Single-Cell Transcriptomics Reveals the Complexity of the Tumor Microenvironment of Treatment-Naive Osteosarcoma

Biomimetic Targeted Co-Delivery System Engineered from Genomic Insights for Precision Treatment of Osteosarcoma

The high heterogeneity and severe side effects of chemotherapy are major factors contributing to the failure of osteosarcoma treatment. Herein, a comprehensive genomic analysis is conducted, and identified two prominent characteristics of osteosarcoma: significant cyclin-dependent kinases 4 (CDK4) amplification and homologous recombination repair deficiency. Based on these findings, a co-delivery system loaded with CDK4/6 inhibitors and poly ADP-ribose polymerase (PARP) inhibitors is designed. By employing metal-organic frameworks (MOFs) as carriers, issue of drug insolubility is effectively addressed, while also enabling controlled release in response to the tumor microenvironment. To enhance targeting capability and biocompatibility, the MOFs are further coated with a bio-membrane targeting B7H3. This targeted biomimetic co-delivery system possesses several key features: 1) it can precisely target osteosarcoma with high B7H3 expression; 2) the combination of CDK4/6 inhibitors and PARP inhibitors exhibits synergistic effects, significantly impairing tumor's DNA repair capacity; and 3) the system has the potential for combination with photodynamic therapy, amplifying DNA repair defects to maximize tumor cell eradication. Furthermore, it is observed that this co-delivery system can activate immune microenvironment, increasing CD8+ T cell infiltration and converting osteosarcoma from an immune-cold to an immune-hot tumor. In summary, the co-delivery system is an effective therapeutic strategy and holds promise as a novel approach for osteosarcoma treatment.

Single-Cell Spatial-Temporal Analysis of ZNF451 in Mediating Drug Resistance and CD8+ T Cell Dysfunction

Cisplatin is widely used to treat osteosarcoma, but recurrent cases often develop resistance, allowing the disease to progress and complicating clinical management. This study aimed to elucidate the immune microenvironment of osteosarcoma, providing insights into the mechanisms of recurrence and identifying potential therapeutic strategies. By analyzing multiple single-cell and bulk RNA-sequencing datasets, we discovered that the SUMOylation-related gene ZNF451 promotes osteosarcoma recurrence and alters its immune microenvironment. ZNF451 was found to importantly enhance the growth, migration, and invasion of resistant cells while also reducing their sensitivity to cisplatin and lowering their apoptosis rate. Moreover, our data indicated that ZNF451 plays a crucial role in bone resorption and epithelial-mesenchymal transition. ZNF451 also regulates CD8+ T cell function, leading to their exhaustion and transition to the CD8T.EXH state. Additionally, β-cryptoxanthin has been identified as a potential therapeutic agent that inhibits osteosarcoma progression by targeting ZNF451. In summary, these findings highlight the critical role of ZNF451 in promoting osteosarcoma progression and underscore its potential as a therapeutic target and biomarker for osteosarcoma.

Proteomic and transcriptomic analyses identify apo-transcobalamin-II as a biomarker of overall survival in osteosarcoma

Background

The large-scale proteomic platform known as the SomaScan® assay is capable of simultaneously measuring thousands of proteins in patient specimens through next-generation aptamer-based multiplexed technology. While previous studies have utilized patient peripheral blood to suggest serum biomarkers of prognostic or diagnostic value in osteosarcoma (OSA), the most common primary pediatric bone cancer, they have ultimately been limited in the robustness of their analyses. We propose utilizing this aptamer-based technology to describe the systemic proteomic milieu in patients diagnosed with this disease.

Methods

To determine novel biomarkers associated with overall survival in OSA, we deployed the SomaLogic SomaScan® 7k assay to investigate the plasma proteomic profile of naive primary, recurrent, and metastatic OSA patients. Following identification of differentially expressed proteins (DEPs) between 2-year deceased and survivor cohorts, publicly available databases including Survival Genie, TIGER, and KM Plotter Immunotherapy, among others, were utilized to investigate the significance of our proteomic findings.

Results

Apo-transcobalamin-II (APO-TCN2) was identified as the most DEP between 2-year deceased and survivor cohorts (Log2 fold change = 6.8, P-value = 0.0017). Survival analysis using the Survival Genie web-based platform indicated that increased intratumoral TCN2 expression was associated with better overall survival in both OSA (TARGET-OS) and sarcoma (TCGA-SARC) datasets. Cell-cell communication analysis using the TIGER database suggested that TCN2+ Myeloid cells likely interact with marginal zone and immunoglobin-producing B lymphocytes expressing the TCN2 receptor (CD320) to promote their proliferation and survival in both non-small cell lung cancer and melanoma tumors. Analysis of publicly available OSA scRNA-sequencing datasets identified similar populations in naive primary tumors. Furthermore, circulating APO-TCN2 levels in OSA were then associated with a plasma proteomic profile likely necessary for robust B lymphocyte proliferation, infiltration, and formation of intratumoral tertiary lymphoid structures for improved anti-tumor immunity.

Conclusions

Overall, APO-TCN2, a circulatory protein previously described in various lymphoproliferative disorders, was associated with 2-year survival status in patients diagnosed with OSA. The relevance of this protein and apparent immunological function (anti-tumor B lymphocyte responses) was suggested using publicly available solid tumor RNA-sequencing datasets. Further studies characterizing the biological function of APO-TCN2 and its relevance in these diseases is warranted.

Spatial multiplexed immunofluorescence analysis reveals coordinated cellular networks associated with overall survival in metastatic osteosarcoma

Patients diagnosed with advanced osteosarcoma, often in the form of lung metastases, have abysmal five-year overall survival rates. The complexity of the osteosarcoma immune tumor microenvironment has been implicated in clinical trial failures of various immunotherapies. The purpose of this exploratory study was to spatially characterize the immune tumor microenvironment of metastatic osteosarcoma lung specimens. Knowledge of the coordinating cellular networks within these tissues could then lead to improved outcomes when utilizing immunotherapy for treatment of this disease. Importantly, various cell types, interactions, and cellular neighborhoods were associated with five-year survival status. Of note, increases in cellular interactions between T lymphocytes, positive for programmed cell death protein 1, and myeloid-derived suppressor cells were observed in the 5-year deceased cohort. Additionally, cellular neighborhood analysis identified an Immune-Cold Parenchyma cellular neighborhood, also associated with worse 5-year survival. Finally, the Osteosarcoma Spatial Score, which approximates effector immune activity in the immune tumor microenvironment through the spatial proximity of immune and tumor cells, was increased within 5-year survivors, suggesting improved effector signaling in this patient cohort. Ultimately, these data represent a robust spatial multiplexed immunofluorescence analysis of the metastatic osteosarcoma immune tumor microenvironment. Various communication networks, and their association with survival, were described. In the future, identification of these networks may suggest the use of specific, combinatory immunotherapeutic strategies for improved anti-tumor immune responses and outcomes in osteosarcoma.

Unlocking the tumor-immune microenvironment in osteosarcoma: insights into the immune landscape and mechanisms

Osteosarcoma has a unique tumor microenvironment (TME), which is characterized as a complex microenvironment comprising of bone cells, immune cells, stromal cells, and heterogeneous vascular structures. These elements are intricately embedded in a mineralized extracellular matrix, setting it apart from other primary TMEs. In a state of normal physiological function, these cell types collaborate in a coordinated manner to maintain the homeostasis of the bone and hematopoietic systems. However, in the pathological condition, i.e., neoplastic malignancies, the tumor-immune microenvironment (TIME) has been shown to promote cancer cells proliferation, migration, apoptosis and drug resistance, as well as immune escape. The intricate and dynamic system of the TIME in osteosarcoma involves crucial roles played by various infiltrating cells, the complement system, and exosomes. This complexity is closely associated with tumor cells evading immune surveillance, experiencing uncontrolled proliferation, and facilitating metastasis. In this review, we elucidate the intricate interplay between diverse cell populations in the osteosarcoma TIME, each contributing uniquely to tumor progression. From chondroblastic and osteoblastic osteosarcoma cells to osteoclasts, stromal cells, and various myeloid and lymphoid cell subsets, the comprehensive single-cell analysis provides a detailed roadmap of the complex osteosarcoma ecosystem. Furthermore, we summarize the mutations, epigenetic mechanisms, and extracellular vesicles that dictate the immunologic landscape and modulate the TIME of osteosarcoma. The perspectives of the clinical implementation of immunotherapy and therapeutic approaches for targeting immune cells are also intensively discussed.

