Whole transcriptome analysis identifies differentially regulated networks between osteosarcoma and normal bone samples

Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma

Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type's preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs' risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma.

The combination of apatinib and antigen-specific DC-induced T cells exert antitumor effects by potently improving the immune microenvironment of osteosarcoma

Objective

Osteosarcoma (OS) is the most common primary bone sarcoma with a high propensity for local invasion and metastasis. Although the antitumor effect of apatinib has been well confirmed in advanced OS, the synergistic effect of apatinib and immunotherapies has not yet been elucidated.

Methods

In this study, we established tumour-bearing mice and observed tumour size with low and high doses of apatinib treatments. The expression of 17 cytokines, including vascular endothelial growth factor (VEGF), was detected by protein microarray analysis. Moreover, we designed apatinib and antigen-specific dendritic cell (DC)-T combination treatment for tumour-bearing mice. Tumour growth was detected by statistical analysis of tumour size and microvessel density (MVD) counting, the protein expression of VEGF by western blotting, the cytokines interleukin 6 (IL-6), IL-17 and interferon-gamma (IFN-γ) by enzyme-linked immunosorbent assay (ELISA), and the numbers of myeloid-derived suppressor cells (MDSCs) and tumour-infiltration macrophages (TAMs) by flow cytometry.

Results

The results showed that apatinib efficiently suppressed tumour growth, and high-dose apatinib achieved a stronger effect. The same was true for DC-T immunotherapy. However, their combination treatment revealed a better oncolytic effect. Meanwhile, apatinib or DC-T treatment inhibited the expression of VEGF and the proangiogenic mediators IL-6 and IL-17 but increased IFN-γ production. Combination therapy further reduced/increased these effects. In addition, the combination treatment reduced MDSC but enhanced TAM-M1 ratios in the OS microenvironment. These findings indicated that apatinib and antigen-specific DC-T combination therapy was more efficient in oncolysis by regulating pro-/anti-angiogenic inducers and improving the immune state in the OS microenvironment.

Conclusion

This study proved that it was feasible to employ immunotherapy with therapeutic agents in OS treatment, which may provide a new approach in addition to the combination of surgery with chemotherapy in tumour treatment.

Insights into Dysregulated Neurological Biomarkers in Cancer

The link between neurodegenerative diseases (NDs) and cancer has generated greater interest in biomedical research, with decades of global studies investigating neurodegenerative biomarkers in cancer to better understand possible connections. Tau, amyloid-β, α-synuclein, SOD1, TDP-43, and other proteins associated with nervous system diseases have also been identified in various types of solid and malignant tumors, suggesting a potential overlap in pathological processes. In this review, we aim to provide an overview of current evidence on the role of these proteins in cancer, specifically examining their effects on cell proliferation, apoptosis, chemoresistance, and tumor progression. Additionally, we discuss the diagnostic and therapeutic implications of this interconnection, emphasizing the importance of further research to completely comprehend the clinical implications of these proteins in tumors. Finally, we explore the challenges and opportunities in targeting these proteins for the development of new targeted anticancer therapies, providing insight into how to integrate knowledge of NDs in oncology research.

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.

Airway microbiome signature accurately discriminates Mycobacterium tuberculosis infection status

Mycobacterium tuberculosis remains one of the deadliest infectious agents globally. Amidst efforts to control TB, long treatment duration, drug toxicity, and resistance underscore the need for novel therapeutic strategies. Despite advances in understanding the interplay between microbiome and disease in humans, the specific role of the microbiome in predicting disease susceptibility and discriminating infection status in tuberculosis still needs to be fully investigated. We investigated the impact of M.tb infection and M.tb-specific IFNγ immune responses on airway microbiome diversity by performing TB GeneXpert and QuantiFERON-GOLD assays during the follow-up phase of a longitudinal HIV-Lung Microbiome cohort of individuals recruited from two large independent cohorts in rural Uganda. M.tb rather than IFNγ immune response mainly drove a significant reduction in airway microbiome diversity. A microbiome signature comprising Streptococcus, Neisseria, Fusobacterium, Prevotella, Schaalia, Actinomyces, Cutibacterium, Brevibacillus, Microbacterium, and Beijerinckiacea accurately discriminated active TB from Latent TB and M.tb-uninfected individuals.

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.

Identification of immune-related tumor antigens and immune subtypes in osteosarcoma

Purpose

The development of tumor vaccines has become a hot topic in immunotherapy for osteosarcoma (OS); however, more tumor antigens with stronger immunogenicity need to be identified.

Methods

We downloaded six sets of gene expression profile data from online databases. The overexpressed genes were analyzed, intersected, and used to calculate the immune infiltration abundance in the TARGET OS dataset based on their expression matrix. Potential tumor antigen genes were identified based on whether they exhibited a high correlation with the antigen-presenting cells (APCs). A total of 1330 immune-related genes (IRGs) from the ImmPort website were retrieved based on their expression, and the Consensus Cluster method was used to obtain immune subtypes of the OS samples. Prognosis, immune microenvironment, and sensitivity to drugs were compared among the immune subtypes.

Results

In total, 680 genes were overexpressed in at least two datasets, of which TREM2, TNFRSF12A, and THY1 were positively correlated with different APCs. Based on the expression matrix of 1330 IRGs in TARGET-OS, two immune subtypes, IS1 and IS2, were identified. The prognosis of the IS1 subtype was better than that of IS2, the expression of immune checkpoint (ICP)-related genes was higher in patients with the IS1 subtype, and immune cell infiltration and sensitivity to 16 drugs were generally higher in IS1 subtype patients.

Conclusion

We identified three APC-correlated genes that can be considered to code for potential novel tumor antigens for OS vaccines. Two immune subtypes in patients with OS were identified to implement personalized treatments using mRNA vaccines.

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

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

Integrated transcriptomic analysis systematically reveals the heterogeneity and molecular characterization of cancer-associated fibroblasts in osteosarcoma

BACKGROUND

Osteosarcoma (OS), with a peak incidence during the adolescent growth spurt, is correlated with poor prognosis for its high malignancy. The tumor microenvironment (TME) is highly complicated, with frequent interactions between tumor and stromal cells. The cancer-associated fibroblasts (CAFs) in the TME have been considered to actively involve in the progression, metastasis, and drug resistance of OS. This study aimed to characterize cellular heterogeneity and molecular characterization in CAFs subtypes and explore the potential targeting therapeutic strategies to improve the prognosis of OS patients.

