The contribution of immune infiltrates and the local microenvironment in the pathogenesis of osteosarcoma

Heparin and Heparin-Based Drug Delivery Systems: Pleiotropic Molecular Effects at Multiple Drug Resistance of Osteosarcoma and Immune Cells

One of the main problems of modern health care is the growing number of oncological diseases both in the elderly and young population. Inadequately effective chemotherapy, which remains the main method of cancer control, is largely associated with the emergence of multidrug resistance in tumor cells. The search for new solutions to overcome the resistance of malignant cells to pharmacological agents is being actively pursued. Another serious problem is immunosuppression caused both by the tumor cells themselves and by antitumor drugs. Of great interest in this context is heparin, a biomolecule belonging to the class of glycosaminoglycans and possessing a broad spectrum of biological activity, including immunomodulatory and antitumor properties. In the context of the rapid development of the new field of “osteoimmunology,” which focuses on the collaboration of bone and immune cells, heparin and delivery systems based on it may be of intriguing importance for the oncotherapy of malignant bone tumors. Osteosarcoma is a rare but highly aggressive, chemoresistant malignant tumor that affects young adults and is characterized by constant recurrence and metastasis. This review describes the direct and immune-mediated regulatory effects of heparin and drug delivery systems based on it on the molecular mechanisms of (multiple) drug resistance in (onco) pathological conditions of bone tissue, especially osteosarcoma.

PLOD2 high expression associates with immune infiltration and facilitates cancer progression in osteosarcoma

Background

Osteosarcoma (OS) is the most common primary malignant bone tumors in children and adolescents. Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 (PLOD2) is a key gene in mediating the formation of the stabilized collagen cross-link, playing an important role in the progression of cancer. However, the interaction between OS and PLOD2 has not been clarified so far.

Methods

The target gene PLOD2 was screened through our own RNA-seq results and other two RNA-seq results from GEO database. The expression of PLOD2 in OS was detected by RT-qPCR, Western blot and immunohistochemistry. Functional experiments were performed to investigate the role of PLOD2 in OS cell invasion, migration and angiogenesis in vitro. An OS lung metastasis model was established to investigate the function of PLOD2 in OS metastasis and angiogenesis in vivo. The role of PLOD2 in immune infiltration in OS was explored by KEGG/GO analysis and immune infiltration analysis with TARGET, TCGA and TIMER.

Results

PLOD2 was high-expressed in OS, which was related to poor prognosis of OS patients. PLOD2 promoted OS cell migration, invasion and angiogenesis in vitro and aggravated OS metastasis and angiogenesis in vivo. Bioinformatic analysis showed that PLOD2 played an important role in immune cell infiltration in OS, including CD8 positive T cells, macrophages M0 cells, DC cells, endothelial cells, iDC cells, ly endothelial cells, MEP cells, mv endothelial cells, native B cells, smooth muscle cells and Th1 cells. Immunohistochemical results showed that the expression of CD4 and CD8A was negatively correlated with the expression of PLOD2 in OS.

Conclusion

PLOD2 was high-expressed in OS and promoted OS migration, invasion and angiogenesis in vitro and facilitated OS metastasis and angiogenesis in vivo. PLOD2 was associated with immune cell infiltration in OS, which could be a promising target to treat OS patients with metastasis and utilized to guide clinical immunotherapy in the future.

Bioinformatics analysis of the key genes in osteosarcoma metastasis and immune invasion

BACKGROUND

This study sought to identify potential key genes for osteosarcoma metastasis and analyze their immune infiltration patterns using bioinformatic methods.

METHODS

We obtained transcriptomic data related to osteosarcoma and osteosarcoma with metastasis from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) and The Gene Expression Omnibus (GEO) databases and identified the differentially expressed genes (DEGs). We also identified potential key genes for osteosarcoma metastasis by a protein-protein interaction network analysis, and we conducted a Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify the core genes for prognosis, immune cell infiltration, and drug sensitivity, and the risk prediction and prognosis models of metastasis were constructed.

RESULTS

By comparing the transcriptome data of osteosarcomas without metastasis and those with metastasis, a total of 19 core DEGs were identified, and the GO and KEGG analyses revealed an association between these DEGs and the regulation of cell division, secretory granule lumen, the Ras-associated protein 1 (Rap1) signaling pathway, and the mitogen-activated protein kinase (MAPK) signaling pathway. Compared with other immune cells, macrophage infiltration was predominant in osteosarcoma samples with metastatic osteosarcoma, and insulin-like growth factors-1 (IGF1) and myelocytomatosis protein 2 (MYC2) genes were predicted to more than 50 targeted therapeutic agents. A metastasis prediction model with 5 genes [i.e., ecotropic viral integration site 2B (EVI2B), CCAAT/enhancer binding protein (CEBPA), lymphocyte cytosolic protein 2 (LCP2), selectin L (SELL), and Niemann-Pick disease, type C2A (NPC2A)], and a prognostic model with 4 genes [i.e., insulin-like growth factors-2 (IGF2), cathepsin O (CTSO), Niemann-Pick disease, type C2 (NPC2), and amyloid beta (A4) precursor protein-binding, family B, member 1 interacting protein (APBB1IP)] were developed.

CONCLUSIONS

We constructed a metastasis prediction model with 5 genes (i.e., EVI2B, CEBPA, LCP2, SELL, and NPC2A), and a prognostic model with 4 genes (i.e., IGF2, CTSO, NPC2, and APBB1IP) that may be potential biomarkers for osteosarcoma metastasis. Macrophages are the predominant immune infiltrating cells in osteosarcoma metastasis and may provide a new direction for the treatment of osteosarcoma.

Lipopolysaccharide-binding protein expression is associated to the metastatic status of osteosarcoma patients

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Intratumour Gram^- bacteria can be detected in OS.

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Enriched intratumour in Gram^- bacteria infiltrate is associated with local disease.

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A poor Gram^- bacteria infiltration may be predict a higher risk of metastasis.

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Immune stimulation of OS by LPS represents a potential therapeutic option.

Osteosarcoma (OS) is a rare malignant primary bone tumours characterized by a high genetic and cell composition heterogeneity. Unfortunately, despite the use of drug combinations and the recent development of immunotherapies, the overall survival has not improved in the last four decades. Due to the key role of the tumour microenvironment in the pathogenesis of OS, a better understanding of its microenvironment is mandatory to develop new therapeutic approaches. From retrospective biological cohorts of OS, we analysed by immunohistochemistry the presence of lipopolysaccharide (LPS)-binding protein (LBP) in diagnostic biopsies with local disease and compared their level of infiltration to patients suffering from metastatic status. LBP is considered as a marker of LPS exposure and can indirectly reflect the presence of Gram-negative microbiota. LBP were detected in the cytoplasm of OS cells as well as in tumour-associated macrophage. Tumour samples of patients with local disease were significantly enriched in LBP compared to tumour tissues of patients with metastatic status. Lung metastatic tissues showed similar level of LBP compared to paired primary tumours. Overall, this study strongly suggests the presence of Gram-negative bacteria in OS tissues and demonstrated their significant differential level according the metastatic status. This tumour-associated microbiome may help in the conceptualisation of new therapeutic approach to trigger efficient therapeutic responses against cancer.

Bioinformatics Analysis and Structure of Gastric Cancer Prognosis Model Based on Lipid Metabolism and Immune Microenvironment

OBJECTIVES

The reprogramming of lipid metabolism is a new trait of cancers. However, the role of lipid metabolism in the tumor immune microenvironment (TIME) and the prognosis of gastric cancer remains unclear.

METHODS

Consensus clustering was applied to identify novel subgroups. ESTIMATE, TIMER, and MCPcounter algorithms were used to determine the TIME of the subgroups. The underlying mechanisms were elucidated using functional analysis. The prognostic model was established using the LASSO algorithm and multivariate Cox regression analysis.

RESULTS

Three molecular subgroups with significantly different survival were identified. The subgroup with relatively low lipid metabolic expression had a lower immune score and immune cells. The differentially expressed genes (DEGs) were concentrated in immune biological processes and cell migration via GO and KEGG analyses. GSEA analysis showed that the subgroups were mainly enriched in arachidonic acid metabolism. Gastric cancer survival can be predicted using risk models based on lipid metabolism genes.

CONCLUSIONS

The TIME of gastric cancer patients is related to the expression of lipid metabolism genes and could be used to predict cancer prognosis accurately.

Construction of the prognostic enhancer RNA regulatory network in osteosarcoma

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Our enhancer RNAs-based prognostic model showed good predictive ability in osteosarcoma.

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CCAAT enhancer binding protein alpha (CEBPA) may regulate CD8A molecule (CD8A).

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CD8A activation may promote CD3E molecule (CD3E) expression and activate allograft rejection in CD8+ T cells.

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Above signal axis provided new insights in the mechanism of osteosarcoma tumorigenesis.

Background

Osteosarcoma (OS) is a common malignant tumor in osteoarticular system, the 5-year overall survival of which is poor. Enhancer RNAs (eRNAs) have been implicated in the tumorigenesis of various cancer types, whereas their roles in OS tumorigenesis remains largely unclear.