Single-cell RNA sequencing reveals the communications between tumor microenvironment components and tumor metastasis in osteosarcoma

Introduction

Osteosarcoma is a common type of bone cancer characterized by a poor prognosis due to its metastatic nature. The tumor microenvironment (TME) plays a critical role in tumor metastasis and therapy response. Therefore, our study aims to explore the metastatic mechanism of osteosarcoma, potentially opening new avenues for cancer treatment.

Methods

In this study, we collected data from the GSE152048, GSE14359, and GSE49003 datasets. Differentially expressed genes (DEGs) were identified in osteosarcoma cases with primary and metastatic features using R software and the limma package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate metastasis-related genes. A protein-protein interaction (PPI) network was established using the STRING database to further analyze these metastasis-associated genes. The abundances of different cell types with a mixed cell population were estimated using the CIBERSORT approach. The scRNA-seq data were analyzed by the Seurat package in R software, and intercellular communications were elucidated using the CellChat R package.

Results

In this study, 92 DEGs related to metastasis were identified, including 41 upregulated and 51 downregulated genes in both the GSE14359 and GSE49003 datasets. Metastasis-associated pathways were identified, including those involving the cyclin-dependent protein kinase holoenzyme complex, transferase complex, transferring phosphorus-containing groups, SCF ubiquitin ligase complex, and the serine/threonine protein kinase complex. KEGG and PPI network analyses revealed 15 hub genes, including Skp2, KIF20A, CCNF, TROAP, PHB, CKS1B, MCM3, CCNA2, TRIP13, CENPM, Hsp90AB1, JUN, CKS2, TK1, and KIF4A. Skp2 has been known as an E3 ubiquitin ligase involved in osteosarcoma progression. The proportion of CD8+ T cells was found to be higher in metastatic osteosarcoma tissues, and high expression of PHB was associated with a favorable prognosis in osteosarcoma patients. Additionally, 23 cell clusters were classified into eight cell types, including chondrocytes, MSC, T cells, monocytes, tissue stem cells, neurons, endothelial cells, and macrophages. The 15 hub genes were expressed across various cell types, and interactions between different cell types were observed.

Conclusion

Our study reveals the intricate communication between tumor microenvironment components and tumor metastasis in osteosarcoma.

Unraveling the role of bisphenol A in osteosarcoma biology: insights into prognosis and immune microenvironment modulation

BACKGROUND

Bisphenol A (BPA) is a common environmental pollutant, and its specific mechanisms in cancer development and its impact on the tumor immune microenvironment are not yet fully understood.

METHODS

Transcriptome data from osteosarcoma (OS) patients were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. BPA-related genes were identified through the Comparative Toxicogenomics Database (CTD), yielding 177 genes. Differentially expressed genes were analyzed using the GSE162454 dataset from the Tumor Immune Single Cell Hub 2 (TISCH2). We constructed the prognostic model using univariate Cox regression and LASSO analysis. The model was validated using the GSE16091 dataset. GO, KEGG, and GSEA analyses were performed to investigate the mechanisms of BPA-related genes.

RESULTS

A total of 15 BPA-related genes were identified as differentially expressed in OS. Univariate Cox regression and LASSO analysis identified four key prognostic genes (FOLR1, MYC, ESRRA, VEGFA). The prognostic model exhibited strong predictive performance with area under the curve (AUC) values of 0.89, 0.6, and 0.79 for predicting 1-, 2-, and 3-year survival, respectively. External validation using the GSE16091 dataset confirmed the model's high accuracy with AUC values exceeding 0.88. Our results indicated that the prognosis of the high-risk population is generally poorer, which may be associated with alterations in the tumor immune microenvironment. In the high-risk group, immune cells showed predominantly low expression levels, while immune checkpoint genes were significantly overexpressed, along with markedly elevated tumor purity. These findings revealed a correlation between upregulation of BPA-related genes and formation of an immunosuppressive microenvironment, leading to unfavorable patient outcomes.

CONCLUSION

Our study highlighted the significant association of BPA with OS biology, particularly in its potential role in modulating the tumor immune microenvironment. We offered a fresh insight into the influence of BPA on cancer development, thus providing valuable insights for future clinical interventions and treatment strategies.

Spatiotemporal evolutionary process of osteosarcoma immune microenvironment remodeling and C1QBP-driven drug resistance deciphered through single-cell multi-dimensional analysis

The tumor immune microenvironment has manifested a crucial correlation with tumor occurrence, development, recurrence, and metastasis. To explore the mechanisms intrinsic to osteosarcoma (OS) initiation and progression, this study synthesizes multiple single-cell RNA sequencing data sets, constructing a comprehensive landscape of the OS microenvironment. Integrating single-cell RNA sequencing with bulk RNA sequencing data has enabled the identification of a significant correlation between heightened expression of the fatty acid metabolism-associated gene (C1QBP) and patient survival in OS. C1QBP not only amplifies the proliferation, migration, invasion, and anti-apoptotic properties of OS but also instigates cisplatin resistance. Subsequent investigations suggest that C1QBP potentially promotes macrophage polarization from monocytes/macrophages toward M2 and M3 phenotypes. Consequently, C1QBP may emerge as a novel target for modulating OS progression and resistance therapy.

A single-cell and spatially resolved atlas of human osteosarcomas

Osteosarcomas are intricate cellular ecosystems, where heterotypic interactions significantly influence disease progression and therapeutic outcomes. Despite their importance, a detailed understanding of their cellular composition and organizational structure remains elusive. In this study, we provide a comprehensive single-cell and spatially resolved transcriptomics analysis of human osteosarcomas. We construct a cellular meta-map to dissect spatial transcriptomic data, unveiling a detailed atlas of osteosarcoma compositional subgroups. We meticulously characterize the unique gene signatures and functional states of each subgroup and investigate the impact of chemotherapy on these cellular subpopulations. Additionally, our spatial transcriptomics analysis identifies a distinct spatial niche, located at the forefront of tumor necrotic zones, potentially associated with chemotherapy resistance. We also delve into the crosstalk between different cellular subgroups. This study furnishes a comprehensive transcriptional atlas of osteosarcoma's cellular architecture, enriching our comprehension of its complexity and laying the groundwork for more targeted therapeutic approaches.

Single-cell transcriptomic insights into chemotherapy-induced remodeling of the osteosarcoma tumor microenvironment

PURPOSE

Neoadjuvant chemotherapy serves as an effective strategy for treating osteosarcoma (OS) not only by targeting cancerous cells but also by influencing the tumor's immune and stromal elements. Gaining insights into how chemotherapy reshapes the tumor's local environment is crucial for advancing OS treatment protocols.

METHODS

Using single-cell RNA sequencing, this study analyzed tumor samples from patients with advanced osteosarcoma collected both before and after chemotherapy.

RESULTS

The results revealed that chemotherapy caused the remaining OS cells to express higher levels of genes associated with stemness. Additionally, this process enhances the presence of cancer-associated fibroblasts, increasing their ability to modify the extracellular matrix (ECM). Chemotherapy also increases the number of endothelial cells, albeit with compromised differentiation capabilities. Importantly, the treatment reduced the immune cell population, including myeloid and T/NK cells, particularly impacting the subpopulations with tumor-fighting capabilities.

CONCLUSION

These findings highlight the complex reaction of the tumor environment to chemotherapy, providing valuable insights into how chemotherapy influences OS cells and the tumor microenvironment (TME). This knowledge is essential for understanding OS resistance mechanisms to treatments, potentially guiding the development of novel therapies for managing advanced OS.

Exploring the Role of Neutrophil-Related Genes in Osteosarcoma via an Integrative Analysis of Single-Cell and Bulk Transcriptome

BACKGROUND

The involvement of neutrophil-related genes (NRGs) in patients with osteosarcoma (OS) has not been adequately explored. In this study, we aimed to examine the association between NRGs and the prognosis as well as the tumor microenvironment of OS.