METHODS

The single-cell atlas of human OS tumor lesions were constructed from the GEO database. Then significant marker genes and potential biological functions for each CAFs subtype were identified and explored using the Seurat R package. Next, by performing the survival analyses and constructing the risk scores for CAFs subtypes, we aimed to identify and characterize the prognostic values of specific marker genes and different CAFs subtypes. Furthermore, we explored the therapeutic targets and innovative drugs targeting different CAFs subtypes based on the GDSC database. Finally, prognoses related CAFs subtypes were further validated through immunohistochemistry (IHC) on clinical OS specimens.

RESULTS

Overall, nine main cell clusters and five subtypes of CAFs were identified. The differentially expressed marker genes for each CAFs clusters were then identified. Moreover, through Gene Ontology (GO) enrichment analysis, we defined the CAFs_2 (upregulated CXCL14 and C3), which was closely related to leukocyte migration and chemotaxis, as inflammatory CAFs (iCAFs). Likewise, we defined the CAFs_4 (upregulated CD74, HLA-DRA and HLA-DRB1), which was closely related to antigen process and presentation, as antigen-presenting CAFs (apCAFs). Furthermore, Kaplan-Meier analyses showed that CAFs_2 and CAFs_4 were correlated with poor clinical prognosis of OS patients. Meanwhile, therapeutic drugs targeting CAFs_2 and CAFs_4, such as 17-AAG/Docetaxel/Bleomycin and PHA-793887/NG-25/KIN001-102, were also explored, respectively. Finally, IHC assay confirmed the abundant CAFs_2 and CAFs_4 subtypes infiltration in the OS microenvironment compared with adjacent tissues.

CONCLUSION

Our study revealed the diversity, complexity, and heterogeneity of CAFs in OS, and complemented the single-cell atlas in OS TME.

Identification and prognostic evaluation of differentially expressed long noncoding RNAs associated with immune infiltration in osteosarcoma

Osteosarcoma is a malignant bone cancer that originates from the bone with the strongest invasiveness. Tumor formation strongly correlates with immune cell infiltration into the tumor immune microenvironment (TIME). Therefore, we aimed to identify TIME-related biomarkers as potential prognostic markers of osteosarcoma. The mRNA and long noncoding RNA (lncRNA) transcriptome data of 88 patients with osteosarcoma and the expression profile of GSE99671 were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Immune infiltration scores and types were evaluated using ESTIMATE and CIBERSORT. A linear model was established to identify the differentially expressed genes (DEGs) and lncRNAs (DElncRNAs). Functional enrichment analysis of DEGs was conducted by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and gene set variation analysis. DElncRNAs were analyzed using a weighted gene co-expression network. Least absolute shrinkage and selection operator regression was applied to screen for prognostic markers. Patient survival was predicted by the risk score and analyzed by receiver operating characteristic curve. Clinical features affecting patient survival were assessed. Immune infiltration positively correlated with osteosarcoma patient survival. Different immune cell infiltrates in patients with osteosarcma may serve as prognostic indicators and targets for immunotherapy. In total, 1125 DEGs, 80 DElncRNAs, and 11 pairs of co-expressed lncRNA-mRNAs were identified. DEGs in the three modules were associated with immune infiltration into the TIME. Four DElncRNAs, namely AC015819.1, AC015911.3, AL365361.1, and USP30-AS1, showed good prognostic ability for osteosarcoma and were positively correlated with the immune score. Tumor metastasis and risk scores alone were good prognostic indicators, and a combination of the two variables can better predict the prognosis of osteosarcoma. We identified four lncRNAs, AC015819.1, AC015911.3, AL365361.1, and USP30-AS1, as potential biomarkers for osteosarcoma prognosis.

RANK/RANKL axis promotes migration, invasion, and metastasis of osteosarcoma via activating NF-κB pathway

Osteosarcoma (OS) is one of the most prevalent primary bone tumors with a high degree of metastasis and poor prognosis. Epithelial-to-mesenchymal transition (EMT) is a cellular mechanism that contributes to the invasion and metastasis of cancer cells, and OS cells have been reported to exhibit EMT-like characteristics. Our previous studies have shown that the interaction between tumor necrosis factor superfamily member 11 (TNFRSF11A; also known as RANK) and its ligand TNFSF11 (also known as RANKL) promotes the EMT process in breast cancer cells. However, whether the interaction between RANK and RANKL enhances aggressive behavior by inducing EMT in OS cells has not yet been elucidated. In this study, we showed that the interaction between RANK and RANKL increased the migration, invasion, and metastasis of OS cells by promoting EMT. Importantly, we clarified that the RANK/RANKL axis induces EMT by activating the nuclear factor-kappa B (NF-κB) pathway. Furthermore, the NF-κB inhibitor dimethyl fumarate (DMF) suppressed migration, invasion, and EMT in OS cells. Our results suggest that the RANK/RANKL axis may serve as a potential tumor marker and promising therapeutic target for OS metastasis. Furthermore, DMF may have clinical applications in the treatment of lung metastasis in patients with OS.

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.

Transcriptome Sequencing Unveils a Molecular-Stratification-Predicting Prognosis of Sarcoma Associated with Lipid Metabolism

Sarcomas are heterogeneous connective tissue malignancies that have been historically categorized into soft tissue and bone cancers. Although multimodal therapies are implemented, many sarcoma subtypes are still difficult to treat. Lipids play vital roles in cellular activities; however, ectopic levels of lipid metabolites have an impact on tumor recurrence, metastasis, and drug resistance. Thus, precision therapies targeting lipid metabolism in sarcoma need to be explored. In this study, we performed a comprehensive analysis of molecular stratification based on lipid metabolism-associated genes (LMAGs) using both public datasets and the data of patients in our cohort and constructed a novel prognostic model consisting of squalene epoxidase (SQLE) and tumor necrosis factor (TNF). We first integrated information on gene expression profile and survival outcomes to divide TCGA sarcoma patients into high- and low-risk subgroups and further revealed the prognosis value of the metabolic signature and immune infiltration of patients in both groups, thus proposing various therapeutic recommendations for sarcoma. We observed that the low-risk sarcoma patients in the TCGA-SARC cohort were characterized by high proportions of immune cells and increased expression of immune checkpoint genes. Subsequently, this lipid metabolic signature was validated in four external independent sarcoma datasets including the CHCAMS cohort. Notably, SQLE, a rate-limiting enzyme in cholesterol biosynthesis, was identified as a potential therapeutic target for sarcoma. Knockdown of SQLE substantially inhibited cell proliferation and colony formation while promoting the apoptosis of sarcoma cells. Terbinafine, an inhibitor of SQLE, displayed similar tumor suppression capacity in vitro. The prognostic predictive model and the potential drug target SQLE might serve as valuable hints for further in-depth biological, diagnostic, and therapeutic exploration of sarcoma.