Methods

Differentially expressed eRNAs (DEEs), transcription factors (DETFs), target genes (DETGs) were identified using limma (Linear Models for Microarray Analysis) package. Prognosis-related DEEs were accessed by univariate Cox regression analysis. A multivariate model was constructed to evaluate the prognosis of OS samples. Prognosis-related DEEs, DETFs, DETGs, immune cells, and hallmark gene sets were co-analyzed to construct an regulatory network. Specific inhibitors were also filtered by connectivity Map analysis. External validation and scRNA-seq analysis were performed to verify our key findings.

Results

3,981 DETGs, 468 DEEs, 51 DETFs, and 27 differentially expressed hallmark gene sets were identified. A total of Multivariate risk predicting model based on 18 prognosis-related DEEs showed a high accuracy (area under curve (AUC) = 0.896). GW-8510 was the candidate inhibitor targeting prognosis-related DEEs (mean = 0.670, p < 0.001). Based on the OS tumorigenesis-related regulation network, we identified that CCAAT enhancer binding protein alpha (CEBPA, DETF) may regulate CD8A molecule (CD8A, DEE), thereby promoting the transcription of CD3E molecule (CD3E, DETG), which may affect allograft rejection based on CD8+ T cells.

Conclusion

We constructed an eRNA-based prognostic model for predicting the OS patients’ prognosis and explored the potential regulation network for OS tumorigenesis by an integrated bioinformatics analysis, providing promising therapeutic targets for OS patients.

A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA

Objective

Osteosarcoma (OS) is a common bone malignancy with poor prognosis. We aimed to investigate the relationship between cuproptosis-related lncRNAs (CRLncs) and the survival outcomes of patients with OS.

Methods

Transcriptome and clinical data of 86 patients with OS were downloaded from The Cancer Genome Atlas (TCGA). The GSE16088 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The 10 cuproptosis-related genes (CRGs) were obtained from a recently published article on cuproptosis in Science. Combined analysis of OS transcriptome data and the GSE16088 dataset identified differentially expressed CRGs related to OS. Next, pathway enrichment analysis was performed. Co-expression analysis obtained CRLncs related to OS. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the risk prognostic model of CRLncs. The samples were divided evenly into training and test groups to verify the accuracy of the model. Risk curve, survival, receiver operating characteristic (ROC) curve, and independent prognostic analyses were performed. Next, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the correlation between the risk prognostic models and OS immune microenvironment. Drug sensitivity analysis identified drugs with potential efficacy in OS. Real-time quantitative PCR, Western blotting, and immunohistochemistry analyses verified the expression of CRGs in OS. Real-time quantitative PCR was used to verify the expression of CRLncs in OS.

Results

Six CRLncs that can guide OS prognosis and immune microenvironment were obtained, including three high-risk CRLncs (AL645608.6, AL591767.1, and UNC5B-AS1) and three low-risk CRLncs (CARD8-AS1, AC098487.1, and AC005041.3). Immune cells such as B cells, macrophages, T-helper type 2 (Th2) cells, regulatory T cells (Treg), and immune functions such as APC co-inhibition, checkpoint, and T-cell co-inhibition were significantly downregulated in high-risk groups. In addition, we obtained four drugs with potential efficacy for OS: AUY922, bortezomib, lenalidomide, and Z.LLNle.CHO. The expression of LIPT1, DLAT, and FDX1 at both mRNA and protein levels was significantly elevated in OS cell lines compared with normal osteoblast hFOB1.19. The mRNA expression level of AL591767.1 was decreased in OS, and that of AL645608.6, CARD8-AS1, AC005041.3, AC098487.1, and UNC5B-AS1 was upregulated in OS.

Conclusion

CRLncs that can guide OS prognosis and the immune microenvironment and drugs that may have a potential curative effect on OS obtained in this study provide a theoretical basis for OS survival research and clinical decision-making.

Immune Microenvironment in Osteosarcoma: Components, Therapeutic Strategies and Clinical Applications

Osteosarcoma is a primary malignant tumor that tends to threaten children and adolescents, and the 5-year event-free survival rate has not improved significantly in the past three decades, bringing grief and economic burden to patients and society. To date, the genetic background and oncogenesis mechanisms of osteosarcoma remain unclear, impeding further research. The tumor immune microenvironment has become a recent research hot spot, providing novel but valuable insight into tumor heterogeneity and multifaceted mechanisms of tumor progression and metastasis. However, the immune microenvironment in osteosarcoma has been vigorously discussed, and the landscape of immune and non-immune component infiltration has been intensively investigated. Here, we summarize the current knowledge of the classification, features, and functions of the main infiltrating cells, complement system, and exosomes in the osteosarcoma immune microenvironment. In each section, we also highlight the complex crosstalk network among them and the corresponding potential therapeutic strategies and clinical applications to deepen our understanding of osteosarcoma and provide a reference for imminent effective therapies with reduced adverse effects.

Canine models of human cancer: Bridging the gap to improve precision medicine

Dogs are remarkable, adaptable, and dependable creatures that have evolved alongside humans while contributing tremendously to our survival. Our canine companions share many similarities to human disease, particularly cancer. With the advancement of next-generation sequencing technology, we are beginning to unravel the complexity of cancer and the vast intra- and intertumoral heterogeneity that makes treatment difficult. Consequently, precision medicine has emerged as a therapeutic approach to improve patient survival by evaluating and classifying an individual tumor's molecular profile. Many canine and human cancers share striking similarities in terms of genotypic, phenotypic, clinical, and histological presentations. Dogs are superior to rodent models of cancer because they are a naturally heterogeneous population in which tumors occur spontaneously, are exposed to similar environmental conditions, and show more similarities in key modulators of tumorigenesis and clinical response, including the immune system, drug metabolism, and gut microbiome. In this chapter, we will explore various canine models of human cancers and emphasize the dog's critical role in advancing precision medicine and improving the survival of both man and man's best friend.

Construction of an Immune-Related lncRNA Signature That Predicts Prognosis and Immune Microenvironment in Osteosarcoma Patients

Osteosarcoma is one of the most common bone tumors in teenagers. We hope to provide a reliable method to predict the prognosis of osteosarcoma and find potential targets for early diagnosis and precise treatment. To address this issue, we performed a detailed bioinformatics analysis based on the Cancer Genome Atlas (TCGA). A total of 85 osteosarcoma patients with gene expression data and clinicopathological features were included in this study, which was considered the entire set. They were randomly divided into a train set and a test set. We identified six lncRNAs (ELFN1-AS1, LINC00837, OLMALINC, AL669970.3, AC005332.4 and AC023157.3), and constructed a signature that exhibited good predictive ability of patient survival and metastasis. What’s more, we found that risk score calculated by the signature was positively correlated to tumor purity, CD4+ naive T cells, and negatively correlated to CD8+ T cells. Furthermore, we investigated each lncRNA in the signature and found that these six lncRNAs were associated with tumorigenesis and immune cells in the tumor microenvironment. In conclusion, we constructed and validated a signature, which had good performance in the prediction of survival, metastasis and immune microenvironment. Our study indicated possible mechanisms of these lncRNAs in the development of osteosarcoma, which may provide new insights into the precise treatment of osteosarcoma.

Novel Immunotherapies for Osteosarcoma

Osteosarcoma (OS) is the most common primary malignant bone sarcoma mainly affecting adolescents and young adults, which often progresses to pulmonary metastasis and leads to the death of OS patients. OS is characterized as a highly heterogeneous cancer type and the underlying pathologic mechanisms triggering tumor progress and metastasis are incompletely recognized. Surgery combined with neoadjuvant and postoperative chemotherapy has elevated 5-year survival to over 70% for patients with localized OS tumors, as opposed to only 20% of patients with recurrence and/or metastasis. Therefore, novel therapeutic strategies are needed to overcome the drawbacks of conventional treatments. Immunotherapy is gaining momentum for the treatment of OS with an increasing number of FDA-approved therapies for malignancies resistant to conventional therapies. Here, we review the OS tumor microenvironment and appraise the promising immunotherapies available in the management of OS.

Knockdown of CD44 inhibits proliferation, migration and invasion of osteosarcoma cells accompanied by downregulation of cathepsin S

BACKGROUND

Osteosarcoma (OS) is a malignant bone tumour of mesenchymal origin. These tumours are characterised by rich vascularisation, therefore promoting rapid proliferation and facilitating metastasis. CD44 has been reported to be involved in OS, but its role and molecular mechanisms in the pathogenesis of the disease are not fully determined.

METHODS

In this study, we investigated the antitumor effect of CD44 on the development of OS and further explored the molecular mechanisms. The expression of CD44, cathepsin S and MMP-9 was detected by Western blot (WB) and reverse transcription-polymerase chain reaction (RT-qPCR) in different cell lines (MG63, U2OS OS and hFOB 1.19). To elucidate the role of CD44 in OS, MG63 and U2OS cells were treated with small interference RNA (siRNA) to knock down CD44, and the knockdown efficiency was validated with GFP and RT-qPCR. Furthermore, cell proliferation was assayed using Cell Counting Kit‑8 (CCK-8) and colony formation assays, and cell migration and invasion were assayed by transwell and wound-healing assays.