METHODS

The OS data were obtained from the TARGET-OS and GEO database. Initially, we extracted NRGs by intersecting 538 NRGs from single-cell RNA sequencing (scRNA-seq) data between aneuploid and diploid groups, as well as 161 up-regulated differentially expressed genes (DEGs) from the TARGET-OS datasets. Subsequently, we conducted Least Absolute Shrinkage and Selection Operator (Lasso) analyses to identify the hub genes for constructing the NRG-score and NRG-signature. To assess the prognostic value of the NRG signatures in OS, we performed Kaplan-Meier analysis and generated time-dependent receiver operating characteristic (ROC) curves. Gene enrichment analysis (GSEA) and gene set variation analysis (GSVA) were utilized to ascertain the presence of tumor immune microenvironments (TIMEs) and immunomodulators (IMs). Additionally, the KEGG neutrophil signaling pathway was evaluated using ssGSEA. Subsequently, PCR and IHC were conducted to validate the expression of hub genes and transcription factors (TFs) in K7M2-induced OS mice.

RESULTS

FCER1G and C3AR1 have been identified as prognostic biomarkers for overall survival. The findings indicate a significantly improved prognosis for OS patients. The effectiveness and precision of the NRG signature in prognosticating OS patients were validated through survival ROC curves and an external validation dataset. The results clearly demonstrate that patients with elevated NRG scores exhibit decreased levels of immunomodulators, stromal score, immune score, ESTIMATE score, and infiltrating immune cell populations. Furthermore, our findings substantiate the potential role of SPI1 as a transcription factor in the regulation of the two central genes involved in osteosarcoma development. Moreover, our analysis unveiled a significant correlation and activation of the KEGG neutrophil signaling pathway with FCER1G and C3AR1. Notably, PCR and IHC demonstrated a significantly higher expression of C3AR1, FCER1G, and SPI1 in Balb/c mice induced with K7M2.

CONCLUSIONS

Our research emphasizes the significant contribution of neutrophils within the TIME of osteosarcoma. The newly developed NRG signature could serve as a good instrument for evaluating the prognosis and therapeutic approach for OS.

TrkA + sensory neurons regulate osteosarcoma proliferation and vascularization to promote disease progression

Bone pain is a presenting feature of bone cancers such as osteosarcoma (OS), relayed by skeletal-innervating peripheral afferent neurons. Potential functions of tumor-associated sensory neurons in bone cancers beyond pain sensation are unknown. To uncover neural regulatory functions, a chemical-genetic approach in mice with a knock-in allele for TrkA was used to functionally perturb sensory nerve innervation during OS growth and disease progression. TrkA inhibition in transgenic mice led to significant reductions in sarcoma-associated sensory innervation and vascularization, tumor growth and metastasis, and prolonged overall survival. Single-cell transcriptomics revealed that sarcoma denervation was associated with phenotypic alterations in both OS tumor cells and cells within the tumor microenvironment, and with reduced calcitonin gene-related peptide (CGRP) and vascular endothelial growth factor (VEGF) signaling. Multimodal and multi-omics analyses of human OS bone samples and human dorsal root ganglia neurons further implicated peripheral innervation and neurotrophin signaling in OS tumor biology. In order to curb tumor-associated axonal ingrowth, we next leveraged FDA-approved bupivacaine liposomes leading to significant reductions in sarcoma growth, vascularity, as well as alleviation of pain. In sum, TrkA-expressing peripheral neurons positively regulate key aspects of OS progression and sensory neural inhibition appears to disrupt calcitonin receptor signaling (CALCR) and VEGF signaling within the sarcoma microenvironment leading to significantly reduced tumor growth and improved survival. These data suggest that interventions to prevent pathological innervation of osteosarcoma represent a novel adjunctive therapy to improve clinical outcomes and survival.

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

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

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

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

Immunotherapy in Sarcoma: Current Data and Promising Strategies

Traditionally sarcomas have been considered immunologically quiet tumours, with low tumour mutational burden (TMB) and an immunosuppressive tumour microenvironment (TME), consisting of decreased T-cell infiltration and elevated levels of H1F1α, macrophages and neutrophils.1,2 However, research has shown that a subset of sarcomas are immunologically 'hot' with either high TMB, PDL-1 expression, CD8+ T cells or presence of tertiary lymphoid structures (TLS) demonstrating sensitivity to immunotherapy.3,4 Here, we review the current evidence for immunotherapy use in bone sarcomas (BS) and soft tissue sarcomas (STS), with immune checkpoint inhibitors (ICI) and adoptive cellular therapies including engineered T-cell therapies, chimeric antigen receptor (CAR) T-cell therapies, tumour infiltrating lymphocytes (TILs) and cancer vaccines and biomarkers of response.

Advancing skeletal health and disease research with single-cell RNA sequencing

Orthopedic conditions have emerged as global health concerns, impacting approximately 1.7 billion individuals worldwide. However, the limited understanding of the underlying pathological processes at the cellular and molecular level has hindered the development of comprehensive treatment options for these disorders. The advent of single-cell RNA sequencing (scRNA-seq) technology has revolutionized biomedical research by enabling detailed examination of cellular and molecular diversity. Nevertheless, investigating mechanisms at the single-cell level in highly mineralized skeletal tissue poses technical challenges. In this comprehensive review, we present a streamlined approach to obtaining high-quality single cells from skeletal tissue and provide an overview of existing scRNA-seq technologies employed in skeletal studies along with practical bioinformatic analysis pipelines. By utilizing these methodologies, crucial insights into the developmental dynamics, maintenance of homeostasis, and pathological processes involved in spine, joint, bone, muscle, and tendon disorders have been uncovered. Specifically focusing on the joint diseases of degenerative disc disease, osteoarthritis, and rheumatoid arthritis using scRNA-seq has provided novel insights and a more nuanced comprehension. These findings have paved the way for discovering novel therapeutic targets that offer potential benefits to patients suffering from diverse skeletal disorders.

Single-cell and spatial transcriptomics reveal metastasis mechanism and microenvironment remodeling of lymph node in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common primary malignant bone tumor and is highly prone to metastasis. OS can metastasize to the lymph node (LN) through the lymphatics, and the metastasis of tumor cells reestablishes the immune landscape of the LN, which is conducive to the growth of tumor cells. However, the mechanism of LN metastasis of osteosarcoma and remodeling of the metastatic lymph node (MLN) microenvironment is not clear.

METHODS

Single-cell RNA sequencing of 18 samples from paracancerous, primary tumor, and lymph nodes was performed. Then, new signaling axes closely related to metastasis were identified using bioinformatics, in vitro experiments, and immunohistochemistry. The mechanism of remodeling of the LN microenvironment in tumor cells was investigated by integrating single-cell and spatial transcriptomics.

RESULTS

From 18 single-cell sequencing samples, we obtained 117,964 cells. The pseudotime analysis revealed that osteoblast(OB) cells may follow a differentiation path from paracancerous tissue (PC) → primary tumor (PT) → MLN or from PC → PT, during the process of LN metastasis. Next, in combination of bioinformatics, in vitro and in vivo experiments, and immunohistochemistry, we determined that ETS2/IBSP, a new signal axis, might promote LN metastasis. Finally, single-cell and spatial dissection uncovered that OS cells could reshape the microenvironment of LN by interacting with various cell components, such as myeloid, cancer-associated fibroblasts (CAFs), and NK/T cells.

CONCLUSIONS

Collectively, our research revealed a new molecular mechanism of LN metastasis and clarified how OS cells influenced the LN microenvironment, which might provide new insight for blocking LN metastasis.