Angio-Long Noncoding RNA MALAT1 (rs3200401) and MIAT (rs1061540) Gene Variants in Ovarian Cancer

The genotyping of long non-coding RNA (lncRNA)-related single-nucleotide polymorphisms (SNPs) could be associated with cancer risk and/or progression. This study aimed to analyze the angiogenesis-related lncRNAs MALAT1 (rs3200401) and MIAT (rs1061540) variants in patients with ovarian cancer (OC) using "Real-Time allelic discrimination polymerase chain reaction" in 182 formalin-fixed paraffin-embedded (FFPE) samples of benign, borderline, and primary malignant ovarian tissues. Differences in the genotype frequencies between low-grade ovarian epithelial tumors (benign/borderline) and malignant tumors and between high-grade malignant epithelial tumors and malignant epithelial tumors other than high-grade serous carcinomas were compared. Odds ratios (ORs)/95% confidence intervals were calculated as measures of the association strength. Additionally, associations of the genotypes with the available pathological data were analyzed. The heterozygosity of MALAT1 rs3200401 was the most common genotype (47.8%), followed by C/C (36.3%). Comparing the study groups, no significant differences were observed regarding this variant. In contrast, the malignant epithelial tumors had a higher frequency of the MIAT rs1061540 C/C genotype compared to the low-grade epithelial tumor cohorts (56.7% vs. 37.6, p = 0.031). The same genotype was significantly higher in high-grade serous carcinoma than its counterparts (69.4% vs. 43.8%, p = 0.038). Multivariate Cox regression analysis showed that the age at diagnosis was significantly associated with the risk of OC development. In contrast, the MIAT T/T genotype was associated with a low risk of malignant epithelial tumors under the homozygote comparison model (OR = 0.37 (0.16-0.83), p = 0.017). Also, MIAT T allele carriers were less likely to develop high-grade serous carcinoma under heterozygote (CT vs. CC; OR = 0.33 (0.12-0.88), p = 0.027) and homozygote (TT vs. CC; OR = 0.26 (0.07-0.90), p = 0.034) comparison models. In conclusion, our data provide novel evidence for a potential association between the lncRNA MIAT rs1061540 and the malignant condition of ovarian cancer, suggesting the involvement of such lncRNAs in OC development.

Artificial neural network-based gene screening and immune cell infiltration analysis of osteosarcoma feature

BACKGROUND

The present study aimed to construct an artificial neural network (ANN) model that leverages characteristic genes associated with osteosarcoma (OS) to enable accurate prognostication for OS patients.

METHODS

Our research revealed 467 differentially expressed genes (DEGs) via gene expression contrast analysis, consisting of 345 downregulated genes and 122 upregulated genes. Gene Ontology (GO) enrichment analysis illuminated functions primarily encompassing T-cell activation, secretory granule lumen and antioxidant activity, among others. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we discovered significant correlations between the DEGs and certain pathways, including phagosome, Staphylococcus aureus infection and human T-cell leukemia virus 1 infection. We then screened out 30 characteristic DEGs (CDEGs) based on random forest analysis and constructed the ANN model using the gene score matrix. To verify the credibility and accuracy of the ANN model, we performed internal and external validation processes, which affirmed our model's predictive capabilities.

RESULTS

The study further delved into the analysis of immune cell infiltration and its correlation with the target CDEGs, revealing disparities in the infiltration of 22 types of immune cells across different groups and their interrelationships. Moreover, we probed the expression of the two foremost CDEGs (YES1 and MFNG) in OS and normal tissues. We noted a positive relationship between the expression of YES1 and MFNG in OS tissues and the clinicopathological characteristics of OS patients.

CONCLUSIONS

Collectively, the findings of the present study validate the effectiveness of the CDEGs-based ANN model in predicting OS patients, which might facilitate early diagnosis and treatment of OS.

Silencing Lnc-HES1-10 Inhibits Osteosarcoma Cells Proliferation, Invasive Ability, and Metastasis

BACKGROUND

Long noncoding RNA (LncRNA) play a vital role in the development and pathophysiology of osteosarcoma (OS). However, the LncRNA activated by HES1-10 in OS has not been furthered investigated. This present study aims to show the possible function of Lnc-HES1-10 in OS.

METHODS

Cell proliferation in vitro were assessed by the MTT assay, whereas the migration and invasion abilities of OS cell lines were measured by wound-healing migration assay and transwell invasion assay, respectively. Quantitative reverse transcriptase polymerase chain reaction and western blot analysis was used to detected the expression level of HES1-10.

RESULTS

The present study demonstrated that the Lnc-HES1-10 is overexpressed in OS and associated with poor prognosis of patients. In addition, the results revealed that Lnc-HES1-10 is overexpressed in MG63 and 143B OS cell lines and promote proliferation on both cell lines in vitro. Furthermore, migration and invasion abilities of MG63 and 143B cells are suppressed after silencing Lnc-HES1-10.

CONCLUSION

Our finding demonstrates that HES1-10 plays a crucial role in regulating OS growth and metastasis.

The combination of baseline neutrophil to lymphocyte ratio and dynamic changes during treatment can better predict the survival of osteosarcoma patients

Background

Osteosarcoma is a primary malignant bone tumor with a high metastatic potential that accounts for a significant proportion of all bone tumors. The prognosis for patients with metastatic or recurrence disease remains poor. The neutrophil-to-lymphocyte ratio (NLR) has become a potential prognostic biomarker for cancer. Recent evidence suggests that the dynamic changes in neutrophil-to-lymphocyte ratio (NLR) during treatment may be more informative in predicting patient prognosis, but the value of dynamic NLR in osteosarcoma has not yet been determined.

Methods

This retrospective study retrospectively analyzed the clinical information of 251 osteosarcoma patients diagnosed and treated in West China Hospital of Sichuan University, explored the impact of baseline NLR and changes in NLR during treatment on the prognosis of osteosarcoma patients, and further combined baseline NLR with Delta NLR to build an NLR staging system.

Results

The results showed that both baseline NLR and delta NLR had some predictive ability for the prognosis of osteosarcoma patients (P = 6.90e-4, P = 0.022). Patients with high baseline NLR were more likely to have a decrease in delta NLR (P = 1.24e-10). The NLR stage had a better predictive ability than baseline NLR and delta NLR, and was an independent prognostic factor for overall survival in osteosarcoma patients HR: 2.456 (1.625-3.710) (P = 1.97e-05).

Conclusion

NLR has value in continuous monitoring, and continuous monitoring of NLR can better predict the survival of osteosarcoma patients compared to baseline NLR.

