Immune checkpoints in osteosarcoma: Recent advances and therapeutic potential

The contribution of the novel CLTC-VMP1 fusion gene to autophagy regulation and energy metabolism in cisplatin-resistant osteosarcoma

Osteosarcoma (OS) is a highly malignant tumor, and chemotherapy resistance is a major challenge in the treatment of this disease. This study aims to explore the role of the CLTC-VMP1 gene fusion in the mechanism of chemotherapy resistance in OS and investigate its molecular mechanisms in mediating energy metabolism reprogramming by regulating autophagy and apoptosis balance. Using single-cell transcriptome analysis, the heterogeneity of OS cells and their correlation with resistance to platinum drugs were revealed. Cisplatin-resistant cell lines were established in human OS cell lines for subsequent experiments. Based on transcriptomic analysis, the importance of VMP1 in chemotherapy resistance was confirmed. Lentiviral vectors overexpressing or interfering with VMP1 were used, and it was observed that inhibiting VMP1 could reverse cisplatin resistance, promote cell apoptosis, and inhibit autophagy, and mitochondrial respiration and glycolysis. Furthermore, the presence of CLTC-VMP1 gene fusion was validated, and its ability to regulate autophagy and apoptosis balance, promote mitochondrial respiration, and glycolysis was demonstrated. Mouse model experiments further confirmed the promoting effect of CLTC-VMP1 on tumor growth and chemotherapy resistance. In summary, the CLTC-VMP1 gene fusion mediates energy metabolism reprogramming by regulating autophagy and apoptosis balance, which promotes chemotherapy resistance in OS.NEW & NOTEWORTHY This study identifies the CLTC-VMP1 gene fusion as a key driver of chemotherapy resistance in osteosarcoma by regulating autophagy and reprogramming cellular energy metabolism. Through single-cell transcriptomics, the research reveals the heterogeneity of tumor cells and the role of VMP1 in promoting resistance to cisplatin. The findings suggest that targeting the CLTC-VMP1 fusion gene may offer new therapeutic strategies to overcome chemotherapy resistance in osteosarcoma.

Photothermal-Triggered Extracellular Matrix Clearance and Dendritic Cell Maturation for Enhanced Osteosarcoma Immunotherapy

Osteosarcoma, a predominant malignant tumor among adolescents, exhibits high mortality and suboptimal immunotherapy efficacy due to a collagen-dense extracellular matrix (ECM) that hinders cytotoxic T lymphocyte (CTL) infiltration. Herein, we developed mesoporous polydopamine (MPDA) nanoparticles encapsulating bromelain and the immune adjuvant R848 (M@B/R), aimed at enhancing photothermal immunotherapy. These nanoparticles efficiently accumulate at the tumor site following injection. Upon near-infrared (NIR) light irradiation, photothermal therapy (PTT) induces immunogenic cell death in tumor cells and, with the aid of R848, efficiently promotes dendritic cell maturation, activating antitumor immunity and leading to CTL infiltration into the tumor. Concurrently, NIR-induced heating activates bromelain, resulting in ECM degradation and improved CTL penetration into the tumor. Our in vivo evaluations demonstrate potent antitumor effects in osteosarcoma-bearing mice. This integrated approach offers a promising strategy for overcoming physical barriers in ECM-rich tumors, marking a significant advancement in the treatment of osteosarcoma.

Potential predictive value of immune-related genes FUCA1 and NCKAP1L for osteosarcoma metastasis

BACKGROUND

Osteosarcoma is a common malignant tumor with a low survival rate after metastasis. Current treatments have not proven to effectively increase patient survival rates. Immunotherapy is a promising new treatment approach, however, immune target therapy has not shown satisfactory results. This study aims to provide new insights and evidence for the use of immunotherapy in osteosarcoma, based on a comprehensive analysis of gene expression data from databases.

METHODS

Gene expression and GSAV analysis were conducted on samples from patients with metastatic and non-metastatic osteosarcoma in the TARGET and GEO databases to identify relevant genes. These genes were further analyzed using GO, KEGG, GSVA, correlation analysis, and immune microenvironment scoring techniques. The tissue location of gene expression was confirmed through single-cell analysis. Validation of gene expression patterns was performed using polymerase chain reaction, western blot, and immunohistochemistry.

RESULTS

The study identified FUCA1 and NCKAP1L as significantly enriched in non-metastatic osteosarcoma, with higher expression associated with better patient survival rates. Gene function enrichment was primarily related to immune functions, with positive correlations to macrophage phagocytosis, antigen presentation, and macrophage polarization pathways. Analysis of the immune microenvironment revealed a positive correlation between gene expression and immune scores, with increased presence of macrophages, T cells, and B cells in the high expression group. Single-cell analysis and experimental results confirmed the enrichment of FUCA1 and NCKAP1L in macrophages.

CONCLUSION

The identification of FUCA1 and NCKAP1L as potential prognostic biomarkers suggests their potential for improving patient outcomes. Modulation of macrophages may offer a promising strategy for enhancing the immune microenvironment in osteosarcoma.

Trifluoperazine exerts anti-osteosarcoma effect by inducing mitochondria-dependent apoptosis via AKT/TXNIP signaling pathway

The survival rates for patients with osteosarcoma (OS) have stagnated over the past few decades. It is essential to find new therapies and drugs. A licensed antipsychotic medication called trifluoperazine (TFP) significantly reduces the growth of several cancers. However, the exact molecular pathways of TFP in OS remain to be discovered. Our research revealed that TFP greatly reduced OS cell migration and growth and caused the arrest of G0/G1 cell cycle. Combined with RNA-Seq data and further research, we confirmed that TFP promoted reactive oxygen species (ROS) production by elevating thioredoxin binding protein (TXNIP) expression to induce mitochondria-dependent apoptosis. Interestingly, we first demonstrated that AKT was an upstream regulatory target of TXNIP in OS cells. Dephosphorylation of AKT led to an increase in TXNIP expression, further elucidating the anticancer mechanism of TFP. In vivo, TFP inhibited subcutaneous OS cell proliferation and induced OS cell apoptosis without noticeable side effects. In conclusion, our findings imply that TFP is a potential treatment for OS.

Neoadjuvant Chemotherapy for Adults with Osteogenic Sarcoma

OPINION STATEMENT

Osteosarcoma is the most common primary malignant bone tumor in adolescents and adults. The 5-year survival rate is 65% when localized; however, survival drops dramatically to 10-20% in cases of metastatic disease. Therapy for osteosarcoma saw its first significant advancement in the 1970-80's, with the introduction of our current standard of care, consisting of the neo/adjuvant treatment regimen methotrexate, doxorubicin (Adriamycin), and cisplatin (collectively referred to as MAP) and surgical resection. Since MAP, development of a better therapeutic approach has stalled, creating a plateau in patient outcomes that has persisted for 40 years. Despite substantial research into a variety of pathways for novel treatment options, clinical trials have not produced sizeable improvements in outcomes. In this article, we discuss our current neoadjuvant standard of care therapy, followed by a review of contemporary therapeutic options, including tyrosine kinase inhibitors (TKIs), immune checkpoint inhibitors (ICIs), monoclonal antibodies (mAbs), and chimeric antigen receptor (CAR) T cells. Lastly, we consider the challenges hindering the success of novel treatment options and future research directions.