RESULTS

We found that CD44 expression in the MG63 and U2OS OS cell lines was markedly increased compared to that of the human osteoblast hFOB 1.19 cell line. Knockdown of CD44 inhibited proliferation, migration and invasion of MG63 and U2OS cells. Cathepsin S expression in the MG63 and U2OS OS cell lines was increased compared to that of the human osteoblast hFOB 1.19 cell line. When CD44 was knocked down, its expression level went down.

CONCLUSION

Taken together, our data reinforced the evidence that CD44 knockdown inhibited cell proliferation, migration and invasion of OS cells accompanied by altered expression of cathepsin S. These findings offer new clues for OS development and progression, suggesting CD44 as a potential therapeutic target for OS.

Exosomal Long Non-Coding RNA ANCR Mediates Drug Resistance in Osteosarcoma

Osteosarcoma (OS) is rare cancer with bimodal age distribution with peaks observed in children and young adults. Typically, OS is treated with pre-surgery neoadjuvant therapy, surgical excision, and post-surgery chemotherapy. However, the efficacy of treatment on disease prognosis and objective response is not currently optimal, often resulting in drug resistance; in turn, highlighting the need to understand mechanisms driving resistance to therapy in OS patients. Using Doxycycline (Dox)-sensitive and resistant variants of OS cells lines KHOS and U2OS, we found that the resistant variants KHOS-DR and U2OS-DR have significantly higher in vitro proliferation. Treating the Dox-sensitive KHOS/U2OS cells with exosomes isolated from KHOS-DR/U2OS-DR made them resistant to treatment with Dox in vitro and in vivo and enhanced tumor growth and progression, while decreasing overall survival. Expression of the long non-coding RNA (lncRNA) ANCR was significantly higher in the KHOS-DR and U2OS-DR variants. SiRNA-mediated knockdown of ANCR decreased in vitro proliferation, while increasing sensitivity to Dox treatment in the KHOS-DR/U2OS-DR cells. Expression of the exosomal lncRNA ANCR was critical for drug resistance and OS tumor progression in xenografts and was correlated to resistance to Adriamycin and overall survival is patients with OS. These results establish lncRNA ANCR as a critical mediator of resistance to therapy in OS patients, highlighting it as a potential therapeutic target in OS patients.

Global Characterization of Metabolic Genes Regulating Survival and Immune Infiltration in Osteosarcoma

Background: The alterations in metabolic profile of tumors have been identified as one of the prognostic hallmarks of cancers, including osteosarcoma. These alterations are majorly controlled by groups of metabolically active genes. However, the regulation of metabolic gene signatures in tumor microenvironment of osteosarcoma has not been well explained.

Objectives: Thus, we investigated the sets of previously published metabolic genes in osteosarcoma patients and normal samples.

Methods: We applied computational techniques to identify metabolic genes involved in the immune function of tumor microenvironment (TME) and survival and prognosis of the osteosarcoma patients. Potential candidate gene PAICS (phosphoribosyl aminoimidazole carboxylase, phosphoribosyl aminoimidazole succino carboxamide synthetase) was chosen for further studies in osteosarcoma cell lines for its role in cell proliferation, migration and apoptosis.

Results: Our analyses identified a list of metabolic genes differentially expressed in osteosarcoma tissues. Next, we scrutinized the list of genes correlated with survival and immune cells, followed by clustering osteosarcoma patients into three categories: C1, C2, and C3. These analyses led us to choose PAICS as potential candidate gene as its expression showed association with poor survival and negative correlation with the immune cells. Furthermore, we established that loss of PAICS induced apoptosis and inhibited proliferation, migration, and wound healing in HOS and MG-63 cell lines. Finally, the results were supported by constructing and validating a prediction model for prognosis of the osteosarcoma patients.

Conclusion: Here, we conclude that metabolic genes specifically PAICS play an integral role in the immune cell infiltration in osteosarcoma TME, as well as cancer development and metastasis.

Development of Personalized Signature Based on the Immune Landscape to Predict the Prognosis of Osteosarcoma and the Response to Immunotherapy and Targeted Therapy

As a heterogeneous and aggressive disease, osteosarcoma (OS) faces great challenges to prognosis and individualized treatment. Hence, we explore the role of immune-related genes in predicting prognosis and responsiveness to immunotherapy and targeted therapies in patients with OS based on the immunological landscape of osteosarcoma. Based on the database of the Therapeutical Applicable Research to Generate Effective Treatments (TARGET), single-sample gene set enrichment analysis (ssGSEA) was used to obtain the enrichment scores of 29 immune characteristics. A series of bioinformatics methods were performed to construct the immune-related prognostic signature (IRPS). Gene set enrichment analysis and gene set variation analysis were used to explore the biological functions of IRPS. We also analyzed the relationship between IRPS and tumor microenvironment. Lastly, the reactivity of IRPS to immune checkpoint therapy and targeted drugs was explored. The ssGSEA algorithm was used to define two immune subtypes, namely Immunity_High and Immunity_Low. Immunity_High was associated with a good prognosis and was an independent prognostic factor of OS. The IRPS containing 7 genes was constructed by the least absolute shrinkage and selection operator Cox regression. The IRPS can divide patients into low- and high-risk patients. Compared with high-risk patients, low-risk patients had a better prognosis and were positively correlated with immune cell infiltration and immune function. Low-risk patients benefited more from immunotherapy, and the sensitivity of targeted drugs in high- and low-risk groups was determined. IRPS can be used to predict the prognosis of OS patients, and provide therapeutic responsiveness to immunotherapy and targeted therapy.

Local treatment of a pediatric osteosarcoma model with a 4-1BBL armed oncolytic adenovirus results in an antitumor effect and leads to immune memory

Osteosarcoma is an aggressive bone tumor occurring primarily in pediatric patients. Despite years of intensive research, the outcomes of patients with metastatic disease or who do not respond to therapy have remained poor and have not changed in the last 30 years. Oncolytic virotherapy is becoming a reality to treat local and metastatic tumors while maintaining a favorable safety profile. Delta-24-ACT is a replicative oncolytic adenovirus engineered to selectively target cancer cells and to potentiate immune responses through expression of the immune costimulatory ligand 4-1BB. This work aimed to assess the antisarcoma effect of Delta-24-ACT. MTS and replication assays were used to quantify the antitumor effects of Delta-24-ACT in vitro in osteosarcoma human and murine cell lines. Evaluation of the in vivo antitumor effect and immune response to Delta-24-ACT was performed in immunocompetent mice bearing orthotopic K7M2 cell line. Immunophenotyping of the tumor microenvironment was characterized by immunohistochemistry and flow cytometry. In vitro, Delta-24-ACT killed osteosarcoma cells and triggered the production of danger signals. In vivo, local treatment with Delta-24-ACT led to antitumor effects against both the primary tumor and spontaneous metastases in a murine osteosarcoma model. Viral treatment was safe, with no noted toxicity. Delta-24-ACT significantly increased the median survival time of treated mice. Collectively, our data identify Delta-24-ACT administration as an effective and safe therapeutic strategy for local and metastatic osteosarcoma. These results support clinical translation of this viral immunotherapy approach.

Click Pt(IV)-Carbohydrates Pro-Drugs for Treatment of Osteosarcoma

The selectivity vs. cancer cells has always been a major challenge for chemotherapeutic agents and in particular for cisplatin, one of the most important anticancer drugs for the treatment of several types of tumors. One strategy to overtake this challenge is to modify the coordination sphere of the metallic center with specific vectors whose receptors are overexpressed in the tumoral cell membrane, such as monosaccharides. In this paper, we report the synthesis of four novel glyco-modified Pt(IV) pro-drugs, based on cisplatin scaffold, and their biological activity against osteosarcoma (OS), a malignant tumor affecting in particular adolescents and young adults. The sugar moiety and the Pt scaffold are linked exploiting the Copper Azide Alkyne Cycloaddition (CUAAC) reaction, which has become the flagship of click chemistry due to its versatility and mild conditions. Cytotoxicity and drug uptake on three different OS cell lines as well as CSCs (Cancer Stem Cell) are described.

Exploration and Validation of a Novel Inflammatory Response-Associated Gene Signature to Predict Osteosarcoma Prognosis and Immune Infiltration

Background

Inflammatory response took part in the progression of tumor and was regarded as the hallmark of cancer. However, the prognostic relationship between osteosarcoma and inflammatory response-associated genes (IRGs) was unclear. This research aimed to explore the correlations between osteosarcoma prognosis and IRG signature.