Comprehensive analysis of BTNL9 as a prognostic biomarker correlated with immune infiltrations in thyroid cancer

BACKGROUND

Thyroid cancer (THCA) is the most common type of endocrine cancers, and the disease recurrences were usually associated with the risks of metastasis and fatality. Butyrophilin-like protein 9 (BTNL9) is a member of the immunoglobulin families. This study investigated the prognostic role of BTNL9 in THCA.

METHODS

Gene enhancers of BTNL9 were identified by interrogating H3K27ac ChIP-seq and RNA-seq data of papillary thyroid cancer (PTC) and benign thyroid nodule (BTN) tissues. Meanwhile, BTNL9 expression level was verified by qRT-PCR in 30 pairs of primary THCA and adjacent normal tissues. Clinicopathological and RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) to analyze the relations between BTNL9 expression and immune cell infiltration, chemokines/cytokines, immune checkpoint genes, clinical parameters and prognosis values. Besides, survival analysis combining BTNL9 expression and immune cell infiltration scores was conducted. Functional enrichment analysis was performed to investigate the potential biological mechanisms. Cox regression analyses were used to explore independent clinical indicators, and a nomogram model incorporating BTNL9 expression with clinical parameters was established.

RESULTS

BTNL9 showed significantly stronger H3K27ac modifications in BTN than PTC tissues at the promoter region (chr5: 181,035,673-181,047,436) and gene body (chr5: 181,051,544-181,054,849). The expression levels of BTNL9 were significantly down-regulated in THCA samples compared to normal tissues, and were strongly associated with different tumor stages, immune cell infiltrations, chemokines/cytokines and immune checkpoint genes in THCA. Functional enrichment analyses indicated that BTNL9 was involved in immune-related and cancer-related pathways. The Kaplan-Meier analysis showed lower BTNL9 expression was associated with poorer progression-free interval (PFI). BTNL9 expression and pathologic stages were independent prognostic indicators of PFI in THCA.

CONCLUSIONS

The results implied an important role of BTNL9 in the tumor progression, with the possibility of serving as a novel prognostic biomarker and a potential therapeutic target for THCA.

Engineered bone marrow as a clinically relevant ex vivo model for primary bone cancer research and drug screening

Osteosarcoma (OS) is the most common primary malignant bone cancer in children and adolescents. While numerous other cancers now have promising therapeutic advances, treatment options for OS have remained unchanged since the advent of standard chemotherapeutics and offer less than a 25% 5-y survival rate for those with metastatic disease. This dearth of clinical progress underscores a lack of understanding of OS progression and necessitates the study of this disease in an innovative system. Here, we adapt a previously described engineered bone marrow (eBM) construct for use as a three-dimensional platform to study how microenvironmental and immune factors affect OS tumor progression. We form eBM by implanting acellular bone-forming materials in mice and explanting the cellularized constructs after 8 wk for study. We interrogate the influence of the anatomical implantation site on eBM tissue quality, test ex vivo stability under normoxic (5% O2) and standard (21% O2) culture conditions, culture OS cells within these constructs, and compare them to human OS samples. We show that eBM stably recapitulates the composition of native bone marrow. OS cells exhibit differential behavior dependent on metastatic potential when cultured in eBM, thus mimicking in vivo conditions. Furthermore, we highlight the clinical applicability of eBM as a drug-screening platform through doxorubicin treatment and show that eBM confers a protective effect on OS cells that parallel clinical responses. Combined, this work presents eBM as a cellular construct that mimics the complex bone marrow environment that is useful for mechanistic bone cancer research and drug screening.

Meta-analysis of integrated ChIP-seq and transcriptome data revealed genomic regions affected by estrogen receptor alpha in breast cancer

BACKGROUND

The largest group of patients with breast cancer are estrogen receptor-positive (ER+) type. The estrogen receptor acts as a transcription factor and triggers cell proliferation and differentiation. Hence, investigating ER-DNA interaction genomic regions can help identify genes directly regulated by ER and understand the mechanism of ER action in cancer progression.

METHODS

In the present study, we employed a workflow to do a meta-analysis of ChIP-seq data of ER+ cell lines stimulated with 10 nM and 100 nM of E2. All publicly available data sets were re-analyzed with the same platform. Then, the known and unknown batch effects were removed. Finally, the meta-analysis was performed to obtain meta-differentially bound sites in estrogen-treated MCF7 cell lines compared to vehicles (as control). Also, the meta-analysis results were compared with the results of T47D cell lines for more precision. Enrichment analyses were also employed to find the functional importance of common meta-differentially bound sites and associated genes among both cell lines.

RESULTS

Remarkably, POU5F1B, ZNF662, ZNF442, KIN, ZNF410, and SGSM2 transcription factors were recognized in the meta-analysis but not in individual studies. Enrichment of the meta-differentially bound sites resulted in the candidacy of pathways not previously reported in breast cancer. PCGF2, HNF1B, and ZBED6 transcription factors were also predicted through the enrichment analysis of associated genes. In addition, comparing the meta-analysis results of both ChIP-seq and RNA-seq data showed that many transcription factors affected by ER were up-regulated.

CONCLUSION

The meta-analysis of ChIP-seq data of estrogen-treated MCF7 cell line leads to the identification of new binding sites of ER that have not been previously reported. Also, enrichment of the meta-differentially bound sites and their associated genes revealed new terms and pathways involved in the development of breast cancer which should be examined in future in vitro and in vivo studies.

Usefulness of COL11A1 as a Prognostic Marker of Tumor Infiltration

BACKGROUND

Determining the infiltration of carcinomas is essential for the proper follow-up and treatment of cancer patients. However, it continues to be a diagnostic challenge for pathologists in multiple types of tumors. In previous studies (carried out in surgical specimens), the protein COL11A1 has been postulated as an infiltration marker mainly expressed in the extracellular matrix (ECM). We hypothesized that a differential expression of COL11A1 may exist in the peritumoral stroma of tumors that have acquired infiltrating properties and that it may be detected in the small biopsies usually available in normal clinical practice.

MATERIAL AND METHODS

In our study, we performed immunohistochemical staining in more than 350 invasive and noninvasive small samples obtained via core needle biopsy (CNB), colonoscopy, or transurethral resection of bladder tumor (TURBT) of breast, colorectal, bladder, and ovarian cancer.

RESULTS

Our results revealed that COL11A1 immunostaining had a sensitivity to classify the samples into infiltrative vs. noninfiltrative tumors of 94% (breast), 97% (colorectal), >90% (bladder), and 74% (ovarian); and a specificity of 97% (breast), 100% (colorectal), and >90% (bladder). In ovarian cancer, the negative predictive value (0.59) did not present improvement over the usual histopathological markers. In all samples tested, the cumulative sensitivity was 86% and the specificity 96% (p < 0.0001).