Spatial Heterogeneity of PD-1/PD-L1 Defined Osteosarcoma Microenvironments at Single-Cell Spatial Resolution

Osteosarcoma, predominantly affecting children and adolescents, is a highly aggressive bone cancer with a 5-year survival rate of 65% to 70%. The spatial dynamics between tumor-associated macrophage (TAM) and other cellular subtypes, including T cells, osteoblasts, and osteoclasts, are critical for understanding the complexities of the osteosarcoma tumor microenvironment (TME) and can provide insights into potential immunotherapeutic strategies. Our study employs a pioneering approach that combines deep learning-based digital image analysis with multiplex fluorescence immunohistochemistry to accurately implement cell detection, segmentation, and fluorescence intensity measurements for the in-depth study of the TME. We introduce a novel algorithm for TAM/osteoclast differentiation, crucial for the accurate characterization of cellular composition. Our findings reveal distinct heterogeneity in cell composition and spatial orchestration between PD-1 (-/+) and PD-L1 (-/+) patients, highlighting the role of T-cell functionality in this context. Furthermore, our analysis demonstrates the efficacy of nivolumab in suppressing tumor growth and enhancing lymphocyte infiltration without altering the M1/M2-TAM ratio. This study provides critical insights into the spatial orchestration of cellular subtypes within the PD-1/PD-L1 defined osteosarcoma TME. By leveraging advanced multiplex fluorescence immunohistochemistry and artificial intelligence, we underscore the critical role of TAMs and T-cell interactions, proposing new therapeutic avenues focusing on TAM repolarization and targeted immunotherapies, thus underscoring the study's potential impact on improving osteosarcoma treatment.

Advances on immunotherapy for osteosarcoma

Osteosarcoma is the most common primary bone cancer in children and young adults. Limited progress has been made in improving the survival outcomes in patients with osteosarcoma over the past four decades. Especially in metastatic or recurrent osteosarcoma, the survival rate is extremely unsatisfactory. The treatment of osteosarcoma urgently needs breakthroughs. In recent years, immunotherapy has achieved good therapeutic effects in various solid tumors. Due to the low immunogenicity and immunosuppressive microenvironment of osteosarcoma, immunotherapy has not yet been approved in osteosarcoma patients. However, immune-based therapies, including immune checkpoint inhibitors, chimeric antigen receptor T cells, and bispecfic antibodies are in active clinical development. In addition, other immunotherapy strategies including modified-NK cells/macrophages, DC vaccines, and cytokines are still in the early stages of research, but they will be hot topics for future study. In this review, we showed the functions of cell components including tumor-promoting and tumor-suppressing cells in the tumor microenvironment of osteosarcoma, and summarized the preclinical and clinical research results of various immunotherapy strategies in osteosarcoma, hoping to provide new ideas for future research in this field.

PRKDC Induces Chemoresistance in Osteosarcoma by Recruiting GDE2 to Stabilize GNAS and Activate AKT

Chemoresistance is one of the major causes of poor prognosis in osteosarcoma. Alternative therapeutic strategies for osteosarcoma are limited, indicating that increasing sensitivity to currently used chemotherapies could be an effective approach to improve patient outcomes. Using a kinome-wide CRISPR screen, we identified PRKDC as a critical determinant of doxorubicin (DOX) sensitivity in osteosarcoma. The analysis of clinical samples demonstrated that PRKDC was hyperactivated in osteosarcoma, and functional experiments showed that the loss of PRKDC significantly increased sensitivity of osteosarcoma to DOX. Mechanistically, PRKDC recruited and bound GDE2 to enhance the stability of protein GNAS. The elevated GNAS protein levels subsequently activated AKT phosphorylation and conferred resistance to DOX. The PRKDC inhibitor AZD7648 and DOX synergized and strongly suppressed the growth of osteosarcoma in mouse xenograft models and human organoids. In conclusion, the PRKDC-GDE2-GNAS-AKT regulatory axis suppresses DOX sensitivity and comprises targetable candidates for improving the efficacy of chemotherapy in osteosarcoma. Significance: Targeting PRKDC suppresses AKT activation and increases sensitivity to doxorubicin in osteosarcoma, which provides a therapeutic strategy for overcoming chemoresistance.

Prediction of Prognosis and Immunotherapy Response with a Novel Natural Killer Cell Marker Genes Signature in Osteosarcoma

Background: Natural killer (NK) cells are characterized by their antitumor efficacy without previous sensitization, which have attracted attention in tumor immunotherapy. The heterogeneity of osteosarcoma (OS) has hindered therapeutic application of NK cell-based immunotherapy. The authors aimed to construct a novel NK cell-based signature to identify certain OS patients more responsive to immunotherapy. Materials and Methods: A total of eight publicly available datasets derived from patients with OS were enrolled in this study. Single-cell RNA sequencing data obtained from the Gene Expression Omnibus (GEO) database were analyzed to screen NK cell marker genes. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was used to construct an NK cell-based prognostic signature in the TARGET-OS dataset. The differences in immune cell infiltration, immune system-related metagenes, and immunotherapy response were evaluated among risk subgroups. Furthermore, this prognostic signature was experimentally validated by reverse transcription-quantitative real-time PCR (RT-qPCR). Results: With differentially expressed NK cell marker genes screened out, a five-gene NK cell-based prognostic signature was constructed. The prognostic predictive accuracy of the signature was validated through internal clinical subgroups and external GEO datasets. Low-risk OS patients contained higher abundances of infiltrated immune cells, especially CD8 T cells and naive CD4 T cells, indicating that T cell exhaustion states were present in the high-risk OS patients. As indicated from correlation analysis, immune system-related metagenes displayed a negative correlation with risk scores, suggesting the existence of immunosuppressive microenvironment in OS. In addition, based on responses to immune checkpoint inhibitor therapy in two immunotherapy datasets, the signature helped predict the response of OS patients to anti-programmed cell death protein 1 (PD-1) or anti-programmed cell death ligand 1 (PD-L1) therapy. RT-qPCR results demonstrated the roughly consistent relationship of these five gene expressions with predicting outcomes. Conclusions: The NK cell-based signature is likely to be available for the survival prediction and the evaluation of immunotherapy response of OS patients, which may shed light on subsequent immunotherapy choices for OS patients. In addition, the authors revealed a potential link between immunosuppressive microenvironment and OS.

