and tumor metastasis. Additionally, Kaplan-Meier and Cox regression analysis showed a longer overall survival in patients with low proportion of peripheral blood CD4+CXCR5+ Tfh cells in CD4+ T cells, and their activation level may be a prognostic factor in OS patients. In conclusion, peripheral blood CD4+CXCR5+ Tfh cell activation in OS patients was associated with a poor prognosis. This study provided ideas for improving the clinical treatment of OS patients.

Infiltration of LPAR5+ macrophages in osteosarcoma tumor microenvironment predicts better outcomes.

Introduction: Tumor microenvironment (TME) has been shown to be extensively involved in tumor development. However, the dynamic change of TME components and their effects are still unclear. Here, we attempted to identify TME-related genes that could help predict survival and may be potential therapeutic targets. Methods: Data was collected from UCSC Xena and GEO database. ESTIMATE and CIBERSORT algorithms were applied to estimate the components and the proportions of TIICs in TME. We analyzed the gene expression differences of immune components and stromal components, respectively, and finally got the overlapped DEGs. Through protein-protein interaction (PPI) network and univariate Cox regression analysis based on shared DEGs, we screened out and validated the TME-related genes. Focusing on this gene, we analyzed the expression and prognostic value of this gene, and investigated its relationship with immune cells by correlation analysis, single cell analysis, immunohistochemistry and immunofluorescence analysis. Results: Through a series analysis, we found that the proportion of immune and stromal components was an important prognostic factor, and screened out a key gene, LPAR5, which was highly correlated with prognosis and metastasis. And the expression of LPAR5 was positively correlated with immune cells, especially macrophages, indicating LPAR5+ macrophages played an important role in tumor microenvironment of osteosarcoma. Meanwhile, the genes in LPAR5 high expression group were enriched in immune-related activities and pathways, and differentially expressed genes between LPAR5+ macrophages and LPAR5- macrophages were enriched in the biological processes associated with phagocytosis and antigen presentation. What' more, we found that LPAR5 was mainly expressed in TME, and high LPAR5 expression predicting a better prognosis. Conclusion: We identified a TME-related gene, LPAR5, which is a promising indicator for TME remodeling in osteosarcoma. Particularly, LPAR5+ macrophages might have great potential to be a prognostic factor and therapeutic target for osteosarcoma.

Preoperative prognostic nutritional index and systemic immune-inflammation index predict survival outcomes in osteosarcoma: A comparison between young and elderly patients.

OBJECTIVE: This retrospective study of patients with osteosarcoma investigated the following biomarkers of inflammation and nutritional status: neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, prognostic nutritional index (PNI), and systemic immune-inflammation index (SII). The efficacies of these indicators to predict overall survival (OS) of young and elderly patients were compared. METHODS: The data of 125 patients with osteosarcoma, comprising the young (≤20 years) and elderly (60-80 years), were reviewed. Receiver operating characteristic (ROC) curves were calculated to determine the optimal cut-off value and area under the ROC curve of each potential biomarker. Kaplan-Meier curves and a Cox proportional hazards model were used to perform survival analyses. RESULTS: The cut-off values for low and high PNI ( ≤48.5, >48.5) and low and high SII (≤607.3, >607.3) were determined. Osteosarcoma patients in low PNI group or high SII group exhibited poorer OS relative to those in high PNI or low SII groups. The univariate and multivariate analyses indicated that preoperative PNI and SII were independent prognostic factors for OS in both the young and elderly subjects. CONCLUSION: Preoperative PNI and SII can be viable biomarkers of prognosis for both young and elderly patients with osteosarcoma. Awareness of these valuable indexes will enable clinicians to evaluate the inflammatory and nutritional status of these patients and establish a framework for individualized therapy.

Thrombospondin-1 induced programmed death-ligand 1-mediated immunosuppression by activating the STAT3 pathway in osteosarcoma.