CONCLUSIONS

COL11A1-positive immunostaining in small biopsies of breast, colon, bladder and ovarian cancer is an accurate predictive marker of tumor infiltration that can be easily implemented in daily clinical practice.

Dog breeds and conformations predisposed to osteosarcoma in the UK: a VetCompass study

BACKGROUND

Osteosarcoma is a malignant bone neoplasia that has high welfare consequences for affected dogs. Awareness of breed and canine conformational risk factors for osteosarcoma can assist with earlier diagnosis and improved clinical management. Study of osteosarcoma in dogs also offers translational value for humans. Anonymised clinical data within VetCompass on dogs under primary veterinary care in the UK were searched for osteosarcoma cases. Descriptive statistics reported overall and breed-specific prevalence. Risk factor analysis used multivariable logistic regression modelling.

RESULTS

From 905,552 study dogs, 331 osteosarcoma cases were confirmed yielding a one-year period prevalence of 0.037% (95% CI: 0.033-0.041). Breeds with the highest annual prevalence were the Scottish Deerhound (3.28%, 95% CI 0.90-8.18), Leonberger (1.48%, 95% CI 0.41- 3.75), Great Dane (0.87%, 95% CI 0.43- 1.55) and Rottweiler (0.84%, 95% CI 0.64-1.07). The median age at diagnosis was 9.64 years (IQR: 7.97-11.41). Following multivariable modelling, 11 breeds showed increased odds of osteosarcoma compared with crossbred dogs. Breeds with the highest odds included Scottish Deerhound (OR 118.40, 95% CI 41.12-340.95), Leonberger (OR 55.79, 95% CI 19.68-158.15), Great Dane (OR 34.24, 95% CI 17.81-65.83) and Rottweiler (OR 26.67, 95% CI 18.57-38.29). Compared with breeds with mesocephalic skull conformation, breeds with dolichocephalic skull conformation (OR 2.72, 95% CI 2.06-3.58) had increased odds while breeds with brachycephalic skull conformation showed reduced odds (OR 0.50, 95% CI 0.32-0.80). Chondrodystrophic breeds had 0.10 times the odds (95% CI 0.06-0.15) compared with non-chondrodystrophic breeds. Increasing adult bodyweight was associated with increasing odds of osteosarcoma.

CONCLUSIONS

The current study cements the concept that breed, bodyweight and longer leg or longer skull length are all strong risk factors for osteosarcoma in dogs. With this awareness, veterinarians can update their clinical suspicion and judgement, breeders can select towards lower-risk animals, and researchers can robustly define more useful study populations for fundamental and translational bioscience.

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.

ac4C acetylation regulates mRNA stability and translation efficiency in osteosarcoma

Objective

N4-acetylcytidine (ac4C) acetylation can promote target gene expression through improved mRNA stability. To explore the role of ac4C acetylation in osteosarcoma, U2OS and MG63 cell lines were treated with the N-acetyltransferase 10 (NAT10) inhibitor Remodelin. Reverse transcription-polymerase chain reaction (RT-PCR) and Western blot were used to test the gene and protein expression efficiency.

Methods

The proliferation rate of osteosarcoma cells was measured by a cell counting kit-8 (CCK8) assay. The cell cycle and apoptosis were analyzed by flow cytometry. The invasiveness of osteosarcoma cells was detected by a transwell invasion assay. The ac4C acetylation of target genes was screened by acetylated RNA immunoprecipitation and sequencing (acRIP-seq).

Results

We found that when osteosarcoma cells were treated with Remodelin at the optimal concentration, their NAT10 expression and the cell proliferation was inhibited, the cells in the G1 phase increased (P < 0.05) but those in the S phase decreased, the apoptotic cells in the early and late stages increased, and the cells invasiveness decreased (P < 0.05).

Conclusions

The farnesyltransferase subunit beta gene (FNTB) was identified by acRIP-seq as one of the target genes of ac4C acetylation and was further verified by RT-PCR and Western blot analyses. Remodelin was demonstrated to reduce the stability and protein translation efficiency of target gene mRNA in osteosarcoma cells. In conclusion, inhibition of ac4C acetylation in osteosarcoma can block proliferation and metastasis as well as promote apoptosis and cell cycle arrest. Ac4C acetylation contributes to the stability and protein translation efficiency of the downstream target gene mRNA.

Gene network analyses of larvae under different egg-protecting behaviors provide novel insights into immune response mechanisms of Amphioctopus fangsiao

Amphioctopus fangsiao was a representative economic species in cephalopods, which was vulnerable to marine bacteria. Vibrio anguillarum was a highly infectious pathogen that have recently been found to infect A. fangsiao and inhibit its growth and development. There were significant differences in the immune response mechanisms between egg-protected and egg-unprotected larvae. To explore larval immunity under different egg-protecting behaviors, we infected A. fangsiao larvae with V. anguillarum for 24 h and analyzed the transcriptome data about egg-protected and egg-unprotected larvae infected with 0, 4, 12, and 24 h using weighted gene co-expression networks (WGCNA) and protein-protein interaction (PPI) networks. Network analyses revealed a series of immune response processes after infection, and identified six key modules and multiple immune-related hub genes. Meanwhile, we found that ZNF family, such as ZNF32, ZNF160, ZNF271, ZNF479, and ZNF493 might play significant roles in A. fangsiao immune response processes. We first creatively combined WGCNA and PPI network analysis to deeply explore the immune response mechanisms of A. fangsiao larvae with different egg-protecting behaviors. Our results provided further insights into the immunity of V. anguillarum infected invertebrates, and laid the foundation for exploring the immune differences among cephalopods with different egg protecting behaviors.

Chondrosarcoma Resistance to Radiation Therapy: Origins and Potential Therapeutic Solutions

Chondrosarcoma is a malignant cartilaginous tumor that is particularly chemoresistant and radioresistant to X-rays. The first line of treatment is surgery, though this is almost impossible in some specific locations. Such resistances can be explained by the particular composition of the tumor, which develops within a dense cartilaginous matrix, producing a resistant area where the oxygen tension is very low. This microenvironment forces the cells to adapt and dedifferentiate into cancer stem cells, which are described to be more resistant to conventional treatments. One of the main avenues considered to treat this type of tumor is hadrontherapy, in particular for its ballistic properties but also its greater biological effectiveness against tumor cells. In this review, we describe the different forms of chondrosarcoma resistance and how hadrontherapy, combined with other treatments involving targeted inhibitors, could help to better treat high-grade chondrosarcoma.

Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression

BACKGROUND

Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease.

METHODS

Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene's regulation on osteosarcoma development were in succession explored.

RESULTS

Based on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene's physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene's association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored.

CONCLUSION

Using multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene's clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use.

Up-regulation of Core 1 Beta 1, 3-Galactosyltransferase Suppresses Osteosarcoma Growth with Induction of IFN-γ Secretion and Proliferation of CD8+ T Cells

AIM

Abnormal glycosylation often occurs in tumor cells. T-synthase (core 1 beta 1,3- galactosyltransferase, C1GALT1, or T-synthase) is a key enzyme involved in O-glycosylation. Although T-synthase is known to be important in human tumors, the effects of T-synthase and T-antigen on human tumor responses remain poorly defined.

METHODS

In this study, a T-synthase-specific short hairpin RNA (shRNA) or T-synthase-specific eukaryotic expression vector(pcDNA3.1(+)) was transfected into murine Osteosarcoma LM8 cells to assess the effects of T-synthase on T cells and cytokines.

RESULTS

The up-regulation of T-synthase promoted the proliferation of osteosarcoma cells in vitro, but it promoted the proliferation of tumor initially up to 2-3 weeks but showed significant growth inhibitory effect after 3 weeks post-implantation in vivo. Osteosarcoma cells with high T-synthase expression in vitro promoted the proliferation and inhibited the apoptosis of CD8+ T cells. Further, T-synthase upregulation promoted CD8+ T-cell proliferation and the increased production of CD4+ T cell-derived IFN-γ cytokines to induce the increased tumor lethality of CTLs.

CONCLUSION

Our data suggest that high T-synthase expression inhibits tumor growth by improving the body's anti-tumor immunity. Therefore, using this characteristic to prepare tumor cell vaccines with high immunogenicity provides a new idea for clinical immunotherapy of osteosarcoma.

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

Introduction

Tumor microenvironment (TME) has been shown to be extensively involved in tumor development. However, the dynamic change of TME components and their effects are still unclear. Here, we attempted to identify TME-related genes that could help predict survival and may be potential therapeutic targets.

Methods

Data was collected from UCSC Xena and GEO database. ESTIMATE and CIBERSORT algorithms were applied to estimate the components and the proportions of TIICs in TME. We analyzed the gene expression differences of immune components and stromal components, respectively, and finally got the overlapped DEGs. Through protein-protein interaction (PPI) network and univariate Cox regression analysis based on shared DEGs, we screened out and validated the TME-related genes. Focusing on this gene, we analyzed the expression and prognostic value of this gene, and investigated its relationship with immune cells by correlation analysis, single cell analysis, immunohistochemistry and immunofluorescence analysis.

Results

Through a series analysis, we found that the proportion of immune and stromal components was an important prognostic factor, and screened out a key gene, LPAR5, which was highly correlated with prognosis and metastasis. And the expression of LPAR5 was positively correlated with immune cells, especially macrophages, indicating LPAR5⁺ macrophages played an important role in tumor microenvironment of osteosarcoma. Meanwhile, the genes in LPAR5 high expression group were enriched in immune-related activities and pathways, and differentially expressed genes between LPAR5⁺ macrophages and LPAR5^- macrophages were enriched in the biological processes associated with phagocytosis and antigen presentation. What' more, we found that LPAR5 was mainly expressed in TME, and high LPAR5 expression predicting a better prognosis.

Conclusion

We identified a TME-related gene, LPAR5, which is a promising indicator for TME remodeling in osteosarcoma. Particularly, LPAR5⁺ macrophages might have great potential to be a prognostic factor and therapeutic target for osteosarcoma.

Hypoxia-immune-related microenvironment prognostic signature for osteosarcoma

Introduction: Increasing evidences have shown that hypoxia and the immune microenvironment play vital roles in the development of osteosarcoma. However, reliable gene signatures based on the combination of hypoxia and the immune status for prognostic prediction of osteosarcoma have so far not been identified. Methods: The individual hypoxia and immune status of osteosarcoma patients were identified with transcriptomic profiles of a training cohort from the TARGET database using ssGSEA and ESTIMATE algorithms, respectively. Lasso regression and stepwise Cox regression were performed to develop a hypoxia-immune-based gene signature. An independent cohort from the GEO database was used for external validation. Finally, a nomogram was constructed based on the gene signature and clinical features to improve the risk stratification and to quantify the risk assessment for individual patients. Results: Hypoxia and the immune status were significantly associated with the prognosis of osteosarcoma patients. Seven hypoxia- and immune-related genes (BNIP3, SLC38A5, SLC5A3, CKMT2, S100A3, CXCL11 and PGM1) were identified to be involved in our prognostic signature. In the training cohort, the prognostic signature discriminated high-risk patients with osteosarcoma. The hypoxia-immune-based gene signature proved to be a stable and predictive method as determined in different datasets and subgroups of patients. Furthermore, a nomogram based on the prognostic signature was generated to optimize the risk stratification and to quantify the risk assessment. Similar results were validated in an independent GEO cohort, confirming the stability and reliability of the prognostic signature. Conclusion: The hypoxia-immune-based prognostic signature might contribute to the optimization of risk stratification for survival and personalized management of osteosarcoma patients.

Identification of optimal reference genes for gene expression normalization in human osteosarcoma cell lines under proliferative conditions

The molecular pathogenesis and therapeutic target research studies on osteosarcoma (OS) have developed well during the last few years using various OS cell lines with reverse transcription quantitative polymerase chain reaction (RT-qPCR). However, the identification of suitable reference genes of RT-qPCR for OS cell lines has not been reported. Here, we conducted the normalization research of 12 reference genes (GAPDH, ACTB, 18S, B2M, ALAS1, GUSB, HPRT1, HMBS, PPIA, PUM1, RPL29, and TBP) for gene expression analysis in four kinds of human OS cell lines (U2OS, Saos-2, HOS, and MG-63) to improve the investigation of molecular mechanisms and the accuracy of diagnosis and prognostic molecular targets of OS. The gene expression stability and applicability of the 12 reference gene candidates were determined using geNorm, NormFinder, and BestKeeper software. The results indicated that PUM1 and the combination of PPIA + ALAS1 were recommended as the optimal reference gene in these four different sources of human OS cell lines under proliferative conditions. The present study identified the most suitable reference genes and reference gene combinations for OS cell lines under proliferative conditions in order to use in gene expression profile analysis. A reliable standardized method has the potential to improve the understanding of the biological mechanisms underlying OS in the future.