Biomaterials-Boosted Immunotherapy for Osteosarcoma

Osteosarcoma (OS) is a primary malignant bone tumor that emanates from mesenchymal cells, commonly found in the epiphyseal end of long bones. The highly recurrent and metastatic nature of OS poses significant challenges to the efficacy of treatment and negatively affects patient prognosis. Currently, available clinical treatment strategies primarily focus on maximizing tumor resection and reducing localized symptoms rather than the complete eradication of malignant tumor cells to achieve ideal outcomes. The biomaterials-boosted immunotherapy for OS is characterized by high effectiveness and a favorable safety profile. This therapeutic approach manipulates the tumor microenvironments at the cellular and molecular levels to impede tumor progression. This review delves into the mechanisms underlying the treatment of OS, emphasizing biomaterials-enhanced tumor immunity. Moreover, it summarizes the immune cell phenotype and tumor microenvironment regulation, along with the ability of immune checkpoint blockade to activate the autoimmune system. Gaining a profound comprehension of biomaterials-boosted OS immunotherapy is imperative to explore more efficacious immunotherapy protocols and treatment options in this setting.

Anti-tumor effects of the eIF4A inhibitor didesmethylrocaglamide and its derivatives in human and canine osteosarcomas

Inhibition of translation initiation using eIF4A inhibitors like (-)-didesmethylrocaglamide [(-)-DDR] and (-)-rocaglamide [(-)-Roc] is a potential cancer treatment strategy as they simultaneously diminish multiple oncogenic drivers. We showed that human and dog osteosarcoma cells expressed higher levels of eIF4A1/2 compared with mesenchymal stem cells. Genetic depletion of eIF4A1 and/or 2 slowed osteosarcoma cell growth. To advance preclinical development of eIF4A inhibitors, we demonstrated the importance of (-)-chirality in DDR for growth-inhibitory activity. Bromination of DDR at carbon-5 abolished growth-inhibitory activity, while acetylating DDR at carbon-1 was tolerated. Like (-)-DDR, (±)-DDR, and (-)-Roc, (±)-DDR-acetate increased γH2A.X levels and induced G2/M arrest and apoptosis. Consistent with translation inhibition, these rocaglates decreased the levels of several mitogenic kinases, the STAT3 transcription factor, and the stress-activated protein kinase p38. However, phosphorylated p38 was greatly enhanced in treated cells, suggesting activation of stress response pathways. RNA sequencing identified RHOB as a top upregulated gene in both (-)-DDR- and (-)-Roc-treated osteosarcoma cells, but the Rho inhibitor Rhosin did not enhance the growth-inhibitory activity of (-)-DDR or (-)-Roc. Nonetheless, these rocaglates potently suppressed tumor growth in a canine osteosarcoma patient-derived xenograft model. These results suggest that these eIF4A inhibitors can be leveraged to treat both human and dog osteosarcomas.

EYA4 reduces chemosensitivity of osteosarcoma to doxorubicin through DNA damage repair

Previous studies have demonstrated that Eyes Absent 4 (EYA4) influences the proliferation and migration of tumor cells. Notably, studies have established that EYA4 can also limit tumor sensitivity to chemotherapeutic agents. The objective of this study was to investigate the effect of EYA4 in conferring drug resistance in osteosarcoma (OS). Bioinformatics, histological, and cellular analyses revealed that the expression level of EYA4 was higher in OS tissues than in healthy tissues/cells and in resistant tissues/cells compared with sensitive tissues/cells. In vitro and in vivo experiments demonstrated that EYA4 knockdown increased the sensitivity of OS to doxorubicin (DOX). Conversely, overexpression of EYA4 decreased the sensitivity of OS to DOX. Exploration of the resistance mechanism exposed that EYA4 facilitates DNA double-strand break (DSB) repair, a typical mode of DNA damage repair (DDR). Subsequently, our findings indicated that EYA4 could directly interact with histone H2AX to activate the DDR pathway. Taken together, our observations indicated that EYA4 may serve as a target molecule for reversing drug resistance in OS patients.

FBXO22 promotes osteosarcoma progression via regulation of FOXO1 for ubiquitination and degradation

Accumulating evidence has demonstrated that F-box protein 22 (FBXO22) participates in tumour development and progression in various types of human malignancies. However, the functions and detailed molecular mechanisms of FBXO22 in osteosarcoma tumorigenesis and progression remain elusive. In this study, we aimed to determine the effects of FBXO22 on the cell proliferation, migration and invasion of osteosarcoma cells using cell counting kit-8 and Matrigel Transwell approaches. Moreover, we explored the molecular mechanisms by which FBXO22 mediated oncogenesis and progression in osteosarcoma via Western blotting, immunoprecipitation and ubiquitination. We found that FBXO22 depletion inhibited the proliferation, migration and invasion of osteosarcoma cells, whereas FBXO22 overexpression increased the proliferation and motility of osteosarcoma cells. Mechanistically, FBXO22 promoted the ubiquitination and degradation of FoxO1 in osteosarcoma cells. FBXO22 depletion reduced cell proliferation and motility via regulation of FoxO1. Taken together, our findings provide new insight into FBXO22-induced osteosarcoma tumorigenesis. The inhibition of FBXO22 could be a promising strategy for the treatment of osteosarcoma.

Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.

Molecular Landscape and Prognostic Value in the Post-Translational Ubiquitination, SUMOylation and Neddylation in Osteosarcoma: A Transcriptome Study

Background

Post-translational modifications (PTM) significantly influence the pathogenesis and progression of diverse neoplastic conditions. Nevertheless, there has been limited research focusing on the potential of PTM-related genes (PTMRGs) as tumor biomarkers for predicting the survival of specific patients.

Methods

The datasets utilized in this research were obtained from the TARGET and GEO repositories, respectively. The gene signature was constructed through the utilization of LASSO Cox regression method. GSEA and GO was used to identify hub pathways associated with risk genes. The functionality of risk genes in osteosarcoma (OS) cell lines was verified through the implementation of the CCK-8 assay, cell cycle analysis, and immunofluorescence assay.

Results

Two distinct PTM patterns and gene clusters were finally determined. Significant differences in the prognosis of patients were found among two different PTM patterns and gene clusters, so were in the function enrichment and the landscape of TME immune cell infiltration. Moreover, we examined two external immunotherapy cohorts and determining that patients in the low-risk group was more likely to profit from immunotherapy. In addition, we mapped the expression of the genes in the signature in distinct cells using single-cell analysis. Finally, CCK-8 assay, cell cycle analysis, and immunofluorescence assay were utilized to confirm that RAD21 was expressed and functioned in OS.

Conclusion

In conclusion, this study elucidated the potential link between PTM and immune infiltration landscape of OS for the first time and provided a new assessment protocol for the precise selection of treatment strategies for patients with advanced OS.

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.