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

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

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

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

Role of proteoglycan synthesis genes in osteosarcoma stem cells

Osteosarcoma stem cells (OSCs) contribute to the pathogenesis of osteosarcoma (OS), which is the most common malignant primary bone tumor. The significance and underlying mechanisms of action of proteoglycans (PGs) and glycosaminoglycans (GAGs) in OSC phenotypes and OS malignancy are largely unknown. This study aimed to investigate the role of PG/GAG biosynthesis and the corresponding candidate genes in OSCs and poor clinical outcomes in OS using scRNA-seq and bulk RNA-seq datasets of clinical OS specimens, accompanied by biological validation by in vitro genetic and pharmacological analyses. The expression of β-1,3-glucuronyltransferase 3 (B3GAT3), one of the genes responsible for the biosynthesis of the common core tetrasaccharide linker region of PGs, was significantly upregulated in both OSC populations and OS tissues and was associated with poor survival in patients with OS with high stem cell properties. Moreover, the genetic inactivation of B3GAT3 by RNA interference and pharmacological inhibition of PG biosynthesis abrogated the self-renewal potential of OSCs. Collectively, these findings suggest a pivotal role for B3GAT3 and PG/GAG biosynthesis in the regulation of OSC phenotypes and OS malignancy, thereby providing a potential target for OSC-directed therapy.

Single-Cell RNA Sequencing Pro-angiogenic Macrophage Profiles Reveal Novel Prognostic Biomarkers and Therapeutic Targets for Osteosarcoma

Osteosarcoma (OS) is a malignant bone tumor that most commonly occurs in children and adolescents. OS patients have a poor prognosis, and 5-year survival rates have rarely improved significantly over the past few decades. OS prognosis may be related to the infiltration of tumor-associated macrophages (TAMs). However, the role of proangiogenic macrophages, a subtype of TAMs, in OS prognosis has not been reported. In this study, seven subtypes of TAMs were identified from single-cell RNA sequencing (scRNA-seq) data that we propose defining as proangiogenic TAMs (Angio-TAMs), interferon-primed TAMs (IFN-TAMs), inflammatory cytokine-enriched TAMs (Inflam-TAMs), immune regulatory TAMs (Reg-TAMs), lipid-associated TAMs (LA-TAMs), and resident-tissue macrophages like TAMs (RTM-TAMs) (containing two subcellular types). In the survival analysis of each macrophage subtype, it was found that patients with Angio-TAMs had the most significant difference in survival. Eight genes associated with Angio-TAMs were obtained by differential expression analysis, and these genes were built into a prognostic model using the LASSO algorithm. Clinical OS case samples were categorized into high-risk and low-risk subgroups using median risk scores. In comparison to the low-risk subgroup, the survival time of the high-risk subgroup was much shorter. Additional studies on immune cell infiltration and immune checkpoint molecule expression in the two risk subgroups were carried out. In immunotherapy response prediction, the Angio-TAM-associated gene risk signature was found to be negatively correlated with immune checkpoint responses. In addition, the associated enriched GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were mainly involved in the malignant progression of tumors. As suggested by these findings, the Angio-TAM gene risk signature may be an underlying prognostic biomarker and novel therapeutic target for OS patients.Kindly check and confirm whether the ESM file is correctly identifiedWe have checked this file and confirmed that it can be correctly identified.

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Objective

Osteosarcoma (OS) represents a prevalent primary bone neoplasm predominantly affecting the pediatric and adolescent populations, presenting a considerable challenge to human health. The objective of this investigation is to develop a prognostic model centered on anoikis-related genes (ARGs), with the aim of accurately forecasting the survival outcomes of individuals diagnosed with OS and offering insights into modulating the immune microenvironment.

Methods

The study's training cohort comprised 86 OS patients sourced from The Cancer Genome Atlas database, while the validation cohort consisted of 53 OS patients extracted from the Gene Expression Omnibus database. Differential analysis utilized the GSE33382 dataset, encompassing three normal samples and 84 OS samples. Subsequently, the study executed gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses. Identification of differentially expressed ARGs associated with OS prognosis was carried out through univariate COX regression analysis, followed by LASSO regression analysis to mitigate overfitting risks and construct a robust prognostic model. Model accuracy was assessed via risk curves, survival curves, receiver operating characteristic curves, independent prognostic analysis, principal component analysis, and t-distributed stochastic neighbor embedding (t-SNE) analysis. Additionally, a nomogram model was devised, exhibiting promising potential in predicting OS patient prognosis. Further investigations incorporated gene set enrichment analysis to delineate active pathways in high- and low-risk groups. Furthermore, the impact of the risk prognostic model on the immune microenvironment of OS was evaluated through tumor microenvironment analysis, single-sample gene set enrichment analysis (ssGSEA), and immune infiltration cell correlation analysis. Drug sensitivity analysis was conducted to identify potentially effective drugs for OS treatment. Ultimately, the verification of the implicated ARGs in the model construction was conducted through the utilization of real-time quantitative polymerase chain reaction (RT-qPCR).

Results

The ARGs risk prognostic model was developed, comprising seven high-risk ARGs (CBS, MYC, MMP3, CD36, SCD, COL13A1, and HSP90B1) and four low-risk ARGs (VASH1, TNFRSF1A, PIP5K1C, and CTNNBIP1). This prognostic model demonstrates a robust capability in predicting overall survival among patients. Analysis of immune correlations revealed that the high-risk group exhibited lower immune scores compared to the low-risk group within our prognostic model. Specifically, CD8+ T cells, neutrophils, and tumor-infiltrating lymphocytes were notably downregulated in the high-risk group, alongside significant downregulation of checkpoint and T cell coinhibition mechanisms. Additionally, three immune checkpoint-related genes (CD200R1, HAVCR2, and LAIR1) displayed significant differences between the high- and low-risk groups. The utilization of a nomogram model demonstrated significant efficacy in prognosticating the outcomes of OS patients. Furthermore, tumor metastasis emerged as an independent prognostic factor, suggesting a potential association between ARGs and OS metastasis. Notably, our study identified eight drugs-Bortezomib, Midostaurin, CHIR.99021, JNK.Inhibitor.VIII, Lenalidomide, Sunitinib, GDC0941, and GW.441756-as exhibiting sensitivity toward OS. The RT-qPCR findings indicate diminished expression levels of CBS, MYC, MMP3, and PIP5K1C within the context of OS. Conversely, elevated expression levels were observed for CD36, SCD, COL13A1, HSP90B1, VASH1, and CTNNBIP1 in OS.

Conclusion

The outcomes of this investigation present an opportunity to predict the survival outcomes among individuals diagnosed with OS. Furthermore, these findings hold promise for progressing research endeavors focused on prognostic evaluation and therapeutic interventions pertaining to this particular ailment.

Long noncoding RNA Malat1 protects against osteoporosis and bone metastasis

MALAT1, one of the few highly conserved nuclear long noncoding RNAs (lncRNAs), is abundantly expressed in normal tissues. Previously, targeted inactivation and genetic rescue experiments identified MALAT1 as a suppressor of breast cancer lung metastasis. On the other hand, Malat1-knockout mice are viable and develop normally. On a quest to discover the fundamental roles of MALAT1 in physiological and pathological processes, we find that this lncRNA is downregulated during osteoclastogenesis in humans and mice. Remarkably, Malat1 deficiency in mice promotes osteoporosis and bone metastasis of melanoma and mammary tumor cells, which can be rescued by genetic add-back of Malat1. Mechanistically, Malat1 binds to Tead3 protein, a macrophage-osteoclast-specific Tead family member, blocking Tead3 from binding and activating Nfatc1, a master regulator of osteoclastogenesis, which results in the inhibition of Nfatc1-mediated gene transcription and osteoclast differentiation. Notably, single-cell transcriptome analysis of clinical bone samples reveals that reduced MALAT1 expression in pre-osteoclasts and osteoclasts is associated with osteoporosis and metastatic bone lesions. Altogether, these findings identify Malat1 as a lncRNA that protects against osteoporosis and bone metastasis.