Current Status and Prospects of Targeted Therapy for Osteosarcoma

Osteosarcoma (OS) is a highly malignant tumor occurring in bone tissue with a high propensity to metastasize, and its underlying mechanisms remain largely elusive. The OS prognosis is poor, and improving the survival of OS patients remains a challenge. Current treatment methods such as surgical approaches, chemotherapeutic drugs, and immunotherapeutic drugs remain ineffective. As research progresses, targeted therapy is gradually becoming irreplaceable. In this review, several treatment modalities for osteosarcoma, such as surgery, chemotherapy, and immunotherapy, are briefly described, followed by a discussion of targeted therapy, the important targets, and new technologies for osteosarcoma treatment.

A novel chromatin regulator-related immune checkpoint related gene prognostic signature and potential candidate drugs for endometrial cancer patients

Background

Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries and its prevalence is increasing. As an emerging therapy with a promising efficacy, immunotherapy has been extensively applied in the treatment of solid tumors. In addition, chromatin regulators (CRs), as essential upstream regulators of epigenetics, play a significant role in tumorigenesis and cancer development.

Methods

CRs and immune checkpoint-related genes (ICRGs) were obtained from the previous top research. The Genome Cancer Atlas (TCGA) was utilized to acquire the mRNA expression and clinical information of patients with EC. Correlation analysis was utilized for screen CRs-related ICRGs (CRRICRGs). By Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, prognosis related CRRICRGs were screened out and risk model was constructed. The Kaplan–Meier curve was used to estimate the prognosis between high- and low-risk group. By comparing the IC50 value, the drugs sensitivity difference was explored. We obtained small molecule drugs for the treatment of UCEC patients based on CAMP dataset.

Results

We successfully constructed a 9 CRRICRs-based prognostic signature for patients with UCEC and found the riskscore was an independent prognostic factor. The results of functional analysis suggested that CRRICRGs may be involved in immune processes associated with cancer. Immune characteristics analysis provided further evidence that the CRRICRGs-based model was correlated with immune cells infiltration and immune checkpoint. Eight small molecule drugs that may be effective for the treatment of UCEC patients were screened. Effective drugs identified by drug sensitivity profiling in high- and low-risk groups.

Conclusion

In summary, our study provided novel insights into the function of CRRICRGs in UCEC. We also developed a reliable prognostic panel for the survival of patients with UCEC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00253-w.

Single-Cell Profiling of Tumor Microenvironment Heterogeneity in Osteosarcoma Identifies a Highly Invasive Subcluster for Predicting Prognosis

Osteosarcoma is the most common malignant bone tumor in adolescents, and metastasis is the key reason for treatment failure and poor prognosis. Once metastasis occurs, the 5-year survival rate is only approximately 20%, and assessing and predicting the risk of osteosarcoma metastasis are still difficult tasks. In this study, cellular communication between tumor cells and nontumor cells was identified through comprehensive analysis of osteosarcoma single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data, illustrating the complex regulatory network in the osteosarcoma microenvironment. In line with the heterogeneity of osteosarcoma, we found subpopulations of osteosarcoma cells that highly expressed COL6A1, COL6A3 and MIF and were closely associated with lung metastasis. Then, BCDEG, a reliable risk regression model that could accurately assess the metastasis risk and prognosis of patients, was established, providing a new strategy for the diagnosis and treatment of osteosarcoma.

Transcriptomic Analysis of Canine Osteosarcoma from a Precision Medicine Perspective Reveals Limitations of Differential Gene Expression Studies

Despite significant advances in cancer diagnosis and treatment, osteosarcoma (OSA), an aggressive primary bone tumor, has eluded attempts at improving patient survival for many decades. The difficulty in managing OSA lies in its extreme genetic complexity, drug resistance, and heterogeneity, making it improbable that a single-target treatment would be beneficial for the majority of affected individuals. Precision medicine seeks to fill this gap by addressing the intra- and inter-tumoral heterogeneity to improve patient outcome and survival. The characterization of differentially expressed genes (DEGs) unique to the tumor provides insight into the phenotype and can be useful for informing appropriate therapies as well as the development of novel treatments. Traditional DEG analysis combines patient data to derive statistically inferred genes that are dysregulated in the group; however, the results from this approach are not necessarily consistent across individual patients, thus contradicting the basis of precision medicine. Spontaneously occurring OSA in the dog shares remarkably similar clinical, histological, and molecular characteristics to the human disease and therefore serves as an excellent model. In this study, we use transcriptomic sequencing of RNA isolated from primary OSA tumor and patient-matched normal bone from seven dogs prior to chemotherapy to identify DEGs in the group. We then evaluate the universality of these changes in transcript levels across patients to identify DEGs at the individual level. These results can be useful for reframing our perspective of transcriptomic analysis from a precision medicine perspective by identifying variations in DEGs among individuals.

Hsp90 regulates the tumorigenic function of tyrosine protein kinase in osteosarcoma

Despite recent advances in diagnosis and treatment, osteosarcoma remains as the most common bone cancer in children and is associated with poor prognosis. Growing evidence has supported dysregulation of threonine and tyrosine protein kinase (TTK) expression as a hallmark of multiple cancers, however, its function in osteosarcoma remains to be elucidated. In the present study, we found that TTK was frequently overexpressed in osteosarcoma and associated with increased tumour growth and progression. Moreover, using both in vitro and in vivo assays, we provided evidence that TTK level was regulated by a molecular chaperone, heat shock protein 90 (Hsp90). Hsp90 directly interacted with TTK and prevents proteasome-dependent TTK degradation, leading to the accumulation of TTK in osteosarcoma cells. Elevated TTK promoted cancer cell proliferation and survival by activating cell-cycle progression and inhibiting apoptosis. Consistently, depletion of TTK by Hsp90 inhibition induced cell-cycle arrest, generated aneuploidy and eventually resulted in apoptotic cancer cell death. Together, our study revealed an important Hsp90-TTK regulatory axis in osteosarcoma cells to promote cancer cell growth and survival. These findings expand our knowledge on osteosarcoma pathogenesis and offer novel therapeutic options for clinical practice.

A Novel Overall Survival Prediction Signature Based on Cancer Stem Cell-Related Genes in Osteosarcoma

Background: Osteosarcoma is the most general bone malignancy that mostly affects children and adolescents. Numerous stem cell-related genes have been founded in distinct forms of cancer. This study aimed at identifying a stem cell-related gene model for the expected assessment of the prognosis of osteosarcoma patients.

Methods: We obtained the genes expression data and relevant clinical materials from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We identified differentially expressed genes (DEGs) from the GEO dataset, whereas prognostic stem cell-related genes were obtained from the TARGET database. Subsequently, univariate, LASSO and multivariate Cox regression analyses were applied to establish the stem cell-related signature. Finally, the prognostic value of the signature was validated in the GEO dataset.