Anti-tumor Effects of the eIF4A Inhibitor Didesmethylrocaglamide and Its Derivatives in Human and Canine Osteosarcomas

Inhibition of translation initiation using eIF4A inhibitors like (-)-didesmethylrocaglamide [(-)-DDR] and (-)-rocaglamide [(-)-Roc] is a potential cancer treatment strategy as they simultaneously diminish multiple oncogenic drivers. We showed that human and dog osteosarcoma cells expressed high levels of eIF4A1/2, particularly eIF4A2. Genetic depletion of eIF4A1 and/or 2 slowed osteosarcoma cell growth. To advance preclinical development of eIF4A inhibitors, we demonstrated the importance of (-)-chirality in DDR for growth-inhibitory activity. Bromination of DDR at carbon-5 abolished growth-inhibitory activity, while acetylating DDR at carbon-1 was tolerated. Like DDR and Roc, DDR-acetate increased the γH2A.X levels and induced G2/M arrest and apoptosis. Consistent with translation inhibition, these rocaglates decreased the levels of several mitogenic kinases, the STAT3 transcription factor, and the stress-activated protein kinase p38. However, phosphorylated p38 was greatly enhanced in treated cells, suggesting activation of stress response pathways. RNA sequencing identified RHOB as a top upregulated gene in both DDR- and Roc-treated osteosarcoma cells, but the Rho inhibitor Rhosin did not enhance the growth-inhibitory activity of (-)-DDR or (-)-Roc. Nonetheless, these rocaglates potently suppressed tumor growth in a canine osteosarcoma patient-derived xenograft model. These results suggest that these eIF4A inhibitors can be leveraged to treat both human and dog osteosarcomas.

Single-cell transcriptional profiling in osteosarcoma and the effect of neoadjuvant chemotherapy on the tumor microenvironment

Osteosarcoma (OS), a malignant tumor, originates from the bone marrow. Currently, treatment for OS remains limited, making it urgent to understand the immune response in the tumor microenvironment of patients with OS. A comprehensive bioinformatics analysis was performed, including cell clustering subgroups, differential expression genes screening, proposed temporal order, and genomic variant analysis on single-cell RNA-sequencing data, from ten pre-chemotherapy patients and eleven post-chemotherapy patients. Subsequently, we analyzed the differentiation trajectories of osteoblasts, osteoclasts, fibroblasts, myeloid cells, and tumor-infiltrating lymphocytes (TILs) in detail to compare the changes in cell proportions and differential genes pre- and post-chemotherapy. The nine cell types were identified, including fibroblasts, myeloid cells, osteoblasts, TILs, osteoclasts, proliferative osteoblasts, pericytes, endothelial cells, and B cells. Post-chemotherapy treatment, the proportions of myeloid cells and TILs in OS were declined, while the number of osteoblasts was elevated. Besides, a decrease was observed in CD74, FTL, FTH1, MT1X and MT2A, and an increase in PTN, COL3A1, COL1A1, IGFBP7 and FN1. Meanwhile, EMT, DNA repair, G2M checkpoint, and E2F targets were highly enriched post-chemotherapy. Furthermore, there was a down-regulation in the proportions of CD14 monocytes, Tregs, NK cells and CD1C-/CD141-DCs, while an up-regulation was observed in the proportions of SELENOP macrophages, IL7R macrophages, COL1A1 macrophages, CD1C DCs, CD4+ T cells and CD8+ T cells. Overall, these findings revealed changes in the tumor microenvironment of OS post-chemotherapy treatment, providing a new direction for investigating OS treatment.

Bioinformatics analysis and validation of mesenchymal stem cells related gene MT1G in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is a primary malignant bone tumor arising from mesenchymal cells. The standard clinical treatment for OS involves extensive tumor resection combined with neoadjuvant chemotherapy or radiotherapy. OS's invasiveness, lung metastasis, and drug resistance contribute to a low cure rate and poor prognosis with this treatment. Metallothionein 1G (MT1G), observed in various cancers, may serve as a potential therapeutic target for OS.

METHODS

OS samples in GSE33382 and TARGET datasets were selected as the test cohorts. As the external validation cohort, 13 OS tissues and 13 adjacent cancerous tissues from The Second Affiliated Hospital of Nanchang University were collected. Patients with OS were divided into high and low MT1G mRNA-expression groups; differentially expressed genes (DEGs) were identified as MT1G-related genes. The biological function of MT1G was annotated using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and gene set enrichment analysis (GSEA). Gene expression correlation analysis and competing endogenous RNA (ceRNA) regulatory network construction were used to determine potential biological regulatory relationships of DEGs. Survival analysis assessed the prognostic value of MT1G.

RESULTS

MT1G expression increased in OS samples and presented higher in metastatic OS compared with non-metastatic OS. Functional analyses indicated that MT1G was mainly associated with spliceosome. A ceRNA network with DEGs was constructed. MT1G is an effective biomarker predicting survival and correlated with increased recurrence rates and poorer survival.

CONCLUSIONS

This research identified MT1G as a potential biomarker for OS prognosis, highlighting its potential as a therapy target.

The role of programmed cell death in osteosarcoma: From pathogenesis to therapy

Osteosarcoma (OS) is a prevalent bone solid malignancy that primarily affects adolescents, particularly boys aged 14-19. This aggressive form of cancer often leads to deadly lung cancer due to its high migration ability. Experimental evidence suggests that programmed cell death (PCD) plays a crucial role in the development of osteosarcoma. Various forms of PCD, including apoptosis, ferroptosis, autophagy, necroptosis, and pyroptosis, contribute significantly to the progression of osteosarcoma. Additionally, different signaling pathways such as STAT3/c-Myc signal pathway, JNK signl pathway, PI3k/AKT/mTOR signal pathway, WNT/β-catenin signal pathway, and RhoA signal pathway can influence the development of osteosarcoma by regulating PCD in osteosarcoma cell. Therefore, targeting PCD and the associated signaling pathways could offer a promising therapeutic approach for treating osteosarcoma.

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.

Integrated analysis of single-cell and bulk RNA sequencing data reveals prognostic characteristics of lysosome-dependent cell death-related genes in osteosarcoma

BACKGROUND

Tumor cells exhibit a heightened susceptibility to lysosomal-dependent cell death (LCD) compared to normal cells. However, the role of LCD-related genes (LCD-RGs) in Osteosarcoma (OS) remains unelucidated. This study aimed to elucidate the role of LCD-RGs and their mechanisms in OS using several existing OS related datasets, including TCGA-OS, GSE16088, GSE14359, GSE21257 and GSE162454.

RESULTS

Analysis identified a total of 8,629 DEGs1, 2,777 DEGs2 and 21 intersection genes. Importantly, two biomarkers (ATP6V0D1 and HDAC6) linked to OS prognosis were identified to establish the prognostic model. Significant differences in risk scores for OS survival were observed between high and low-risk cohorts. Additionally, scores of dendritic cells (DC), immature DCs and γδT cells differed significantly between the two risk cohorts. Cell annotations from GSE162454 encompassed eight types (myeloid cells, osteoblastic OS cells and plasma cells). ATP6V0D1 was found to be significantly over-expressed in myeloid cells and osteoclasts, while HDAC6 was under-expressed across all cell types. Moreover, single-cell trajectory mapping revealed that myeloid cells and osteoclasts differentiated first, underscoring their pivotal role in patients with OS. Furthermore, ATP6V0D1 expression progressively decreased with time.