FGF23 Expression Is a Promising Immunohistochemical Diagnostic Marker for Undifferentiated Pleomorphic Sarcoma of Bone (UPSb)

Background: Undifferentiated pleomorphic sarcoma of bone (UPSb) is a rare primary bone sarcoma that lacks a specific line of differentiation. Distinguishing between UPSb and other malignant bone sarcomas, including dedifferentiated chondrosarcoma and osteosarcoma, is challenging due to their overlapping features. We have previously identified that UPSb tumours have elevated mRNA levels of Fibroblast Growth Factor 23 (FGF23) transcripts compared to other sarcomas including osteosarcoma. In the present study, we evaluated the specificity and practicality of FGF23 immunoreactivity as a specific diagnostic tool to differentiate UPSb tumours from osteosarcomas and dedifferentiated chondrosarcomas. Methods: A total of 10 UPSb, 10 osteosarcoma, and 10 dedifferentiated chondrosarcoma cases (all high-grade), were retrieved and immunohistochemistry for FGF23 was performed. Results: FGF23 protein was expressed at high levels in 80-90% of undifferentiated pleomorphic sarcoma of the bone cases, whereas it was expressed at significantly lower levels in dedifferentiated chondrosarcoma and osteosarcoma cases. A semiquantitative analysis, considering the intensity of immunoreactivity, confirmed significantly elevated FGF23 expression levels in UPSb tissues compared to those observed in osteosarcoma and dedifferentiated chondrosarcoma tissues. Conclusions: The results we present here suggest that FGF23 immunohistochemistry may be a useful tool to aid in differentiating UPSb from morphologically similar malignant bone sarcomas, especially in situations where sampling is restricted and there is limited clinical information available.

Identifying squalene epoxidase as a metabolic vulnerability in high-risk osteosarcoma using an artificial intelligence-derived prognostic index

BACKGROUND

Osteosarcoma (OSA) presents a clinical challenge and has a low 5-year survival rate. Currently, the lack of advanced stratification models makes personalized therapy difficult. This study aims to identify novel biomarkers to stratify high-risk OSA patients and guide treatment.

METHODS

We combined 10 machine-learning algorithms into 101 combinations, from which the optimal model was established for predicting overall survival based on transcriptomic profiles for 254 samples. Alterations in transcriptomic, genomic and epigenomic landscapes were assessed to elucidate mechanisms driving poor prognosis. Single-cell RNA sequencing (scRNA-seq) unveiled genes overexpressed in OSA cells as potential therapeutic targets, one of which was validated via tissue staining, knockdown and pharmacological inhibition. We characterized changes in multiple phenotypes, including proliferation, colony formation, migration, invasion, apoptosis, chemosensitivity and in vivo tumourigenicity. RNA-seq and Western blotting elucidated the impact of squalene epoxidase (SQLE) suppression on signalling pathways.

RESULTS

The artificial intelligence-derived prognostic index (AIDPI), generated by our model, was an independent prognostic biomarker, outperforming clinicopathological factors and previously published signatures. Incorporating the AIDPI with clinical factors into a nomogram improved predictive accuracy. For user convenience, both the model and nomogram are accessible online. Patients in the high-AIDPI group exhibited chemoresistance, coupled with overexpression of MYC and SQLE, increased mTORC1 signalling, disrupted PI3K-Akt signalling, and diminished immune infiltration. ScRNA-seq revealed high expression of MYC and SQLE in OSA cells. Elevated SQLE expression correlated with chemoresistance and worse outcomes in OSA patients. Therapeutically, silencing SQLE suppressed OSA malignancy and enhanced chemosensitivity, mediated by cholesterol depletion and suppression of the FAK/PI3K/Akt/mTOR pathway. Furthermore, the SQLE-specific inhibitor FR194738 demonstrated anti-OSA effects in vivo and exhibited synergistic effects with chemotherapeutic agents.

CONCLUSIONS

AIDPI is a robust biomarker for identifying the high-risk subset of OSA patients. The SQLE protein emerges as a metabolic vulnerability in these patients, providing a target with translational potential.

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.

Single-cell RNA sequencing reveals the immune microenvironment landscape of osteosarcoma before and after chemotherapy

Chemotherapy, a primary treatment for osteosarcoma (OS), has limited knowledge regarding its impact on tumor immune microenvironment (TIME). Here, tissues from 6 chemotherapy-naive OS patients underwent single-cell RNA sequencing (scRNA-seq) and were analyzed alongside public dataset (GSE152048) containing 7 post-chemotherapy OS tissues. CD45+ (PTPRC+) cells were used for cell clustering and annotation. Changes in immune cell composition pre- and post-chemotherapy were characterized. Totally, 28,636 high-quality CD45+ (PTPRC+) cells were extracted. Following chemotherapy, the proportions of regulatory T cells (Tregs) and activated CD8 T cells decreased, while CD8 effector T cells increased. GO analysis indicated that differentially expressed genes (DEGs) in T cells were associated with cell activation, adaptive immune response, and immune response to tumor cells. Furthermore, the proportions of plasma cells increased, while naive B cells decreased. B cell surface receptors expression was upregulated, and GO analysis revealed DEGs of B cells were mainly enriched in B cell-mediated immunity and B cell activation. Moreover, M2 polarization of macrophages was suppressed post-chemotherapy. Overall, this study elucidates chemotherapy remodels the OS TIME landscape, triggering immune heterogeneity and enhancing anti-tumor properties.

Immune Cells in the Tumor Microenvironment of Soft Tissue Sarcomas

Soft tissue sarcomas (STSs) are a rare heterogeneous group of malignant neoplasms characterized by their aggressive course and poor response to treatment. This determines the relevance of research aimed at studying the pathogenesis of STSs. By now, it is known that STSs is characterized by complex relationships between the tumor cells and immune cells of the microenvironment. Dynamic interactions between tumor cells and components of the microenvironment enhance adaptation to changing environmental conditions, which provides the high aggressive potential of STSs and resistance to antitumor therapy. Today, active research is being conducted to find effective antitumor drugs and to evaluate the possibility of using therapy with immune cells of STS. The difficulty in assessing the efficacy of new antitumor options is primarily due to the high heterogeneity of this group of malignant neoplasms. Studying the role of immune cells in the microenvironment in the progression STSs and resistance to antitumor therapies will provide the discovery of new biomarkers of the disease and the prediction of response to immunotherapy. In addition, it will help to initially divide patients into subgroups of good and poor response to immunotherapy, thus avoiding wasting precious time in selecting the appropriate antitumor agent.

Personalized tumor combination therapy optimization using the single-cell transcriptome

BACKGROUND

The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.

METHODS

Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.

RESULTS

We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.

CONCLUSIONS

Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

The role of TXNIP in cancer: a fine balance between redox, metabolic, and immunological tumor control

Thioredoxin-interacting protein (TXNIP) is commonly considered a master regulator of cellular oxidation, regulating the expression and function of Thioredoxin (Trx). Recent work has identified that TXNIP has a far wider range of additional roles: from regulating glucose and lipid metabolism, to cell cycle arrest and inflammation. Its expression is increased by stressors commonly found in neoplastic cells and the wider tumor microenvironment (TME), and, as such, TXNIP has been extensively studied in cancers. In this review, we evaluate the current literature regarding the regulation and the function of TXNIP, highlighting its emerging role in modulating signaling between different cell types within the TME. We then assess current and future translational opportunities and the associated challenges in this area. An improved understanding of the functions and mechanisms of TXNIP in cancers may enhance its suitability as a therapeutic target.

Single-Nuclei Multiome (ATAC + Gene Expression) Sequencing of a Primary Canine Osteosarcoma Elucidates Intra-Tumoral Heterogeneity and Characterizes the Tumor Microenvironment

Osteosarcoma (OSA) is a highly aggressive bone tumor primarily affecting pediatric or adolescent humans and large-breed dogs. Canine OSA shares striking similarities with its human counterpart, making it an invaluable translational model for uncovering the disease's complexities and developing novel therapeutic strategies. Tumor heterogeneity, a hallmark of OSA, poses significant challenges to effective treatment due to the evolution of diverse cell populations that influence tumor growth, metastasis, and resistance to therapies. In this study, we apply single-nuclei multiome sequencing, encompassing ATAC (Assay for Transposase-Accessible Chromatin) and GEX (Gene Expression, or RNA) sequencing, to a treatment-naïve primary canine osteosarcoma. This comprehensive approach reveals the complexity of the tumor microenvironment by simultaneously capturing the transcriptomic and epigenomic profiles within the same nucleus. Furthermore, these results are analyzed in conjunction with bulk RNA sequencing and differential analysis of the same tumor and patient-matched normal bone. By delving into the intricacies of OSA at this unprecedented level of detail, we aim to unravel the underlying mechanisms driving intra-tumoral heterogeneity, opening new avenues for therapeutic interventions in both human and canine patients. This study pioneers an approach that is broadly applicable, while demonstrating significant heterogeneity in the context of a single individual's tumor.