Methods

The inflammatory response-associated differentially expressed messenger RNAs (DEmRNAs) were screened out through Gene Expression Omnibus (GEO) and Molecular Signature Database (MSigDB) databases. Univariate and multivariate cox regression analyses were utilized to construct the IRG signature. The prognostic value of signature was investigated through Kaplan–Meier (KM) survival curve and nomogram. DEmRNAs among high and low inflammatory response-associated risks were identified and functional enrichment analyses were conducted. ESTIMATE, CIBERSORT and single-sample gene set enrichment analyses (ssGSEA) were implied to reveal the alterations in immune infiltration. All the above results were validated in Target database. The expression of IRGs was also validated in different cell lines by quantitative real-time PCR (qRT-PCR) and osteosarcoma patient samples by immunohistochemistry.

Results

The IRG signature that consisted of two genes (MYC, CLEC5A) was established. In training and validation datasets, patients with lower risk scores survived longer and the IRG signature was confirmed as the independent prognostic factor in osteosarcoma. The nomogram was constructed and the calibration curves demonstrated the reliability of this model. Functional analysis of risk score-associated DEmRNAs indicated that immune-related pathways and functions were significantly enriched. ssGSEA revealed that 14 immune cells and 11 immune functions were significantly dysregulated. The qRT-PCR results indicated IRGs were significantly differently expressed in osteosarcoma and osteoblast cell lines. The immunohistochemistry analyses of patients’ samples revealed the same result.

Conclusion

The novel osteosarcoma inflammatory response-associated prognostic signature was established and validated in this study. This model could serve as the biomarker and therapeutic target for osteosarcoma in the future.

Pyroptosis-Related Gene Signature Is a Novel Prognostic Biomarker for Sarcoma Patients

Sarcoma is a rare and an extremely aggressive form of cancer that originates from mesenchymal cells. Pyroptosis exerts a dual effect on tumours by inhibiting tumour cell proliferation while creating a microenvironment suitable for tumour cell development and proliferation. However, the significance of pyroptosis-related gene (PRG) expression in sarcoma has not yet been evaluated. Here, we conduct a retrospective analysis to examine PRG expression in 256 sarcoma samples from The Cancer Genome Atlas database. We identified the PRGs that had a significant correlation with overall patient survival in sarcoma by performing a univariate Cox regression analysis. Subsequently, we conducted a LASSO regression analysis and created a risk model for a six-PRG signature. As indicated from the Kaplan–Meier analysis, this signature revealed a significant difference between high- and low-risk sarcoma patients. A receiver operating characteristic curve analysis confirmed that this signature could predict overall patient survival in sarcoma patients with high sensitivity and specificity. Gene ontology annotation and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses revealed that five independent PRGs were closely associated with increased immune activity. Moreover, we also deciphered that increased number of immune cells infiltrated the tumour microenvironment in sarcoma. In brief, the PRG signature can effectively act as novel prognostic biomarker for sarcoma patients and is associated with the tumour immune microenvironment.

Immune Checkpoint Inhibitor Therapy for Bone Metastases: Specific Microenvironment and Current Situation

The treatment of bone metastases is a thorny issue. Immunotherapy may be one of the few hopes for patients with unresectable bone metastases. Immune checkpoint inhibitors are the most commonly used immunotherapy drugs currently. In this review, the characteristics and interaction of bone metastases and their immune microenvironment were systematically discussed, and the relevant research progress of the immunological mechanism of tumor bone metastasis was reviewed. On this basis, we expounded the clinical application of immune checkpoint inhibitors for bone metastasis of common tumors, including non-small-cell lung cancer, renal cell carcinoma, prostate cancer, melanoma, and breast cancer. Then, the deficiencies and limitations in current researches were summarized. In-depth basic research on bone metastases and optimization of clinical treatment is needed.

Tumor-Infiltrating Lymphocytes and Cancer Markers in Osteosarcoma: Influence on Patient Survival

Simple Summary

Osteosarcoma (OST) is the most common type of high-grade primary bone tumor, which mainly affects young adults. Despite the efforts that have been made to address the importance of immune-related factors in OST, there is still a lot to understand. The purpose of the current study was to evaluate the tumor-infiltrating lymphocytes (TIL), the expression of proteins involved in tumor biology, and their impact on the clinical outcome of OST patients. Our results suggest that the presence of tumor-infiltrating CD4+ cells provides protection to patients, and that CD8+ cells have a significant impact on the patient’s overall survival (OS) and progression-free survival (PFS). In addition, a strong association of tumor-infiltrating CD4+ cells and the presence of CD44s expression in tumor samples was observed. These findings reinforce the idea that TIL and the expression of tumor markers should be taken into consideration in order to improve OST treatment and management.

Abstract

Osteosarcoma (OST) is the most common type of high-grade primary bone tumor, which mainly affects young adults. The current standard of care for OST combines surgical resection with chemotherapy. The clinical outcomes and the current options to treat OST patients are unsatisfactory and novel treatment strategies are needed. The crosstalk between tumor cells and immune cells is essential to the OST microenvironment. Despite the efforts that have been made to address the importance of immune-related factors in OST, there is still a lot to understand. The purpose of the current study was to evaluate the tumor-infiltrating lymphocytes (TIL), the expression of proteins involved in tumor biology, and their impact on the clinical outcome of OST patients. We studied 93 samples of OST patients using immunohistochemistry and histomorphometry. We looked for the infiltration of CD3+, CD4+, CD8+, TIA1+ and CD20+ cells and for the expression of CD44 standard (CD44s) and variant 6 (CD44v6), CD95/Fas, Fas-L, p53 and p-glycoprotein. All the parameters were analyzed for the influence on the occurrence of death and metastasis, plus patient overall survival (OS) and progression-free survival (PFS). The effect of sex, age, tumor location (distal femur or proximal tibia) and the combination with neoadjuvant chemotherapy was also assessed. Our results suggest that the presence of tumor-infiltrating CD4+ cells provides protection to OST patients, and that CD8+ cells have a significant impact on the patient’s overall survival (OS) and progression-free survival (PFS), which is more evident in male patients. In addition, a strong association between tumor-infiltrating CD4+ cells and the presence of CD44s expression in tumor samples was observed. Analysis of TIL and tumor markers related to tumor biology could be useful to stratify patients and monitor the response to therapy, as well as to assist with the development of immunotherapy strategies to improve the effects of cytotoxic TIL to eradicate the tumor cells.

The Effect of miR-138 on the Function of Follicular Helper T Cells and the Differentiation of B Cells in Osteosarcoma

OBJECTIVE

To explore the effect of miR-138 on the function of follicular helper T (Tfh) cells and the differentiation of B cells in osteosarcoma.

METHODS

Clinically collect peripheral blood from osteosarcoma (OS) patients and healthy volunteers (HC), as well as OS tumor tissues (OS tumor) and adjacent tissues with normal histology (normal group). The CD4+CXCR5+Tfh cells of OS patients were screened and isolated by flow cytometry, and the expression of Tfh cell membrane surface antigens PD-1 and CTLA-4 was detected. In addition, qRT-PCR was used to detect the expression of miR-138 in tissues and Tfh cells, and the correlation relationship between miR-138 and PD-1 and CTLA-4 was analyzed. After interference or overexpression of miR-138 in Tfh cells, coculture with untreated B cells was done, and the levels of IL-10, IL-12, IL-21, and INF-γ in Tfh cell culture medium and the levels of IgM, IgG, and IgA in B cell culture medium after coculture were measured by ELISA. Flow cytometry was used to detect the expression of B cell membrane surface antigens CD27 and CD38 after coculture.

RESULTS

The rate of PD-1- and CTLA-4 positive cells in the peripheral blood and tissues of the OS group was significantly increased, the expression of miR-138 was significantly reduced, and the expression of miR-138 was negatively correlated with the expression of PD-1 and CTLA-4. In addition, upregulation of miR-138 can lead to a significant increase in the level of IL-10 in the supernatant of Tfh cells and a significant decrease in the levels of IL-12, IL-21, and INF-γ, which in turn leads to increased levels of IgM, IgG, and IgA released by B cells. At the same time, it significantly increases the rate of CD27- and CD38-positive cells and promotes the maturation of B cells. Downregulating miR-138 has the opposite effect.

CONCLUSION

Downregulating the expression of miR-138 in osteosarcoma can improve the dysfunction of CD4+CXCR5+Tfh cells and promote the differentiation of B cells.

Tumor-associated macrophages in osteosarcoma

Osteosarcoma (OS) is the most common primary bone tumor in children and adolescents. It is an aggressive tumor with a tendency to spread to the lung, which is the most common site of metastasis. Patients with advanced OS with metastases have poor prognoses despite the application of chemotherapy, thus highlighting the need for novel therapeutic targets. The tumor microenvironment (TME) of OS is confirmed to be essential for and supportive of tumor growth and dissemination. The immune component of the OS microenvironment is mainly composed of tumor-associated macrophages (TAMs). In OS, TAMs promote tumor growth and angiogenesis and upregulate the cancer stem cell-like phenotype. However, TAMs inhibit the metastasis of OS. Therefore, much attention has been paid to investigating the mechanism of TAMs in OS development and the progression of immunotherapy for OS. In this article, we aim to summarize the roles of TAMs in OS and the major findings on the application of TAMs in OS treatment.