CONCLUSIONS

A new prognostic model for OS, associated with LCD-RGs, was developed and validated, offering a fresh perspective for exploring the association between LCD and OS.

A Novel Defined Necroptosis-Related Genes Prognostic Signature for Predicting Prognosis and Treatment of Osteosarcoma

Osteosarcoma (OS) is a frequent primary malignant bone tumor, with a poor prognosis. Necroptosis is strongly correlated with OS and may be an influential target for treating OS. This study's objective was to establish a necroptosis-related gene (NRG) prognostic signature that could predict OS prognosis and guide OS treatment. First, we identified 20 NRGs associated with OS survival based on the TARGET database. We then derived a 7 NRG prognostic signature. Our findings revealed that the 7 NRG prognostic signature performed well in predicting the survival of OS patients. We next analyzed differences in immunological status and immune cell infiltration. In addition, we examined the relationship between chemo/immunotherapeutic response and the 7-NRG prognostic signature. In addition, to probe the mechanisms underlying the NRG prognostic signature, we performed functional enrichment assays including GO and KEGG. Finally, CHMP4C was selected for functional experiments. Silencing CHMP4C prevented OS cells from proliferating, migrating, and invading. This 7-NRG prognostic signature seems to be an excellent predictor that can provide a fresh direction for OS treatment.

Tertiary lymphoid structures in cancer: immune mechanisms and clinical implications

Cancer is a major cause of death globally, and traditional treatments often have limited efficacy and adverse effects. Immunotherapy has shown promise in various malignancies but is less effective in tumors with low immunogenicity or immunosuppressive microenvironment, especially sarcomas. Tertiary lymphoid structures (TLSs) have been associated with a favorable response to immunotherapy and improved survival in cancer patients. However, the immunological mechanisms and clinical significance of TLS in malignant tumors are not fully understood. In this review, we elucidate the composition, neogenesis, and immune characteristics of TLS in tumors, as well as the inflammatory response in cancer development. An in-depth discussion of the unique immune characteristics of TLSs in lung cancer, breast cancer, melanoma, and soft tissue sarcomas will be presented. Additionally, the therapeutic implications of TLS, including its role as a marker of therapeutic response and prognosis, and strategies to promote TLS formation and maturation will be explored. Overall, we aim to provide a comprehensive understanding of the role of TLS in the tumor immune microenvironment and suggest potential interventions for cancer treatment.

Multiple influence of immune cells in the bone metastatic cancer microenvironment on tumors

Bone is a common organ for solid tumor metastasis. Malignant bone tumor becomes insensitive to systemic therapy after colonization, followed by poor prognosis and high relapse rate. Immune and bone cells in situ constitute a unique immune microenvironment, which plays a crucial role in the context of bone metastasis. This review firstly focuses on lymphatic cells in bone metastatic cancer, including their function in tumor dissemination, invasion, growth and possible cytotoxicity-induced eradication. Subsequently, we examine myeloid cells, namely macrophages, myeloid-derived suppressor cells, dendritic cells, and megakaryocytes, evaluating their interaction with cytotoxic T lymphocytes and contribution to bone metastasis. As important components of skeletal tissue, osteoclasts and osteoblasts derived from bone marrow stromal cells, engaging in 'vicious cycle' accelerate osteolytic bone metastasis. We also explain the concept tumor dormancy and investigate underlying role of immune microenvironment on it. Additionally, a thorough review of emerging treatments for bone metastatic malignancy in clinical research, especially immunotherapy, is presented, indicating current challenges and opportunities in research and development of bone metastasis therapies.

N6-methyladenosine regulator YTHDF1 represses the CD8 + T cell-mediated antitumor immunity and ferroptosis in prostate cancer via m6A/PD-L1 manner

Increasing data and literature have illustrated that tumor immune escape represents a major source of tumor formation and recrudesce. Besides, novel findings also indicate that RNA N6-methyladenosine (m6A) participates in the human cancer immune escape. Here, our study investigated the functions of m6A reader YTHDF1 in prostate cancer (PCa) immune response and explored the functional mechanism. Results reported that YTHDF1 up-regulated in PCa samples and was closely correlated to poor clinical prognosis. Functionally, YTHDF1 inhibited the killing activity of CD8 + T cells to PCa cells, and moreover mitigated the ferroptosis. Mechanistically, PD-L1 acted as the target of YTHDF1, and YTHDF1 upregulated the transcriptional activity of PD-L1 mRNA. Collectively, YTHDF1 promoted functional PD-L1 partially through enhancing its transcriptional stability, which was necessary for PCa cells to evade effector T cell cytotoxicity and CD8 + T cells mediated ferroptosis. In conclusion, these findings indicate that YTHDF1 represses the CD8 + T cell-mediated antitumor immunity and ferroptosis in PCa via m6A-PD-L1 manner, which may provide novel insight for PCa immunotherapy.

Unraveling T cell exhaustion in the immune microenvironment of osteosarcoma via single-cell RNA transcriptome

Osteosarcoma (OS) represents a profoundly invasive malignancy of the skeletal system. T cell exhaustion (Tex) is known to facilitate immunosuppression and tumor progression, but its role in OS remains unclear. In this study, single-cell RNA sequencing data was employed to identify exhausted T cells within the tumor immune microenvironment (TIME) of OS. We found that exhausted T cells exhibited substantial infiltration in OS samples. Pseudotime trajectory analysis revealed a progressive increase in the expression of various Tex marker genes, including PDCD1, CTLA4, LAG3, ENTPD1, and HAVCR2 in OS. GSVA showed that apoptosis, fatty acid metabolism, xenobiotic metabolism, and the interferon pathway were significantly activated in exhausted T cells in OS. Subsequently, a prognostic model was constructed using two Tex-specific genes, MYC and FCGR2B, which exhibited exceptional prognostic accuracy in two independent cohorts. Drug sensitivity analysis revealed that OS patients with a low Tex risk were responsive to Dasatinib and Pazopanib. Finally, immunohistochemistry verified that MYC and FCGR2B were significantly upregulated in OS tissues compared with adjacent tissues. This study investigates the role of Tex within the TIME of OS, and offers novel insights into the mechanisms underlying disease progression as well as the potential treatment strategies for OS.