Serum pro-surfactant protein B is correlated with clinical properties in osteosarcoma patients

It is critical to find efficient non-invasive prognostic factor for osteosarcoma. In this study, we demonstrated that serum protein of pro-surfactant protein B (pro-SFTPB) may be a potential diagnostic indicator in osteosarcoma. We found that serum pro-SFTPB was highly expressed in osteosarcoma patients and presented good diagnostic value to discern osteosarcoma patients from non-osteosarcoma control subjects. Serum pro-SFTPB was also significantly correlated with advanced clinical stage, distant metastasis, and shorter overall survival. In addition, serum pro-SFTPB was demonstrated to be an independent prognostic factor for osteosarcoma. Overall, our study demonstrated that serum pro-SFTPB may be a useful diagnostic factor for osteosarcoma.

The fibrinogen-albumin ratio as a novel prognostic factor for elderly patients with osteosarcoma

To analyze the prognostic value of fibrinogen-albumin ratio (FAR) in predicting the overall survival in elderly osteosarcoma patients. One hundred nineteen elderly osteosarcoma patients (> 40 years old) from 2 centers were retrospectively reviewed and analyzed. The cutoff values of the biomarker were calculated via receiver operating characteristic curves, and the cohort was divided into high FAR group and low FAR group. The association between the FAR and clinical-pathological parameters was analyzed. And the prognosis of elderly osteosarcoma patients and the potential risk factors were analyzed using Kaplan-Meier method and Cox proportional hazards model. Finally, a clinical nomogram was constructed, and its predictive capacity was verified. According to receiver operating characteristic results, the cutoff value for FAR was 0.098, and the enrolled patients were divided into the low FAR group and high FAR group. The FAR was significantly correlated with several clinical-pathological characteristics, including age, tumor size, tumor stage, recurrence, and metastasis. Moreover, the multivariate Cox analyses results showed that the FAR, pathological fracture, and metastasis were independent risk factors for overall survival in elderly osteosarcoma patients. The predictive nomogram was subsequently constructed, representing satisfactory predictive performance for prognosis in elderly patients with osteosarcoma. The FAR value is a promising indicator for elderly osteosarcoma patients, which is correlated with the various clinical characteristics and prognosis. A clinical nomogram integrating FAR and other clinical indicators is a convenient and available tool to assess the prognosis and manage the individualized and precise treatment of elderly patients with osteosarcoma.

Carboxypeptidase E is a prognostic biomarker co-expressed with osteoblastic genes in osteosarcoma

Osteosarcoma (OS) is a rare primary malignant bone tumor in adolescents and children with a poor prognosis. The identification of prognostic genes lags far behind advancements in treatment. In this study, we identified differential genes using mRNA microarray analysis of five paired OS tissues. Hub genes, gene set enrichment analysis, and pathway analysis were performed to gain insight into the pathway alterations of OS. Prognostic genes were screened using the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) dataset, then overlapped with the differential gene dataset. The carboxypeptidase E (CPE) gene, found to be an independent risk factor, was further validated using RT-PCR and Gene Expression Omnibus (GEO) datasets. Additionally, we explored the specific expression of CPE in OS tissues by reanalyzing single-cell genomics. Interestingly, CPE was found to be co-expressed with osteoblast lineage cell clusters that expressed RUNX2, SP7, SPP1, and IBSP marker genes in OS. These results suggest that CPE could serve as a prognostic factor in osteoblastic OS and should be further investigated as a potential therapeutic target.

From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies

Cancer manifests as a multifaceted disease, characterized by aberrant cellular proliferation, survival, migration, and invasion. Tumors exhibit variances across diverse dimensions, encompassing genetic, epigenetic, and transcriptional realms. This heterogeneity poses significant challenges in prognosis and treatment, affording tumors advantages through an increased propensity to accumulate mutations linked to immune system evasion and drug resistance. In this review, we offer insights into tumor heterogeneity as a crucial characteristic of cancer, exploring the difficulties associated with measuring and quantifying such heterogeneity from clinical and biological perspectives. By emphasizing the critical nature of understanding tumor heterogeneity, this work contributes to raising awareness about the importance of developing effective cancer therapies that target this distinct and elusive trait of cancer.

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

Osteosarcoma (OS) is a heterogeneous, aggressive malignancy of the bone that disproportionally affects children and adolescents. Therapeutic interventions for OS are limited, which is in part due to the complex tumor microenvironment (TME) that has proven to be refractory to immunotherapies. Thus, there is a need to better define the complexity of the OS TME. To address this need, we used single-cell RNA sequencing (scRNA-seq) to describe the cellular and molecular composition of the TME in 6 treatment-naïve dogs with spontaneously occurring primary OS. Through analysis of 35,310 cells, we identified 30 distinct immune cell types, 9 unique tumor populations, 1 cluster of fibroblasts, and 1 cluster of endothelial cells. Independent reclustering of major cell types revealed the presence of follicular helper T cells, mature regulatory dendritic cells (mregDCs), and 8 transcriptomically distinct macrophage/monocyte populations. Cell-cell interaction inference analysis predicted that mregDCs and tumor-associated macrophages (TAMs) play key roles in modulating T cell mediate immunity. Furthermore, we used publicly available human OS scRNA-seq data to complete a cross-species cell type gene signature homology analysis. The analysis revealed a high degree of cell type gene signature homology between species, suggesting the cellular composition of OS is largely conserved between humans and dogs. Our findings provide key new insights into the biology of canine OS and highlight the conserved features of OS across species. Generally, the data presented here acts as a cellular and molecular roadmap of canine OS which can be applied to advance the translational immuno-oncology research field.

Integrated multiomic analysis and high-throughput screening reveal potential gene targets and synergetic drug combinations for osteosarcoma therapy

Although great advances have been made over the past decades, therapeutics for osteosarcoma are quite limited. We performed long-read RNA sequencing and tandem mass tag (TMT)-based quantitative proteome on osteosarcoma and the adjacent normal tissues, next-generation sequencing (NGS) on paired osteosarcoma samples before and after neoadjuvant chemotherapy (NACT), and high-throughput drug combination screen on osteosarcoma cell lines. Single-cell RNA sequencing data were analyzed to reveal the heterogeneity of potential therapeutic target genes. Additionally, we clarified the synergistic mechanisms of doxorubicin (DOX) and HDACs inhibitors for osteosarcoma treatment. Consequently, we identified 2535 osteosarcoma-specific genes and several alternative splicing (AS) events with osteosarcoma specificity and/or patient heterogeneity. Hundreds of potential therapeutic targets were identified among them, which showed the core regulatory roles in osteosarcoma. We also identified 215 inhibitory drugs and 236 synergistic drug combinations for osteosarcoma treatment. More interestingly, the multiomic analysis pointed out the pivotal role of HDAC1 and TOP2A in osteosarcoma. HDAC inhibitors synergized with DOX to suppress osteosarcoma both in vitro and in vivo. Mechanistically, HDAC inhibitors synergized with DOX by downregulating SP1 to transcriptionally modulate TOP2A expression. This study provided a comprehensive view of molecular features, therapeutic targets, and synergistic drug combinations for osteosarcoma.

A1BG-AS1 promotes the biological functions of osteosarcoma cells via regulating the microRNA-148a-3p/USP22 axis and stabilizing the expression of SIRT1 through deubiquitinase function

BACKGROUND

The study aims to explore the role of A1BG antisense RNA 1 (A1BG-AS1), microRNA (miR)-148a-3p and ubiquitin-specific protease 22 (USP22) on osteosarcoma (OS) cell growth.

RESEARCH DESIGN & METHODS

A1BG-AS1, miR-148a-3p, USP22, and silent information regulator 2 homolog 1 (SIRT1) levels in OS tissues and cells were determined. The effects of A1BG-AS1, miR-148a-3p, and USP22 on the biological functions of OS cells were examined by functional assays. In vivo assay was conducted to observe the effect of A1BG-AS1 on OS growth in vitro. The relationship of A1BG-AS1, miR-148a-3p, and USP22 was analyzed by bioinformatics analysis, RNA-fluorescence in situ hybridization, luciferase activity, and RNA binding protein immunoprecipitation assays. The relation between USP22 and SIRT1 was evaluated by immunoprecipitation.