Development of an immune-related signature for predicting survival outcome and immunotherapy response in osteosarcoma

Osteosarcoma (OS) is the most common bone cancer, mainly diagnosed in children and adolescents. So far, no reliable molecular biomarkers have been identified to effectively evaluate OS prognosis and immune infiltration. Herein, we curated transcriptome profiles and clinical information from the publicly available OS cohorts to establish an immune-related prognostic signature. Besides, immunotherapeutic cohorts of urothelial cancer and melanoma patients were also employed to infer immunotherapy prediction roles of the identified signature. Lymphocytes infiltration, immune response-related pathways and signatures in the microenvironment were assessed according to distinct risk subgroups. Based on the univariate Cox analysis and further feature selection implemented by the LASSO regression model in the TARGET cohort, a 21-immune-gene signature was identified by combing the expression values and corresponding coefficients. We observed that the low-risk score of this signature was significantly linked with the preferable survival outcome (Log-rank test P < 0.001). The consistent results of better prognoses of the low-risk group were also obtained in subsequent two validation cohorts. Immunology analyses showed that favorable immune infiltration and elevated enrichment of immune response signals may contribute to the better outcome of the low-risk OS subgroup. The immunotherapeutic efficacy analyses demonstrated that low-risk patients harbored significantly enhanced response rates and improved immunotherapy survival outcomes. Together, our established signature could evaluate survival risk and represent the immune microenvironment status of OS, which promotes precision treatment and provides a potential biomarker for prognosis prediction and immunotherapy efficacy assessment.

T cell exhaustion drives osteosarcoma pathogenesis

Background

Osteosarcoma (OS) is a rare cancer with a bimodal age distribution that peaks in children and young adults. It has been shown that the expression of programmed cell death protein 1 (PD-1) and programmed death ligand-1 (PD-L1) on tumor-infiltrating immune cells negatively correlates with prognosis of OS patients. However, a comprehensive assessment of the tumor-infiltrating immune cells in OS and their function has not been performed.

Methods

CD8⁺ T cells were isolated from biopsy tissue samples collected from OS patients and control subjects. Mass cytometry, Treg suppression assay, mixed lymphocyte reaction assay, and effector T cell functional assay were performed to analyze the function of tumor-infiltrating T cells. A xenograft metastasis model was established in BALB/c nude mice.

Results

Macrophages and CD3⁺ T cells comprised most of the tumor-infiltrating immune cells in OS, with a disproportionately higher number of helper CD4⁺ T cells than effector CD8⁺ T cells. Whereas the tumor-infiltrating regulatory T cells were functionally intact, the CD8⁺ T cells showed increased expression of the immune checkpoint receptor (ICR) PD-1 and T cell immunoglobulin and mucin-domain containing 3 (TIM3) and were functionally inactive. TIM3 blockade using a monoclonal antibody restored the T cell alloreactive function of the CD8⁺ T cells ex vivo. TIM3 blockade in a xenograft model of OS impaired tumor growth in vivo. TIM3 blockade decreased the number of tumor-infiltrating CD4⁺ T cells while increasing the numbers and functional activation of tumor-infiltrating CD8⁺ T cells in vivo.

Conclusions

These results highlight that TIM3 blockade might be a viable therapeutic option and should be tested in additional preclinical models.

Avenues of research in dietary interventions to target tumor metabolism in osteosarcoma

Osteosarcoma (OS) is the most frequent primary bone cancer, affecting mostly children and adolescents. Although much progress has been made throughout the years towards treating primary OS, the 5-year survival rate for metastatic OS has remained at only 20% for the last 30 years. Therefore, more efficient treatments are needed. Recent studies have shown that tumor metabolism displays a unique behavior, and plays important roles in tumor growth and metastasis, making it an attractive potential target for novel therapies. While normal cells typically fuel the oxidative phosphorylation (OXPHOS) pathway with the products of glycolysis, cancer cells acquire a plastic metabolism, uncoupling these two pathways. This allows them to obtain building blocks for proliferation from glycolytic intermediates and ATP from OXPHOS. One way to target the metabolism of cancer cells is through dietary interventions. However, while some diets have shown anticancer effects against certain tumor types in preclinical studies, as of yet none have been tested to treat OS. Here we review the features of tumor metabolism, in general and about OS, and propose avenues of research in dietary intervention, discussing strategies that could potentially be effective to target OS metabolism.

Low GNG12 Expression Predicts Adverse Outcomes: A Potential Therapeutic Target for Osteosarcoma

Background

G protein subunit gamma 12 (GNG12) is observed in some types of cancer, but its role in osteosarcoma is unknown. This study hypothesized that GNG12 may be a potential biomarker and therapeutic target. We aimed to identify an association between GNG12 and osteosarcoma based on the Gene Expression Omnibus and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) databases.

Methods

Osteosarcoma samples in GSE42352 and TARGET database were selected as the test cohorts. As the external validation cohort, 78 osteosarcoma specimens from The Second Affiliated Hospital of Nanchang University were collected. Patients with osteosarcoma were divided into high and low GNG12 mRNA-expression groups; differentially expressed genes were identified as GNG12-related genes. The biological function of GNG12 was annotated using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and immune infiltration analysis. Gene expression correlation analysis and competing endogenous RNA regulatory network construction were used to determine potential biological regulatory relationships of GNG12. Overall survival, Kaplan–Meier analysis, and log-rank tests were calculated to determine GNG12 reliability in predicting survival prognosis.

Results

GNG12 expression decreased in osteosarcoma samples. GNG12 was a highly effective biomarker for osteosarcoma [area under the receiver operating characteristic (ROC) curve (AUC) = 0.920], and the results of our Kaplan–Meier analysis indicated that overall survival and progression-free survival differed significantly between low and high GNG-expression group (p < 0.05). Functional analyses indicated that GNG12 may promote osteosarcoma through regulating the endoplasmic reticulum. Expression correlation analysis and competing endogenous RNA network construction showed that HOTTIP/miR-27a-3p may regulate GNG12 expression. Furthermore, the subunit suppresses adaptive immunity via inhibiting M1 and M2 macrophage infiltration. GNG12 was inhibited in metastatic osteosarcoma compared with non-metastatic osteosarcoma, and its expression predicted survival of patients (1, 3, and 5-year AUCs were 0.961, 0.826, and 0.808, respectively).

Conclusion

This study identified GNG12 as a potential biomarker for osteosarcoma prognosis, highlighting its potential as an immunotherapy target.

Vitamin B6 as a novel risk biomarker of fractured ankles

ABSTRACT

Ankle fractures are the most common intra-articular fractures. Osteoporosis is a common and frequent disease among the elderly with a poor prognosis and high risk of fractured ankles. However, the relationship between vitamin B6 and the incidence of fractured ankles in patients with osteoporosis is unclear.A total of 101 patients with osteoporosis were recruited. Clinical and followed-up information was recorded. And the vitamin B6, albumin, globulin, and hemoglobin in the blood were tested. Pearson's chi-squared and spearman test were performed to analyze the correlation between fractured ankles and relative parameters. Univariate and multivariate logistic regression, receiver operating characteristic curve analysis, univariate and multivariate Cox proportional hazards regression analysis, and Kaplan-Meier method were also performed.There exist strong relation between the expression level of vitamin B6 and fractured ankle (P < .001). The expression of vitamin B6 [Odd ratio (OR) = 12.071, 95% confidence interval (CI): 4.69-31.143, P < .001] has a clear correlation with whether the patients have fractured ankles via the univariate logistic regression analysis. In terms of multivariate logistic regression level, vitamin B6 (OR = 15.384, 95% CI:5.195-45.556, P < .001) was significantly associated with fractured ankle. In addition, expression level of vitamin B6 [hazard ratio (HR) = 11.684, 95% CI: 6.419-21.267, P < .001] was significantly associated with Maintenance time from recovery to recurrence (MRTT) of patients with osteoporosis.Enhanced vitamin B6 is significantly correlated with the poor prognosis of patients with osteoporosis and the increasing incidence of fractured ankles.

Impact of ABC Transporters in Osteosarcoma and Ewing's Sarcoma: Which Are Involved in Chemoresistance and Which Are Not?

The ATP-binding cassette (ABC) transporter superfamily consists of several proteins with a wide repertoire of functions. Under physiological conditions, ABC transporters are involved in cellular trafficking of hormones, lipids, ions, xenobiotics, and several other molecules, including a broad spectrum of chemical substrates and chemotherapeutic drugs. In cancers, ABC transporters have been intensely studied over the past decades, mostly for their involvement in the multidrug resistance (MDR) phenotype. This review provides an overview of ABC transporters, both related and unrelated to MDR, which have been studied in osteosarcoma and Ewing's sarcoma. Since different backbone drugs used in first-line or rescue chemotherapy for these two rare bone sarcomas are substrates of ABC transporters, this review particularly focused on studies that have provided findings that have been either translated to clinical practice or have indicated new candidate therapeutic targets; however, findings obtained from ABC transporters that were not directly involved in drug resistance were also discussed, in order to provide a more complete overview of the biological impacts of these molecules in osteosarcoma and Ewing's sarcoma. Finally, therapeutic strategies and agents aimed to circumvent ABC-mediated chemoresistance were discussed to provide future perspectives about possible treatment improvements of these neoplasms.