A CIC-related-epigenetic factors-based model associated with prediction, the tumor microenvironment and drug sensitivity in osteosarcoma

Osteosarcoma is generally considered a cold tumor and is characterized by epigenetic alterations. Although tumor cells are surrounded by many immune cells such as macrophages, T cells may be suppressed, be inactivated, or not be presented due to various mechanisms, which usually results in poor prognosis and insensitivity to immunotherapy. Immunotherapy is considered a promising anti-cancer therapy in osteosarcoma but requires more research, but osteosarcoma does not currently respond well to this therapy. The cancer immunity cycle (CIC) is essential for anti-tumor immunity, and is epigenetically regulated. Therefore, it is possible to modulate the immune microenvironment of osteosarcoma by targeting epigenetic factors. In this study, we explored the correlation between epigenetic modulation and CIC in osteosarcoma through bioinformatic methods. Based on the RNA data from TARGET and GSE21257 cohorts, we identified epigenetic related subtypes by NMF clustering and constructed a clinical prognostic model by the LASSO algorithm. ESTIMATE, Cibersort, and xCell algorithms were applied to analyze the tumor microenvironment. Based on eight epigenetic biomarkers (SFMBT2, SP140, CBX5, HMGN2, SMARCA4, PSIP1, ACTR6, and CHD2), two subtypes were identified, and they are mainly distinguished by immune response and cell cycle regulation. After excluding ACTR6 by LASSO regression, the prognostic model was established and it exhibited good predictive efficacy. The risk score showed a strong correlation with the tumor microenvironment, drug sensitivity and many immune checkpoints. In summary, our study sheds a new light on the CIC-related epigenetic modulation mechanism of osteosarcoma and helps search for potential drugs for osteosarcoma treatment.

Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways

BACKGROUND

Metabolic remodeling and changes in tumor immune microenvironment (TIME) in osteosarcoma are important factors affecting prognosis and treatment. However, the relationship between metabolism and TIME needs to be further explored.

METHODS

RNA-Seq data and clinical information of 84 patients with osteosarcoma from the TARGET database and an independent cohort from the GEO database were included in this study. The activity of seven metabolic super-pathways and immune infiltration levels were inferred in osteosarcoma patients. Metabolism-related genes (MRGs) were identified and different metabolic clusters and MRG-related gene clusters were identified using unsupervised clustering. Then the TIME differences between the different clusters were compared. In addition, an MRGs-based risk model was constructed and the role of a key risk gene, ST3GAL4, in osteosarcoma cells was explored using molecular biological experiments.

RESULTS

This study revealed four key metabolic pathways in osteosarcoma, with vitamin and cofactor metabolism being the most relevant to prognosis and to TIME. Two metabolic pathway-related clusters (C1 and C2) were identified, with some differences in immune activating cell infiltration between the two clusters, and C2 was more likely to respond to two chemotherapeutic agents than C1. Three MRG-related gene clusters (GC1-3) were also identified, with significant differences in prognosis among the three clusters. GC2 and GC3 had higher immune cell infiltration than GC1. GC3 is most likely to respond to immune checkpoint blockade and to three commonly used clinical drugs. A metabolism-related risk model was developed and validated. The risk model has strong prognostic predictive power and the low-risk group has a higher level of immune infiltration than the high-risk group. Knockdown of ST3GAL4 significantly inhibited proliferation, migration, invasion and glycolysis of osteosarcoma cells and inhibited the M2 polarization of macrophages.

CONCLUSION

The metabolism of vitamins and cofactors is an important prognostic regulator of TIME in osteosarcoma, MRG-related gene clusters can well reflect changes in osteosarcoma TIME and predict chemotherapy and immunotherapy response. The metabolism-related risk model may serve as a useful prognostic predictor. ST3GAL4 plays a critical role in the progression, glycolysis, and TIME of osteosarcoma cells.

Identification of TNFRSF21 as an inhibitory factor of osteosarcoma based on a necroptosis-related prognostic gene signature and molecular experiments

BACKGROUND

Osteosarcoma is one of the most common malignant bone tumors with bad prognosis. Necroptosis is a form of programmed cell death. Recent studies showed that targeting necroptosis was a new promising approach for tumor therapy. This study aimed to establish a necroptosis-related gene signature to evaluated prognosis and explore the relationship between necroptosis and osteosarcoma.

METHODS

Data from The Cancer Genome Atlas was used for developing the signature and the derived necroptosis score (NS). Data from Gene Expression Omnibus served as validation. Principal component analysis (PCA), Cox regression, receiver operating characteristic (ROC) curves and Kaplan-Meier survival analysis were used to assess the performance of signature. The association between the NS and osteosarcoma was analyzed via gene set enrichment analysis, gene set variation analysis and Pearson test. Single-cell data was used for further exploration. Among the genes that constituted the signature, the role of TNFRSF21 in osteosarcoma was unclear. Molecular experiments were used to explore TNFRSF21 function.

RESULTS

Our data revealed that lower NS indicated more active necroptosis in osteosarcoma. Patients with lower NS had a better prognosis. PCA and ROC curves demonstrated NS was effective to predict prognosis. NS was negatively associated with immune infiltration levels and tumor microenvironment scores and positively associated with tumor purity and stemness index. Single-cell data showed necroptosis heterogeneity in osteosarcoma. The cell communication pattern of malignant cells with high NS was positively correlated with tumor progression. The expression of TNFRSF21 was down-regulated in osteosarcoma cell lines. Overexpression of TNFRSF21 inhibited proliferation and motility of osteosarcoma cells. Mechanically, TNFRSF21 upregulated the phosphorylation levels of RIPK1, RIPK3 and MLKL to promote necroptosis in osteosarcoma.

CONCLUSIONS

The necroptosis prognostic signature and NS established in this study could be used as an independent prognostic factor, TNFRSF21 may be a necroptosis target in osteosarcoma therapy.

Comprehensive Analysis Reveals Prognostic and Therapeutic Immunity-Related Biomarkers for Pediatric Metastatic Osteosarcoma

Background and Objectives: Osteosarcoma, the most prevalent malignant bone tumor in children and adolescents, presents a complex pathogenesis characterized by various genetic and epigenetic alterations. This study aims to identify key differentially expressed genes (DEGs) in pediatric osteosarcoma, with a focus on those influencing metastasis and patient survival. Materials and Methods: We utilized the GSE33382 dataset from the GEO database for a comprehensive bioinformatic analysis. This included a protein-protein interaction (PPI) network analysis, Cox regression, and Kaplan-Meier survival analysis to identify central DEGs associated with osteosarcoma metastasis and patient survival. Results: Our analysis identified 88 DEGs related to osteosarcoma metastasis. Among them, three survival-related central DEGs-C1QA, CD74, and HLA-DMA-were significantly linked to patient outcomes. Further correlation analysis established a strong relationship between these genes, tumor mutation burden (TMB), immune checkpoint gene expression, and overall survival. Notably, C1QA and CD74 exhibited higher expression in non-metastatic osteosarcoma cases, suggesting a potential role in disease progression. Conclusions: The identified DEGs, particularly C1QA, CD74, and HLA-DMA, may serve as critical biomarkers for pediatric osteosarcoma prognosis and potential targets for immunotherapy. These findings provide a deeper understanding of the molecular landscape of osteosarcoma and open new avenues for therapeutic intervention.