RESULTS

A1BG-AS1 and USP22 were highly expressed, and miR-148a-3p was lowly expressed in OS tissues and cells. Down-regulation of A1BG-AS1 and USP22 or up-regulation of miR-148a-3p impaired the malignant behaviors of OS cells. A1BG-AS1 sponged miR-148a-3p, and miR-148a-3p targeted USP22, thereby inhibiting USP22 expression. Up-regulating USP22 reversed the A1BG-AS1 suppression-induced phenotypic inhibition of OS cells. USP22 affected the biological functions of OS cells by deubiquitinating SIRT1.

CONCLUSION

A1BG-AS1 facilitates the biological functions of OS cells via mediating the miR-148a-3p/USP22 axis.

Longitudinal characterization of primary osteosarcoma and derived subcutaneous and orthotopic relapsed patient-derived xenograft models

Osteosarcoma is a rare bone cancer in adolescents and young adults with a dismal prognosis because of metastatic disease and chemoresistance. Despite multiple clinical trials, no improvement in outcome has occurred in decades. There is an urgent need to better understand resistant and metastatic disease and to generate in vivo models from relapsed tumors. We developed eight new patient-derived xenograft (PDX) subcutaneous and orthotopic/paratibial models derived from patients with recurrent osteosarcoma and compared the genetic and transcriptomic landscapes of the disease progression at diagnosis and relapse with the matching PDX. Whole exome sequencing showed that driver and copy-number alterations are conserved from diagnosis to relapse, with the emergence of somatic alterations of genes mostly involved in DNA repair, cell cycle checkpoints, and chromosome organization. All PDX patients conserve most of the genetic alterations identified at relapse. At the transcriptomic level, tumor cells maintain their ossification, chondrocytic, and trans-differentiation programs during progression and implantation in PDX models, as identified at the radiological and histological levels. A more complex phenotype, like the interaction with immune cells and osteoclasts or cancer testis antigen expression, seemed conserved and was hardly identifiable by histology. Despite NSG mouse immunodeficiency, four of the PDX models partially reconstructed the vascular and immune-microenvironment observed in patients, among which the macrophagic TREM2/TYROBP axis expression, recently linked to immunosuppression. Our multimodal analysis of osteosarcoma progression and PDX models is a valuable resource to understand resistance and metastatic spread mechanisms, as well as for the exploration of novel therapeutic strategies for advanced osteosarcoma.

Sulfatinib, a novel multi-targeted tyrosine kinase inhibitor of FGFR1, CSF1R, and VEGFR1-3, suppresses osteosarcoma proliferation and invasion via dual role in tumor cells and tumor microenvironment

Introduction

Tumor progression is driven by intrinsic malignant behaviors caused by gene mutation or epigenetic modulation, as well as crosstalk with the components in the tumor microenvironment (TME). Considering the current understanding of the tumor microenvironment, targeting the immunomodulatory stromal cells such as cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs) could provide a potential therapeutic strategy. Here, we investigated the effect of sulfatinib, a multi-targeted tyrosine kinase inhibitor (TKI) of FGFR1, CSF1R, and VEGFR1-3, on the treatment of osteosarcoma (OS).

Methods

In vitro, the antitumor effect was tested by clony formation assay and apoptosis assay.The inhibition of tumor migration and invasion was detected by Transwell assay, and the de-polarization of macrophage was detected by flow cytometry.In vivo, subcutaneous and orthotopic tumor models were established to verify antitumor effect, and the underlying mechanism was verified by immunohistochemistry(IHC), immunofluorescence(IF) and flow cytometry.

Results

Sulfatinib suppressed OS cell migration and invasion by inhibiting epithelial-mesenchymal transition (EMT) by blocking the secretion of basic fibroblast growth factor (bFGF) in an autocrine manner. In addition, it regulated immune TME via inhibition of the migration of skeletal stem cells (SSCs) to the TME and the differentiation from SSCs to CAFs. Moreover, sulfatinib can suppress OS by modulation of the TME by inhibiting M2 polarization of macrophages. Systemic treatment of sulfatinib can reduce immunosuppression cells M2-TAMs, Tregs, and myeloid-derived suppressor cells (MDSCs) and increase cytotoxic T-cell infiltration in tumors, the lungs, and the spleens.

Discussion

Our preclinical experiments have shown that sulfatinib can inhibit the proliferation, migration, and invasion of OS by playing a dual role on tumor cells and the tumor microenvironment simultaneously and systematically reverse immunosuppression to immune activation status, which could be translated into clinical trials.

Construction and validation of an oxidative-stress-related risk model for predicting the prognosis of osteosarcoma

BACKGROUND

Osteosarcoma is the most common bone malignancy in teenagers, and warrants effective measures for diagnosis and prognosis. Oxidative stress (OS) is the key driver of several cancers and other diseases.

METHODS

The TARGET-osteosarcoma database was employed as the training cohort and GSE21257 and GSE39055 was applied for external validation. The patients were classified into the high- and low-risk groups based on the median risk score of each sample. ESTIMATE and CIBERSORT were applied for the evaluation of tumor microenvironment immune infiltration. GSE162454 of single-cell sequencing was employed for analyzing OS-related genes.

RESULTS

Based on the gene expression and clinical data of 86 osteosarcoma patients in the TARGET database, we identified eight OS-related genes, including MAP3K5, G6PD, HMOX1, ATF4, ACADVL, MAPK1, MAPK10, and INS. In both the training and validation sets, the overall survival of patients in the high-risk group was significantly worse than that in the low-risk group. The ESTIMATE algorithm revealed that patients in the high-risk group had higher tumor purity but lower immune score and stromal score. In addition, the CIBERSORT algorithm showed that the M0 and M2 macrophages were the predominant infiltrating cells in osteosarcoma. Based on the expression analysis of immune checkpoint, CD274(PDL1), CXCL12, BTN3A1, LAG3, and IL10 were identified as potential immune therapy targets. Analysis of the single cell sequencing data also revealed the expression patterns of OS-related genes in different cell types.

CONCLUSIONS

An OS-related prognostic model can accurately provide the prognosis of osteosarcoma patients, and may help identify suitable candidates for immunotherapy.

A new insight of immunosuppressive microenvironment in osteosarcoma lung metastasis

The lung is the primary organ for the metastasis of osteosarcoma. Although the application of neoadjuvant chemotherapy and surgery has remarkably improved the survival rate of patients with osteosarcoma, prognosis is still poor for those patients with metastasis. In this study, we performed further bioinformatics analysis on single-cell RNA sequencing (scRNA-seq) data published before, containing 75,317 cells from two osteosarcoma lung metastasis and five normal lung tissues. First, we classified 17 clusters, including macrophages, T cells, endothelial cells, and so on, indicating highly intratumoral heterogeneity in osteosarcoma lung metastasis. Next, we found macrophages in osteosarcoma lung metastasis did not have significant M1 or M2 polarizations. Then, we identified that T cells occupied the most abundant among all cell clusters, and found CD8+ T cells exhibited a low expression level of immune checkpoints in osteosarcoma lung metastasis. What is more, we identified C2_Malignant cells, and found CD63 might play vital roles in determining the infiltration of T cells and malignant cells in conventional-type osteosarcoma lung metastasis. Finally, we unveiled C1_Therapeutic cluster, a subcluster of malignant cells, was sensitive to oxfendazole and mevastatin, and the potential hydrogen-bond position and binding energy of oxfendazole-KIAA0907 and mevastatin-KIAA0907 were unveiled, respectively. Our results highlighted the power of scRNA-seq technique in identifying the complex tumor microenvironment of osteosarcoma lung metastasis, making it possible to devise precision therapeutic approaches.