ANXA1 as a Prognostic and Immune Microenvironmental Marker for Gliomas Based on Transcriptomic Analysis and Experimental Validation

The tumor microenvironment (TME) plays an important role in the growth and invasion of glioma. This study aimed to analyze the composition of the immune microenvironment in glioma samples and analyze the important differentially expressed genes to identify novel immune-targeted therapy for glioma. We downloaded transcriptomic data of 669 glioma samples from The Cancer Genome Atlas database. CIBERSORT and ESTIMATE methods were used to calculate the proportion of tumor-infiltrating immune cells and ratio of immune and stromal components in the TME. The differentially expressed genes (DEGs) were screened by comparing the genes expressed by both stromal and immune cells. Annexin A1 (ANXA1) was determined to be an important prognostic indicator through the common overlap of univariate Cox regression analysis and protein–protein interaction network analysis. The proportion of tumor-infiltrating immune cells, calculated by CIBERSORT algorithm, had a significant difference in distribution among the high and low ANXA1 expression groups, indicating that ANXA1 could be an important immune marker of TME. Furthermore, ANXA1 level was positively correlated with the histopathological factors and negatively related to the survival of glioma patients based on the analysis of multiple databases. Finally, in vitro experiments verified that antagonizing ANXA1 expression promoted cell apoptosis and inhibited the invasion and migration capacities of glioma cells. Therefore, ANXA1 due to its immune-related functions, can be an important prognostic indicator and immune microenvironmental marker for gliomas. Further studies are warranted to confirm ANXA1 as a potential immunotherapeutic target for gliomas.

The smac mimetic LCL161 targets established pulmonary osteosarcoma metastases in mice

Osteosarcoma is the most common form of primary bone cancer and frequently metastasizes to the lungs. Current therapies fail to successfully treat over two thirds of patients with metastatic osteosarcoma, so there is an urgent imperative to develop therapies that effectively target established metastases. Smac mimetics are drugs that work by inhibiting the pro-survival activity of IAP proteins such as cIAP1 and cIAP2, which can be overexpressed in osteosarcomas. In vitro, osteosarcoma cells are sensitive to a range of Smac mimetics in combination with TNFα. This sensitivity has also been demonstrated in vivo using the Smac mimetic LCL161, which inhibited the growth of subcutaneous and intramuscular osteosarcomas. Here, we evaluated the efficacy of LCL161 using mice bearing osteosarcoma metastases without the presence of a primary tumor, modeling the scenario in which a patient's primary tumor had been surgically removed. We demonstrated the ability of LCL161 as a single agent and in combination with doxorubicin to inhibit the growth of, and in some cases eliminate, established pulmonary osteosarcoma metastases in vivo. Resected lung metastases from treated and untreated mice remained sensitive to LCL161 in combination with TNFα ex vivo. This suggested that there was little to no acquired resistance to LCL161 treatment in surviving osteosarcoma cells and implied that tumor microenvironmental factors underlie the observed variation in responses to LCL161.

Investigating Optimal Chemotherapy Options for Osteosarcoma Patients through a Mathematical Model

Simple Summary

Osteosarcoma is a rare type of cancer with poor prognoses. However, to the best of our knowledge, there are no mathematical models that study the impact of chemotherapy treatments on the osteosarcoma microenvironment. In this study, we developed a data driven mathematical model to analyze the dynamics of the important players in three groups of osteosarcoma tumors with distinct immune patterns in the presence of the most common chemotherapy drugs. The results indicate that the treatments’ start times and optimal dosages depend on the unique growth rate of the tumor, which implies the necessity of personalized medicine. Furthermore, the developed model can be extended by others to build models that can recommend individual-specific optimal dosages.

Abstract

Since all tumors are unique, they may respond differently to the same treatments. Therefore, it is necessary to study their characteristics individually to find their best treatment options. We built a mathematical model for the interactions between the most common chemotherapy drugs and the osteosarcoma microenvironments of three clusters of tumors with unique immune profiles. We then investigated the effects of chemotherapy with different treatment regimens and various treatment start times on the behaviors of immune and cancer cells in each cluster. Saliently, we suggest the optimal drug dosages for the tumors in each cluster. The results show that abundances of dendritic cells and HMGB1 increase when drugs are given and decrease when drugs are absent. Populations of helper T cells, cytotoxic cells, and IFN-γ grow, and populations of cancer cells and other immune cells shrink during treatment. According to the model, the MAP regimen does a good job at killing cancer, and is more effective than doxorubicin and cisplatin combined or methotrexate alone. The results also indicate that it is important to consider the tumor’s unique growth rate when deciding the treatment details, as fast growing tumors need early treatment start times and high dosages.

Exploration of Immune-Related Gene Expression in Osteosarcoma and Association With Outcomes

IMPORTANCE

Host immune dysregulation is associated with initiation and development of osteosarcoma. In addition, immunotherapy for osteosarcomas requires some knowledge of the immune state of patients.

OBJECTIVE

To perform an immunogenomic landscape analysis based on The Cancer Genome Atlas (TCGA) project, which provides osteosarcoma samples with clinical information.

DESIGN, SETTING, AND PARTICIPANTS

This genetic association study was conducted from July 20, 2020, to September 20, 2020, as a secondary analysis of public data. Cox regression and risk score analyses were used to construct signatures of immune-related genes (IRGs) in 84 patients with osteosarcoma from TCGA with corresponding clinical information. Patients were divided into high- and low-risk groups with 42 individuals in each group according to their risk scores. Data were analyzed from July 20 to September 20, 2020.

MAIN OUTCOMES AND MEASURES

Differentially expressed genes (DEGs) were analyzed between groups, and potential molecular mechanisms, expression regulation, and immune cell infiltration were also explored using bioinformation methods. A prognostic model based on independent risk factors selected from multivariate Cox hazard ratio regression was established to estimate 1-year overall survival.

RESULTS

In this genetic association study based on 84 samples from patients with osteosarcoma from TCGA (mean [SD] age, 15.0 [4.8] years; 47 [56.0%] men; mean [SD] follow-up time, 4.1 [2.8] years), a total of 14 survival-associated IRGs were identified. Patients assigned to the high-risk group had worse survival than patients from the low-risk group (1 death [2.4%] vs 26 deaths [61.9%%]; P < .001). The protein digestion and absorption pathway was one of the associated pathways in the functional enrichment analysis (gene ratio, 2:8; P < .001). The prognostic model based on metastases at diagnosis and risk score performed well in 1-year overall survival estimations (area under the curve, 0.947; 95% CI, 0.832-0.972). The risk score was correlated with immune cell infiltration (B cells: r = 0.331; P = .002; macrophages: r = 0.410; P < .001; CD8 T cells: r = 0.230; P = .04).

CONCLUSIONS AND RELEVANCE

This genetic association study developed a prognostic modeling tool for osteosarcoma based on IRG expression profiles, which could result in improved survival rates through more individualized therapies. Further research on IRG expression profiles could provide potential targets for future studies on immune treatment for osteosarcoma.

In vitro three-dimensional cell cultures for bone sarcomas

Bone sarcomas are rare tumour entities that arise from the mesenchyme most of which are highly heterogeneous at the cellular, genetic and epigenetic levels. The three main types are osteosarcoma, Ewing sarcoma, and chondrosarcoma. These oncological entities are characterised by high morbidity and mortality and an absence of significant therapeutic improvement in the last four decades. In the field of oncology, in vitro cultures of cancer cells have been extensively used for drug screening unfortunately with limited success. Indeed, despite the massive knowledge acquired from conventional 2D culture methods, scientific community has been challenged by the loss of efficacy of drugs when moved to clinical trials. The recent explosion of new 3D culture methods is paving the way to more relevant in vitro models mimicking the in vivo tumour environment (e.g. bone structure) with biological responses close to the in vivo context. The present review gives a brief overview of the latest advances of the 3D culture methods used for studying primary bone sarcomas.

The Immune Landscape of Osteosarcoma: Implications for Prognosis and Treatment Response

Osteosarcoma (OS) is a high-grade malignant stromal tumor composed of mesenchymal cells producing osteoid and immature bone, with a peak of incidence in the second decade of life. Hence, although relatively rare, the social impact of this neoplasm is particularly relevant. Differently from carcinomas, molecular genetics and the role of the tumor microenvironment in the development and progression of OS are mainly unknown. Indeed, while the tumor microenvironment has been widely studied in other solid tumor types and its contribution to tumor progression has been definitely established, tumor-stroma interaction in OS has been quite neglected for years. Only recently have new insights been gained, also thanks to the availability of new technologies and bioinformatics tools. A better understanding of the cross-talk between the bone microenvironment, including immune and stromal cells, and OS will be key not only for a deeper knowledge of osteosarcoma pathophysiology, but also for the development of novel therapeutic strategies. In this review, we summarize the current knowledge about the tumor microenvironment in OS, mainly focusing on immune cells, discussing their role and implication for disease prognosis and treatment response.