Deciphering the heterogeneity and immunosuppressive function of regulatory T cells in osteosarcoma using single-cell RNA transcriptome

Osteosarcoma (OS) is a highly invasive malignant neoplasm with poor prognosis. The tumor microenvironment (TME) plays an essential role in the occurrence and development of OS. Regulatory T cells (Tregs) are known to facilitate immunosuppression, tumor progression, invasion, and metastasis. However, the effect of Tregs in the TME of OS remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) data was used to identify Tregs and various other cell clusters in the TME of OS. Gene set variation analysis (GSVA) was used to investigate the signaling pathways in Tregs from OS and adjacent tissues. The CellChat and iTALK packages were used to analyze cellular communication. In addition, a prognostic model was established based on the Tregs-specific genes using bulk RNA-seq from the TARGET database, and it was verified using a Gene Expression Omnibus dataset. The pRRophetic package was used to predict drug sensitivity. Immunohistochemistry was used to verify the expression of candidate genes in OS. Based on the above methods, we showed that the OS samples were highly infiltrated with Tregs. GSVA revealed that oxidative phosphorylation, angiogenesis and mammalian target of rapamycin complex 1 (mTORC1) were highly activated in Tregs from OS compared with those from adjacent tissues. Using cellular communication analysis, we found that Tregs interacted with osteoblastic, endothelial, and myeloid cells via C-X-C motif chemokine ligand (CXCL) signaling; particularly, they strongly affected the expression of C-X-C motif chemokine receptor 4 (CXCR4) and interacted with other cell clusters through CXCL12/transforming growth factor β1 (TGFB1) to collectively enable tumor growth and progression. Subsequently, two Tregs-specific genes-CD320 and MAF-were screened through univariate, least absolute shrinkage and selection operator regression (LASSO) and multivariate analysis to construct a prognostic model, which showed excellent prognostic accuracy in two independent cohorts. In addition, drug sensitivity analysis demonstrated that OS patients at high Tregs risk were sensitive to sunitinib, sorafenib, and axitinib. We also used immunohistochemistry to validate that CD320 and MAF were significantly upregulated in OS tissues compared with adjacent tissues. Overall, this study reveals the heterogeneity of Tregs in the OS TME, providing new insights into the invasion and treatment of this cancer.

Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application

Radiomics is the extraction of predefined mathematic features from medical images for predicting variables of clinical interest. Recent research has demonstrated that radiomics can be processed by artificial intelligence algorithms to reveal complex patterns and trends for diagnosis, and prediction of prognosis and response to treatment modalities in various types of cancer. Artificial intelligence tools can utilize radiological images to solve next-generation issues in clinical decision making. Bone tumors can be classified as primary and secondary (metastatic) tumors. Osteosarcoma, Ewing sarcoma, and chondrosarcoma are the dominating primary tumors of bone. The development of bone tumor model systems and relevant research, and the assessment of novel treatment methods are ongoing to improve clinical outcomes, notably for patients with metastases. Artificial intelligence and radiomics have been utilized in almost full spectrum of clinical care of bone tumors. Radiomics models have achieved excellent performance in the diagnosis and grading of bone tumors. Furthermore, the models enable to predict overall survival, metastases, and recurrence. Radiomics features have exhibited promise in assisting therapeutic planning and evaluation, especially neoadjuvant chemotherapy. This review provides an overview of the evolution and opportunities for artificial intelligence in imaging, with a focus on hand-crafted features and deep learning-based radiomics approaches. We summarize the current application of artificial intelligence-based radiomics both in primary and metastatic bone tumors, and discuss the limitations and future opportunities of artificial intelligence-based radiomics in this field. In the era of personalized medicine, our in-depth understanding of emerging artificial intelligence-based radiomics approaches will bring innovative solutions to bone tumors and achieve clinical application.

The diagnostic value of machine learning for the classification of malignant bone tumor: a systematic evaluation and meta-analysis

Background

Malignant bone tumors are a type of cancer with varying malignancy and prognosis. Accurate diagnosis and classification are crucial for treatment and prognosis assessment. Machine learning has been introduced for early differential diagnosis of malignant bone tumors, but its performance is controversial. This systematic review and meta-analysis aims to explore the diagnostic value of machine learning for malignant bone tumors.

Methods

PubMed, Embase, Cochrane Library, and Web of Science were searched for literature on machine learning in the differential diagnosis of malignant bone tumors up to October 31, 2022. The risk of bias assessment was conducted using QUADAS-2. A bivariate mixed-effects model was used for meta-analysis, with subgroup analyses by machine learning methods and modeling approaches.

Results

The inclusion comprised 31 publications with 382,371 patients, including 141,315 with malignant bone tumors. Meta-analysis results showed machine learning sensitivity and specificity of 0.87 [95% CI: 0.81,0.91] and 0.91 [95% CI: 0.86,0.94] in the training set, and 0.83 [95% CI: 0.74,0.89] and 0.87 [95% CI: 0.79,0.92] in the validation set. Subgroup analysis revealed MRI-based radiomics was the most common approach, with sensitivity and specificity of 0.85 [95% CI: 0.74,0.91] and 0.87 [95% CI: 0.81,0.91] in the training set, and 0.79 [95% CI: 0.70,0.86] and 0.79 [95% CI: 0.70,0.86] in the validation set. Convolutional neural networks were the most common model type, with sensitivity and specificity of 0.86 [95% CI: 0.72,0.94] and 0.92 [95% CI: 0.82,0.97] in the training set, and 0.87 [95% CI: 0.51,0.98] and 0.87 [95% CI: 0.69,0.96] in the validation set.

Conclusion

Machine learning is mainly applied in radiomics for diagnosing malignant bone tumors, showing desirable diagnostic performance. Machine learning can be an early adjunctive diagnostic method but requires further research and validation to determine its practical efficiency and clinical application prospects.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023387057.

Metabolism and senescence in the immune microenvironment of osteosarcoma: focus on new therapeutic strategies

Osteosarcoma is a highly aggressive and metastatic malignant tumor. It has the highest incidence of all malignant bone tumors and is one of the most common solid tumors in children and adolescents. Osteosarcoma tissues are often richly infiltrated with inflammatory cells, including tumor-associated macrophages, lymphocytes, and dendritic cells, forming a complex immune microenvironment. The expression of immune checkpoint molecules is also high in osteosarcoma tissues, which may be involved in the mechanism of anti-tumor immune escape. Metabolism and senescence are closely related to the immune microenvironment, and disturbances in metabolism and senescence may have important effects on the immune microenvironment, thereby affecting immune cell function and immune responses. Metabolic modulation and anti-senescence therapy are gaining the attention of researchers as emerging immunotherapeutic strategies for tumors. Through an in-depth study of the interconnection of metabolism and anti- senescence in the tumor immune microenvironment and its regulatory mechanism on immune cell function and immune response, more precise therapeutic strategies can be developed. Combined with the screening and application of biomarkers, personalized treatment can be achieved to improve therapeutic efficacy and provide a scientific basis for clinical decision-making. Metabolic modulation and anti- senescence therapy can also be combined with other immunotherapy approaches, such as immune checkpoint inhibitors and tumor vaccines, to form a multi-level and multi-dimensional immunotherapy strategy, thus further enhancing the effect of immunotherapy. Multidisciplinary cooperation and integrated treatment can optimize the treatment plan and maximize the survival rate and quality of life of patients. Future research and clinical practice will further advance this field, promising more effective treatment options for patients with osteosarcoma. In this review, we reviewed metabolic and senescence characteristics in the immune microenvironment of osteosarcoma and related immunotherapies, and provide a reference for development of more personalized and effective therapeutic strategies.