Integrated analysis of single-cell and bulk RNA sequencing data reveals an immunostimulatory microenvironment in tumor thrombus of osteosarcoma

Tumor thrombus of bone sarcomas represents a unique reservoir for various types of cancer and immune cells, however, the investigation of tumor thrombus at a single-cell level is very limited. And it is still an open question to identify the thrombus-specific tumor microenvironment that is associated with the tumor-adaptive immune response. Here, by analyzing bulk tissue and single-cell level transcriptome from the paired thrombus and primary tumor samples of osteosarcoma (OS) patients, we define the immunostimulatory microenvironment in tumor thrombus of OS with a higher proportion of tumor-associated macrophages with M1-like states (TAM-M1) and TAM-M1 with high expression of CCL4. OS tumor thrombus is found to have upregulated IFN-γ and TGF-β signalings that are related to immune surveillance of circulating tumor cells in blood circulation. Further multiplexed immunofluorescence staining of the CD3/CD4/CD8A/CD68/CCL4 markers validates the immune-activated state in the tumor thrombus samples. Our study first reports the transcriptome differences at a single-cell level between tumor thrombus and primary tumor in sarcoma.

Signal Pathways and microRNAs in Osteosarcoma Growth and the Dual Role of Mesenchymal Stem Cells in Oncogenesis

The major challenges in Osteosarcoma (OS) therapy are its heterogeneity and drug resistance. The development of new therapeutic approaches to overcome the major growth mechanisms of OS is urgently needed. The search for specific molecular targets and promising innovative approaches in OS therapy, including drug delivery methods, is an urgent problem. Modern regenerative medicine focuses on harnessing the potential of mesenchymal stem cells (MSCs) because they have low immunogenicity. MSCs are important cells that have received considerable attention in cancer research. Currently, new cell-based methods for using MSCs in medicine are being actively investigated and tested, especially as carriers for chemotherapeutics, nanoparticles, and photosensitizers. However, despite the inexhaustible regenerative potential and known anticancer properties of MSCs, they may trigger the development and progression of bone tumors. A better understanding of the complex cellular and molecular mechanisms of OS pathogenesis is essential to identify novel molecular effectors involved in oncogenesis. The current review focuses on signaling pathways and miRNAs involved in the development of OS and describes the role of MSCs in oncogenesis and their potential for antitumor cell-based therapy.

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes

Background

Tumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma.

Methods

ScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What’s more, the prognostic model was verified by external datasets and experiment in vitro.

Results

Eleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes.

Conclusions

This study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response.

Single-cell RNA sequencing in orthopedic research

Although previous RNA sequencing methods have been widely used in orthopedic research and have provided ideas for therapeutic strategies, the specific mechanisms of some orthopedic disorders, including osteoarthritis, lumbar disc herniation, rheumatoid arthritis, fractures, tendon injuries, spinal cord injury, heterotopic ossification, and osteosarcoma, require further elucidation. The emergence of the single-cell RNA sequencing (scRNA-seq) technique has introduced a new era of research on these topics, as this method provides information regarding cellular heterogeneity, new cell subtypes, functions of novel subclusters, potential molecular mechanisms, cell-fate transitions, and cell‒cell interactions that are involved in the development of orthopedic diseases. Here, we summarize the cell subpopulations, genes, and underlying mechanisms involved in the development of orthopedic diseases identified by scRNA-seq, improving our understanding of the pathology of these diseases and providing new insights into therapeutic approaches.

Characterizing the tumor microenvironment at the single-cell level reveals a novel immune evasion mechanism in osteosarcoma

The immune microenvironment extensively participates in tumorigenesis as well as progression in osteosarcoma (OS). However, the landscape and dynamics of immune cells in OS are poorly characterized. By analyzing single-cell RNA sequencing (scRNA-seq) data, which characterize the transcription state at single-cell resolution, we produced an atlas of the immune microenvironment in OS. The results suggested that a cluster of regulatory dendritic cells (DCs) might shape the immunosuppressive microenvironment in OS by recruiting regulatory T cells. We also found that major histocompatibility complex class I (MHC-I) molecules were downregulated in cancer cells. The findings indicated a reduction in tumor immunogenicity in OS, which can be a potential mechanism of tumor immune escape. Of note, CD24 was identified as a novel "don't eat me" signal that contributed to the immune evasion of OS cells. Altogether, our findings provide insights into the immune landscape of OS, suggesting that myeloid-targeted immunotherapy could be a promising approach to treat OS.

RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues

Osteosarcoma (OS) is the most common primary cancer in the skeletal system, characterized by a high incidence of lung metastasis, local recurrence and death. Systemic treatment of this aggressive cancer has not improved significantly since the introduction of chemotherapy regimens, underscoring a critical need for new treatment strategies. TRAIL receptors have long been proposed to be therapeutic targets for cancer treatment, but their role in osteosarcoma remains unclear. In this study, we investigated the expression profile of four TRAIL receptors in human OS cells using total RNA-seq and single-cell RNA-seq (scRNA-seq). The results revealed that TNFRSF10B and TNFRSF10D but not TNFRSF10A and TNFRSF10C are differentially expressed in human OS cells as compared to normal cells. At the single cell level by scRNA-seq analyses, TNFRSF10B, TNFRSF10D, TNFRSF10A and TNFRSF10C are most abundantly expressed in endothelial cells of OS tissues among nine distinct cell clusters. Notably, in osteoblastic OS cells, TNFRSF10B is most abundantly expressed, followed by TNFRSF10D, TNFRSF10A and TNFRSF10C. Similarly, in an OS cell line U2-OS using RNA-seq, TNFRSF10B is most abundantly expressed, followed by TNFRSF10D, TNFRSF10A and TNFRSF10C. According to the TARGET online database, poor patient outcomes were associated with low expression of TNFRSF10C. These results could provide a new perspective to design novel therapeutic targets of TRAIL receptors for the diagnosis, prognosis and treatment of OS and other cancers.

Establishment of Rapid and Accurate Screening System for Molecular Target Therapy of Osteosarcoma

Introduction Comprehensive analyses using clinical sequences subcategorized osteosarcoma (OS) into several groups according to the activated signaling pathways. Mutually exclusive co-occurrences of gene amplification (PDGFRA/KIT/KDR, VEGFA/CCND3, and MDM2/CDK4) have been identified in approximately 40% of OS, representing candidate subsets for clinical evaluation of additional therapeutic options. Thus, it would be desirable to evaluate the specific gene amplification before starting therapy in patients with OS. Materials and Methods This is a retrospective study. We examined 13 cases of clinical OS samples using NanoString-based copy number variation (CNV) analysis. Decalcification and chemotherapeutic effects on this analysis were also assessed. Results First, the accuracy of this system was validated by showing that amplification/deletion data obtained from this system using various types of cancer cell lines almost perfectly matched to that from the Cancer Cell Line Encyclopedia (CCLE). We identified potentially actionable alterations in CDK4/MDM2 amplification in 10% of samples and potential additional therapeutic targets (PDGFRA/KIT/KDR and VEGFA/CCND3) in 20% of samples, which is consistent with the reported frequencies. Furthermore, this assay could identify these potential therapeutic targets regardless of the sample status (frozen vs formalin-fixed paraffin-embedded [FFPE] tissues). Conclusion We established a NanoString-based rapid and cost-effective method with a short turnaround time (TAT) to examine gene amplification status in OS. This CNV analysis using FFPE samples is recommended where the histological evaluation of viable tumor cells is possible, especially for tumors after chemotherapy with higher chemotherapeutic effects.

Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues

Nuclear paraspeckles are subnuclear bodies contracted by nuclear-enriched abundant transcript 1 (NEAT1) long non-coding RNA, localised in the interchromatin space of mammalian cell nuclei. Paraspeckles have been critically involved in tumour progression, metastasis and chemoresistance. To this date, there are limited findings to suggest that paraspeckles, NEAT1 and heterogeneous nuclear ribonucleoproteins (hnRNPs) directly or indirectly play roles in osteosarcoma progression. Herein, we analysed NEAT1, paraspeckle proteins (SFPQ, PSPC1 and NONO) and hnRNP members (HNRNPK, HNRNPM, HNRNPR and HNRNPD) gene expression in 6 osteosarcoma tumour tissues using the single-cell RNA-sequencing method. The normalised data highlighted that the paraspeckles transcripts were highly abundant in osteoblastic OS cells, except NEAT1, which was highly expressed in myeloid cell 1 and 2 subpopulations.