Development of a Novel Immune Infiltration-Related ceRNA Network and Prognostic Model for Sarcoma

Due to the rarity and heterogeneity, it is challenging to explore and develop new therapeutic targets for patients with sarcoma. Recently, immune cell infiltration in the tumor microenvironment (TME) was widely studied, which provided a novel potential approach for cancer treatment. The competing endogenous RNA (ceRNA) regulatory network has been reported as a critical molecular mechanism of tumor development. However, the role of the ceRNA regulatory network in the TME of sarcoma remains unclear. In this study, gene expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) sarcoma datasets, and an immune infiltration-related ceRNA network was constructed, which comprised 14 lncRNAs, 13 miRNAs, and 23 mRNAs. Afterward, we constructed an immune infiltration-related risk score model based on the expression of IRF1, MFNG, hsa-miR-940, and hsa-miR-378a-5p, presenting a promising performance in predicting the prognosis of patients with sarcoma.

A Novel Orthotopic Implantation Technique for Osteosarcoma Produces Spontaneous Metastases and Illustrates Dose-Dependent Efficacy of B7-H3-CAR T Cells

The outcome for metastatic pediatric osteosarcoma (OS) remains poor. Thus, there is an urgent need to develop novel therapies, and immunotherapy with CAR T cells has the potential to meet this challenge. However, there is a lack of preclinical models that mimic salient features of human disease including reliable development of metastatic disease post orthotopic OS cell injection. To overcome this roadblock, and also enable real-time imaging of metastatic disease, we took advantage of LM7 OS cells expressing firefly luciferase (LM7.ffLuc). LM7.ffLuc were implanted in a collagen mesh into the tibia of mice, and mice reliably developed orthotopic tumors and lung metastases as judged by bioluminescence imaging and histopathological analysis. Intratibial implantation also enabled surgical removal by lower leg amputation and monitoring for metastases development post-surgery. We then used this model to evaluate the antitumor activity of CAR T cells targeting B7-H3, an antigen that is expressed in a broad range of solid tumors including OS. B7-H3-CAR T cells had potent antitumor activity in a dose-dependent manner and inhibited the development of pulmonary metastases resulting in a significant survival advantage. In contrast T cells expressing an inactive B7-H3-CAR had no antitumor activity. Using unmodified LM7 cells also enabled us to demonstrate that B7-H3-CAR T cells traffic to orthotopic tumor sites. Hence, we have developed an orthotopic, spontaneously metastasizing OS model. This model may improve our ability not only to predict the safety and efficacy of current and next generation CAR T cell therapies but also other treatment modalities for metastatic OS.

Cancer Stem Cells as a Source of Drug Resistance in Bone Sarcomas

Bone sarcomas are commonly characterized by a high degree of intra-tumor heterogeneity, which in part is due to the presence of subpopulations of tumor cells presenting stem cell properties. Similar to normal stem cells, these cancer stem cells (CSCs) display a drug resistant phenotype and therefore are responsible for relapses and tumor dissemination. Drug resistance in bone sarcomas could be enhanced/modulated during tumor evolution though the acquisition of (epi)-genetic alterations and the adaptation to changing microenvironments, including drug treatments. Here we summarize findings supporting the involvement of pro-stemness signaling in the development of drug resistance in bone sarcomas. This include the activation of well-known pro-stemness pathways (Wnt/β-Cat, NOTCH or JAT/STAT pathways), changes in the metabolic and autophagic activities, the alteration of epigenetic pathways, the upregulation of specific non-coding RNAs and the crosstalk with different microenvironmental factors. This altered signaling is expected to be translated to the clinic in the form of biomarkers of response and new therapies able to overcome drug resistance.

Identification of Epithelial-Mesenchymal Transition-Related Prognostic lncRNAs Biomarkers Associated With Melanoma Microenvironment

Melanoma is the most common cancer of the skin, associated with a worse prognosis and distant metastasis. Epithelial–mesenchymal transition (EMT) is a reversible cellular biological process that plays significant roles in diverse tumor functions, and it is modulated by specific genes and transcription factors. The relevance of EMT-related lncRNAs in melanoma has not been determined. Therefore, RNA expression data and clinical features were collected from the TCGA database (N = 447). Melanoma samples were randomly assigned into the training (315) and testing sets (132). An EMT-related lncRNA signature was constructed via comprehensive analyses of lncRNA expression level and corresponding clinical data. The Kaplan-Meier analysis showed significant differences in overall survival in patients with melanoma in the low and high-risk groups in two sets. Receiver operating characteristic (ROC) curves were used to measure the performance of the model. Cox regression analysis indicated that the risk score was an independent prognostic factor in two sets. Besides, a nomogram was constructed based on the independent variables. Gene Set Enrichment Analysis (GSEA) was applied to evaluate the potential biological functions in the two risk groups. Furthermore, the melanoma microenvironment was evaluated using ESTIMATE and CIBERSORT algorithms in the risk groups. This study indicates that EMT-related lncRNAs can function as potential independent prognostic biomarkers for melanoma survival.

Identification of two immune subtypes in osteosarcoma based on immune gene sets

Osteosarcoma (OS) is a highly aggressive cancer with poor prognosis, which mainly occurs in teenagers. Recent studies have shown that tumor-infiltrating immune cells play an important role in the progression of OS. In the present study, we identified two immune subtypes of OS (referred to as high and low immune cell infiltration subtypes, respectively) based on immune-related gene sets using TARGET and GEO cohort datasets. Elevated immune scores, increased stromal scores, decreased tumor purities, and higher infiltration of CD8 + T cells and M1 macrophages were observed for the high immune cell infiltration subtype. Moreover, the high immune cell infiltration subtype was characterized by high expression of immune checkpoint molecules. Gene set enrichment analysis showed that "B cell receptor signaling pathway" and "T cell receptor signaling pathway" gene sets were enriched in the high immune cell infiltration subtype. In addition, patients in the high immune cell infiltration subtype had better prognosis than patients in the low immune cell infiltration subtype. Furthermore, differentially expressed genes were screened according to the two OS subtypes and a risk model was generated by multivariate Cox regression analysis to predict the prognosis of OS patients. These results in this study showed that OS patients could be divided into two immune subtypes and offered a novel two-gene risk signature to predict the prognosis of patients with OS.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients

Background

Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients.

Methods

We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration.

Results

We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells.

Conclusion

The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

The Role of IGF/IGF-IR-Signaling and Extracellular Matrix Effectors in Bone Sarcoma Pathogenesis

Simple Summary

Bone sarcomas are mesenchymal origin tumors. Bone sarcoma patients show a variable response or do not respond to chemotherapy. Notably, improving efficient chemotherapy approaches, dealing with chemoresistance, and preventing metastasis pose unmet challenges in sarcoma therapy. Insulin-like growth factors 1 and 2 (IGF-1 and -2) and their respective receptors are a multifactorial system that significantly contributes to bone sarcoma pathogenesis. Most clinical trials aiming at the IGF pathway have had limited success. Developing combinatorial strategies to enhance antitumor responses and better classify the patients that could best benefit from IGF-axis targeting therapies is in order. A plausible approach for developing a combinatorial strategy is to focus on the tumor microenvironment (TME) and processes executed therein. Herewith, we will discuss how the interplay between IGF-signaling and the TME constituents affects bone sarcomas’ basal functions and their response to therapy. Potential direct and adjunct therapeutical implications of the extracellular matrix (ECM) effectors will also be summarized.

Abstract

Bone sarcomas, mesenchymal origin tumors, represent a substantial group of varying neoplasms of a distinct entity. Bone sarcoma patients show a limited response or do not respond to chemotherapy. Notably, developing efficient chemotherapy approaches, dealing with chemoresistance, and preventing metastasis pose unmet challenges in sarcoma therapy. Insulin-like growth factors 1 and 2 (IGF-1 and -2) and their respective receptors are a multifactorial system that significantly contributes to bone sarcoma pathogenesis. Whereas failures have been registered in creating novel targeted therapeutics aiming at the IGF pathway, new agent development should continue, evaluating combinatorial strategies for enhancing antitumor responses and better classifying the patients that could best benefit from these therapies. A plausible approach for developing a combinatorial strategy is to focus on the tumor microenvironment (TME) and processes executed therein. Herewith, we will discuss how the interplay between IGF-signaling and the TME constituents affects sarcomas’ basal functions and their response to therapy. This review highlights key studies focusing on IGF signaling in bone sarcomas, specifically studies underscoring novel properties that make this system an attractive therapeutic target and identifies new relationships that may be exploited. Potential direct and adjunct therapeutical implications of the extracellular matrix (ECM) effectors will also be summarized.