Advances in Osteosarcoma

PURPOSE OF REVIEW

This article gives a brief overview of the most recent developments in osteosarcoma treatment, including targeting of signaling pathways, immune checkpoint inhibitors, drug delivery strategies as single or combined approaches, and the identification of new therapeutic targets to face this highly heterogeneous disease.

RECENT FINDINGS

Osteosarcoma is one of the most common primary malignant bone tumors in children and young adults, with a high risk of bone and lung metastases and a 5-year survival rate around 70% in the absence of metastases and 30% if metastases are detected at the time of diagnosis. Despite the novel advances in neoadjuvant chemotherapy, the effective treatment for osteosarcoma has not improved in the last 4 decades. The emergence of immunotherapy has transformed the paradigm of treatment, focusing therapeutic strategies on the potential of immune checkpoint inhibitors. However, the most recent clinical trials show a slight improvement over the conventional polychemotherapy scheme. The tumor microenvironment plays a crucial role in the pathogenesis of osteosarcoma by controlling the tumor growth, the metastatic process and the drug resistance and paved the way of new therapeutic options that must be validated by accurate pre-clinical studies and clinical trials.

A meta-analysis: the clinical value of PD-1 inhibitor or protein tyrosine kinase inhibitors in the treatment of advanced osteosarcoma

Backgrounds

PD-1 inhibitors and TKIs have been used to treat advanced osteosarcoma, but there is still a lack of intuitive data for the comparison of their efficacy. We conducted a meta-analysis to evaluate their therapeutic benefits.

Methods

A systematic methodological search of five primary electronic databases was performed. Studies with a randomized design of any type about PD-1 inhibitors or TKIs for the treatment of advanced osteosarcoma were included. The primary outcomes mainly included CBR, PFS, OS and ORR, The CR, PR, SD and AEs were the secondary outcomes. The survival period (months) of patients was taken as the main analysis data. Random-effects models were used for meta-analysis.

Results

Eight immunocheckpoint inhibitors in 327 patients from 10 clinical trials were finally evaluated. For OS, TKIs [11.67 months (95% CI, 9.32-14.01)] show more obvious advantages than PD-1 inhibitors [6.37 months (95% CI, 3.96-8.78)]. For PFS, TKIs [4.79 months (95% CI, 3.33-6.24)] are longer than PD-1 inhibitors [1.46 months (95% CI, 1.23-1.69)]. Although there was no fatal event, attention should still be paid, especially during the combined application of PD-1 inhibitors with TKIs since their obvious AEs.

Conclusions

The findings of this study suggest that patients with advanced osteosarcoma, TKIs may be more beneficial than PD-1 inhibitors. TKIs combined with PD-1 inhibitors has a bright future in the treatment of advanced osteosarcoma, but we should always pay attention to the strong side effects.

Identification of a novel MYC target gene set signature for predicting the prognosis of osteosarcoma patients

Osteosarcoma is a primary malignant tumor found mainly in teenagers and young adults. Patients have very little long-term survival. MYC controls tumor initiation and progression by regulating the expression of its target genes; thus, constructing a risk signature of osteosarcoma MYC target gene set will benefit the evaluation of both treatment and prognosis. In this paper, we used GEO data to download the ChIP-seq data of MYC to obtain the MYC target gene. Then, a risk signature consisting of 10 MYC target genes was developed using Cox regression analysis. The signature indicates that patients in the high-risk group performed poorly. After that, we verified it in the GSE21257 dataset. In addition, the difference in tumor immune function among the low- and high-risk populations was compared by single sample gene enrichment analysis. Immunotherapy and prediction of response to the anticancer drug have shown that the risk signature of the MYC target gene set was positively correlated with immune checkpoint response and drug sensitivity. Functional analysis has demonstrated that these genes are enriched in malignant tumors. Finally, STX10 was selected for functional experimentation. STX10 silence has limited osteosarcoma cell migration, invasion, and proliferation. Therefore, these findings indicated that the MYC target gene set risk signature could be used as a potential therapeutic target and prognostic indicator in patients with osteosarcoma.

Managing the immune microenvironment of osteosarcoma: the outlook for osteosarcoma treatment

Osteosarcoma, with poor survival after metastasis, is considered the most common primary bone cancer in adolescents. Notwithstanding the efforts of researchers, its five-year survival rate has only shown limited improvement, suggesting that existing therapeutic strategies are insufficient to meet clinical needs. Notably, immunotherapy has shown certain advantages over traditional tumor treatments in inhibiting metastasis. Therefore, managing the immune microenvironment in osteosarcoma can provide novel and valuable insight into the multifaceted mechanisms underlying the heterogeneity and progression of the disease. Additionally, given the advances in nanomedicine, there exist many advanced nanoplatforms for enhanced osteosarcoma immunotherapy with satisfactory physiochemical characteristics. Here, we review the classification, characteristics, and functions of the key components of the immune microenvironment in osteosarcoma. This review also emphasizes the application, progress, and prospects of osteosarcoma immunotherapy and discusses several nanomedicine-based options to enhance the efficiency of osteosarcoma treatment. Furthermore, we examine the disadvantages of standard treatments and present future perspectives for osteosarcoma immunotherapy.

Characterization of the Tumor Microenvironment in Jaw Osteosarcomas, towards Prognostic Markers and New Therapeutic Targets

Background-The purpose of this study was to investigate the bone resorption, as well as the vascular and immune microenvironment, of jaw osteosarcomas (JO) and to correlate these features with patient clinical outcomes. Methods-We studied 50 JO biopsy samples by immunohistochemical analysis of tissue microarrays (TMAs). We investigated the bone remodeling markers RANK/RANKL/OPG, the endothelial glycoprotein CD146, and biomarkers of the immune environment (CD163 and CD68 of macrophages, CD4+ and CD8+ of tumor-infiltrating lymphocytes (TILs), and an immune checkpoint PD-1/PD-L1). The biomarkers were analyzed for their influence on progression (recurrence and metastasis), overall survival (OS), and disease-free survival (DFS). Results-A strong and significant correlation has been found between CD163 staining and lower OS and DFS. The level of CD4+ and CD8+ staining was low and non-significantly associated with survival outcomes. High levels of RANK and RANKL were found in the tumor samples and correlated with lower DFS. Conclusion-Our findings suggest that CD163+ TAMs represent markers of poor prognosis in JO. Targeting TAMs could represent a valuable therapeutic strategy in JO.