Thrombospondin-1 (TSP1) is generally assumed to suppress the growth of osteosarcoma through inhibiting angiogenesis; however, it is unclear whether TSP1 could affect the antitumor immunity against osteosarcoma. We aimed to explore the immune-related tumor-promoting effects of TSP1 and decipher its underlying mechanism. First, we identified that TSP1 regulated programmed death-ligand 1 (PD-L1) expression, which was related to the CD8+ T cells anergy in osteosarcoma cells. The exact role of PD-L1 in the immunosuppressive effect of TSP1 was then further confirmed by the addition of the PD-L1 neutralizing Ab. With the addition of PD-L1 neutralizing Abs during cocultivation, the inhibition of CD8+ T cells was abolished to a certain extent. Further mechanistic investigations showed that TSP1-induced PD-L1 upregulation was achieved by activation of the signal transducer and activator of transcription 3 (STAT3) pathway. In vivo experiments also indicated that TSP1 overexpression could promote the growth of primary lesions, whereas TSP1 knockdown effectively inhibits the growth of the primary lesion as well as lung metastasis by restoring the antitumor immunity. Thrombospondin-1 knockdown combined with PD-L1 neutralizing Ab achieved a more pronounced antitumor effect. Taken together, our study showed that TSP1 upregulates PD-L1 by activating the STAT3 pathway and, therefore, impairs the antitumor immunity against osteosarcoma.

Integrative analysis of immune-related multi-omics profiles identifies distinct prognosis and tumor microenvironment patterns in osteosarcoma.

Osteosarcoma (OS) is the most common primary malignancy of bone. Epigenetic regulation plays a pivotal role in cancer development in various aspects, including immune response. In this study, we studied the potential association of alterations in the DNA methylation and transcription of immune-related genes with changes in the tumor microenvironment (TME) and tumor prognosis of OS. We obtained multi-omics data for OS patients from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. By referring to curated immune signatures and using a consensus clustering method, we categorized patients based on immune-related DNA methylation patterns (IMPs), and evaluated prognosis and TME characteristics of the resulting patient subgroups. Subsequently, we used a machine-learning approach to construct an IMP-associated prognostic risk model incorporating the expression of a six-gene signature (MYC, COL13A1, UHRF2, MT1A, ACTB, and GBP1), which was then validated in an independent patient cohort. Furthermore, we evaluated TME patterns, transcriptional variation in biological pathways, somatic copy number alteration, anticancer drug sensitivity, and potential responsiveness to immune checkpoint inhibitor therapy with regard to our IMP-associated signature scoring model. By integrative IMP and transcriptomic analysis, we uncovered distinct prognosis and TME patterns in OS. Finally, we constructed a classifying model, which may aid in prognosis prediction and provide a potential rationale for targeted- and immune checkpoint inhibitor therapy in OS.

Bioinformatics Analysis on Key Genes and Immune Infiltration of Osteosarcoma / 中国医学科学院学报

Objective To screen the potential key genes of osteosarcoma by bioinformatics methods and analyze their immune infiltration patterns. Methods The gene expression profiles GSE16088 and GSE12865 associated with osteosarcoma were obtained from the Gene Expression Omnibus(GEO),and the differentially expressed genes(DEGs)related to osteosarcoma were screened by bioinformatics tools.Gene Ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment,and analysis of immune cell infiltration were then carried out for the DEGs.The potential Hub genes of osteosarcoma were identified by protein-protein interaction network,and the expression of Hub genes in osteosarcoma and normal tissue samples was verified via the Cancer Genome Atlas(TCGA). Results A total of 108 DEGs were screened out.GO annotation and KEGG pathway enrichment revealed that the DEGs were mainly involved in integrin binding,extracellular matrix (ECM) structural components,ECM receptor interactions,and phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt)signaling pathway.Macrophages were the predominant infiltrating immune cells in osteosarcoma.Secreted phosphoprotein 1(SPP1),matrix metallopeptidase 2(MMP2),lysyl oxidase(LOX),collagen type V alpha(II)chain(COL5A2),and melanoma cell adhesion molecule(MCAM)presented differential expression between osteosarcoma and normal tissue samples(all P<0.05). Conclusions SPP1,MMP2,LOX,COL5A2,and MCAM are all up-regulated in osteosarcoma,which may serve as potential biomarkers of osteosarcoma.Macrophages are the key infiltrating immune cells in osteosarcoma,which may provide new perspectives for the treatment of osteosarcoma.