Complement C1q (C1qA, C1qB, and C1qC) May Be a Potential Prognostic Factor and an Index of Tumor Microenvironment Remodeling in Osteosarcoma

The tumor microenvironment (TME) has important effects on the tumorigenesis and development of osteosarcoma (OS). However, the dynamic mechanism regulating TME immune and matrix components remains unclear. In this study, we collected quantitative data on the gene expression of 88 OS samples from The Cancer Genome Atlas (TCGA) database and downloaded relevant clinical cases of OS from the TARGET database. The proportions of tumor-infiltrating immune cells (TICs) and the numbers of immune and matrix components were determined by CIBERSORT and ESTIMATE calculation methods. Protein-protein interaction (PPI) network construction and Cox regression analysis were conducted to analyze differentially expressed genes (DEGs). The complement components C1qA, C1qB and C1qC were then determined to be predictive factors through univariate Cox analysis and PPI cross analysis. Further analysis found that the levels of C1qA, C1qB and C1qC expression were positively linked to OS patient survival time and negatively correlated with the clinicopathological feature percent necrosis at definitive surgery. The results of gene set enrichment analysis (GSEA) demonstrated that genes related to immune functions were significantly enriched in the high C1qA, C1qB and C1qC expression groups. Proportion analysis of TICs by CIBERSORT showed that the levels of C1qA, C1qB and C1qC expression were positively related to M1 and M2 macrophages and CD8+ cells and negatively correlated with M0 macrophages. These results further support the influence of the levels of C1qA, C1qB and C1qC expression on the immune activity of the TME. Therefore, C1qA, C1qB and C1qC may be potential indicators of remodeling in the OS TME, which is helpful to predict the prognosis of patients with OS and provide new ideas for immunotherapy for OS.

Data-Driven Mathematical Model of Osteosarcoma

As the immune system has a significant role in tumor progression, in this paper, we develop a data-driven mathematical model to study the interactions between immune cells and the osteosarcoma microenvironment. Osteosarcoma tumors are divided into three clusters based on their relative abundance of immune cells as estimated from their gene expression profiles. We then analyze the tumor progression and effects of the immune system on cancer growth in each cluster. Cluster 3, which had approximately the same number of naive and M2 macrophages, had the slowest tumor growth, and cluster 2, with the highest population of naive macrophages, had the highest cancer population at the steady states. We also found that the fastest growth of cancer occurred when the anti-tumor immune cells and cytokines, including dendritic cells, helper T cells, cytotoxic cells, and IFN-γ, switched from increasing to decreasing, while the dynamics of regulatory T cells switched from decreasing to increasing. Importantly, the most impactful immune parameters on the number of cancer and total cells were the activation and decay rates of the macrophages and regulatory T cells for all clusters. This work presents the first osteosarcoma progression model, which can be later extended to investigate the effectiveness of various osteosarcoma treatments.

Identification of Gene as Predictive Biomarkers for the Occurrence and Recurrence of Osteosarcoma

Purpose

Osteosarcoma is the most common malignant bone cancer affecting adolescents and young adults. This study aimed to screen potential diagnostic and therapeutic markers for osteosarcoma.

Methods

Differential expression analysis between osteosarcoma and control was performed in GSE99671, the differentially expressed genes (DEGs) were subjected to co-expression analysis. Enrichment analysis was employed to identify the biological functions and KEGG signaling pathways of module genes. In addition, a differential analysis was also performed between recurrent and non-recurrent osteosarcoma samples in GSE39055, and enrichment analysis was performed for DEGs. Further, Kaplan–Meier curve analysis was performed on the module genes, and receiver operating characteristic (ROC) curve was drawn. Comparison of the module with the highest correlation to osteosarcoma identified key genes. Cox regression model was utilized to identify the predictive ability of key genes for the prognosis of osteosarcoma.

Results

A total of 13 co-expression modules were identified from 4871 DEGs of GSE99671, module 1 had the highest positive correlation with osteosarcoma. Module genes were mainly enriched in autophagy and macrophage migration functions. A total of 1126 DEGs were obtained from GSE39055, significantly involved in neutrophil mediated immunity. Screening of genes with area under the ROC curve (AUC) values greater than 0.73 in both GSE99671 and GSE39055 identified 5 key genes when compared with genes from module 1. The nomogram results showed that ATF5, CHCHD8, ENOPH1, and LOC286367 might predict 5-year or 8-year survival time of osteosarcoma patients. The Cox model results confirmed that the signals of ATF5, CHCHD8, and LOC286367 were robust, and it may be used in the diagnosis, treatment, and prognosis of osteosarcoma.

Conclusion

We found that ATF5, CHCHD8, and LOC286367 can effectively identify osteosarcoma tumorigenesis and even recurrence status. This is helpful for early diagnosis and treatment, improving the clinical treatment of patients with osteosarcoma.

Long non-coding RNA X-inactive specific transcript promotes osteosarcoma metastasis via modulating microRNA-758/Rab16

Background

As a common malignant bone sarcoma, osteosarcoma (OS) affects the health and lives of many people. Here, we probed the effects of long non-coding RNA (lncRNA) X-inactive specific transcript (XIST) and microRNA-758 (miR-758) on OS metastasis, and examined possible downstream effector.

Methods

Quantitative reverse transcription PCR (qRT-PCR) was performed to detect the expressions of XIST and miR-758 in OS tissues and cells. Cell transfection was carried out to alter the levels of XIST and miR-758 in OS cells, and cell viability, migration, and invasion were assessed. Subsequently, qRT-PCR and a dual-luciferase reporter assay were conducted to analyze the regulatory effects of XIST on miR-758 and miR-758 on Rab16. Finally, we investigated whether Rab16 was the downstream effector of XIST/miR-758 axis.

Results

XIST was highly expressed in OS tissues and cells, but the opposite was seen for miR-758. In OS cells, migration, invasion, and epithelial-mesenchymal transformation (EMT) was promoted by overexpression of XIST and miR-758 inhibitor, but were inhibited by XIST knockdown and miR-758 mimics. XIST regulated miR-758 expression, and miR-758 regulated Rab16 expression in OS cells. Overexpression of Rab16 reversed the effects of miR-758 mimics on OS cell migration and invasion.

Conclusions

XIST contributed to OS cell migration, invasion, and EMT via regulation of miR-758/Rab16.

Expression of Lipid-Metabolism Genes Is Correlated With Immune Microenvironment and Predicts Prognosis in Osteosarcoma

Objectives

Osteosarcoma was the most popular primary malignant tumor in children and adolescent, and the 5-year survival of osteosarcoma patients gained no substantial improvement over the past 35 years. This study aims to explore the role of lipid metabolism in the development and diagnosis of osteosarcoma.

Methods

Clinical information and corresponding RNA data of osteosarcoma patients were downloaded from TRGET and GEO databases. Consensus clustering was performed to identify new molecular subgroups. ESTIMATE, TIMER and ssGSEA analyses were applied to determinate the tumor immune microenvironment (TIME) and immune status of the identified subgroups. Functional analyses including GO, KEGG, GSVA and GSEA analyses were conducted to elucidate the underlying mechanisms. Prognostic risk model was constructed using LASSO algorithm and multivariate Cox regression analysis.

Results

Two molecular subgroups with significantly different survival were identified. Better prognosis was associated with high immune score, low tumor purity, high abundance of immune infiltrating cells and relatively high immune status. GO and KEGG analyses revealed that the DEGs between the two subgroups were mainly enriched in immune- and bone remodeling-associated pathways. GSVA and GSEA analyses indicated that, lipid catabolism downregulation and lipid hydroxylation upregulation may impede the bone remodeling and development of immune system. Risk model based on lipid metabolism related genes (LMRGs) showed potent potential for survival prediction in osteosarcoma. Nomogram integrating risk model and clinical characteristics could predict the prognosis of osteosarcoma patients accurately.

Conclusion

Expression of lipid-metabolism genes is correlated with immune microenvironment of osteosarcoma patients and could be applied to predict the prognosis of in osteosarcoma accurately.

3D Cancer Models: The Need for a Complex Stroma, Compartmentalization and Stiffness

The use of tissue-engineered 3D models of cancer has grown in popularity with recent advances in the field of cancer research. 3D models are inherently more biomimetic compared to 2D cell monolayers cultured on tissue-culture plastic. Nevertheless 3D models still lack the cellular and matrix complexity of native tissues. This review explores different 3D models currently used, outlining their benefits and limitations. Specifically, this review focuses on stiffness and collagen density, compartmentalization, tumor-stroma cell population and extracellular matrix composition. Furthermore, this review explores the methods utilized in different models to directly measure cancer invasion and growth. Of the models evaluated, with PDX and in vivo as a relative "gold standard", tumoroids were deemed as comparable 3D cancer models with a high degree of biomimicry, in terms of stiffness, collagen density and the ability to compartmentalize the tumor and stroma. Future 3D models for different cancer types are proposed in order to improve the biomimicry of cancer models used for studying disease progression.