Results: Twenty-five genes were prognostic ferroptosis-related DEGs. Consequently, we identified eight stem cell-related genes as a signature of prognosis of osteosarcoma patients. Then, the Kaplan–Meier (K-M) curve, the AUC value of ROC, and Cox regression analysis verified that the eight stem cell-related gene model were a new and substantial prognostic marker independent of other clinical traits. Moreover, the nomogram on the foundation of risk score and other clinical traits was established for predicting the survival rate of osteosarcoma patients. Biological function analyses displayed that tumor related pathways were affluent.

Conclusion: The expression level of stem cell-related genes offers novel prognostic markers as well as underlying therapeutic targets for the therapy and prevention of osteosarcoma.

Large Scale Identification of Osteosarcoma Pathogenic Genes by Multiple Extreme Learning Machine

At present, the main treatment methods of osteosarcoma are chemotherapy and surgery. Its 5-year survival rate has not been significantly improved in the past decades. Osteosarcoma has extremely complex multigenomic heterogeneity and lacks universally applicable signal blocking targets. Osteosarcoma is often found in adolescents or children under the age of 20, so it is very important to explore its genetic pathogenic factors. We used known osteosarcoma-related genes and computer algorithms to find more osteosarcoma pathogenic genes, laying the foundation for the treatment of osteosarcoma immune microenvironment-related treatments, so as to carry out further explorations on these genes. It is a traditional method to identify osteosarcoma related genes by collecting clinical samples, measuring gene expressions by RNA-seq technology and comparing differentially expressed gene. The high cost and time consumption make it difficult to carry out research on a large scale. In this paper, we developed a novel method “RELM” which fuses multiple extreme learning machines (ELM) to identify osteosarcoma pathogenic genes. The AUC and AUPR of RELM are 0.91 and 0.88, respectively, in 10-cross validation, which illustrates the reliability of RELM.

Identification of abnormally high expression of POGZ as a new biomarker associated with a poor prognosis in osteosarcoma

Osteosarcoma (OS) is the most prevalent malignant bone tumor in children and young adults. There is an urgent need for a novel biomarker related to the prognosis of OS. We performed a meta-analysis incorporating six independent datasets and performed a survival analysis with one independent dataset GSE21257 in the GEO database for gene screening. The results revealed that one potential biomarker related to OS survival, POGZ was the most significantly upregulated gene. We also verified that the POGZ was overexpressed in clinical samples. The survival analysis revealed that POGZ is associated with a poor prognosis in OS. Moreover, flow cytometry analysis of isolated OS cells demonstrated that OS cells were arrested in the G1 phase after POGZ knockdown. The RNA-seq results indicated that POGZ was co-expressed with CCNE1 and CCNB1. Pathway analysis showed that genes associated with high expression levels of POGZ were related to the cell cycle pathway. A cell model was constructed to detect the effects of POGZ. After POGZ knockdown, OS cell proliferation, invasion and migration were all decreased. Therefore, POGZ is an important gene for evaluating the prognosis of OS patients and is a potential therapeutic target.

Immunohistochemical Characterisation of GLUT1, MMP3 and NRF2 in Osteosarcoma

Osteosarcoma (OSA) is an aggressive bone malignancy. Unlike many other malignancies, OSA outcomes have not improved in recent decades. One challenge to the development of better diagnostic and therapeutic methods for OSA has been the lack of well characterized experimental model systems. Spontaneous OSA in dogs provides a good model for the disease seen in people and also remains an important veterinary clinical challenge. We recently used RNA sequencing and qRT-PCR to provide a detailed molecular characterization of OSA relative to non-malignant bone in dogs. We identified differential mRNA expression of the solute carrier family 2 member 1 (SLC2A1/GLUT1), matrix metallopeptidase 3 (MMP3) and nuclear factor erythroid 2–related factor 2 (NFE2L2/NRF2) genes in canine OSA tissue in comparison to paired non-tumor tissue. Our present work characterizes protein expression of GLUT1, MMP3 and NRF2 using immunohistochemistry. As these proteins affect key processes such as Wnt activation, heme biosynthesis, glucose transport, understanding their expression and the enriched pathways and gene ontologies enables us to further understand the potential molecular pathways and mechanisms involved in OSA. This study further supports spontaneous OSA in dogs as a model system to inform the development of new methods to diagnose and treat OSA in both dogs and people.

Pannexin biology and emerging linkages to cancer

Pannexins are a family of glycoproteins that comprises three members, PANX1, PANX2, and PANX3. The widely expressed and interrogated PANX1 forms heptameric membrane channels that primarily serve to connect the cytoplasm to the extracellular milieu by being selectively permeable to small signaling molecules when activated. Apart from notable exceptions, PANX1 in many tumor cells appears to facilitate tumor growth and metastasis, suggesting that pannexin-blocking therapeutics may have utility in cancer. Attenuation of PANX1 function must also consider the fact that PANX1 is found in stromal cells of the tumor microenvironment (TME), including immune cells. This review highlights the key discoveries of the past 5 years that suggest pannexins facilitate, or in some cases inhibit, tumor cell growth and metastasis via direct protein interactions and through the regulated efflux of signaling molecules.

Collagen XI alpha 1 chain, a potential therapeutic target for cancer

Extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and it is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) has been found to be upregulated in a variety of cancers including ovarian cancer, breast cancer, thyroid cancer, pancreatic cancer, non-small-cell lung cancer, and transitional cell carcinoma of the bladder. High levels of COL11A1 usually predict poor prognosis, while COL11A1 is related to angiogenesis, invasion, and drug resistance of cancer. However, little is known about the specific mechanism by which COL11A1 regulates tumor progression. Here, we have organized and summarized the recent developments regarding elucidation of the relationship between COL11A1 and various cancers, as well as the interaction between COL11A1 and intracellular signaling pathways. In addition, we have selected therapeutic agents targeting COL11A1. All these indicate the possibility of using COL11A1 as a target for cancer treatment.

Scutellaria barbata D.Don and Oldenlandia diffusa (Willd.) Roxb crude extracts inhibit hepatitis-B-virus-associated hepatocellular carcinoma growth through regulating circRNA expression

ETHNOPHARMACOLOGICAL RELEVANCE

Scutellaria barbata D.Don (SB) and Oldenlandia diffusa (Willd.) Roxb are commonly known as Ban Zhi Lian and Bai Hua She Cao in Chinese herbal medicines, respectively. As a pair of herbs, they have traditionally been used as ethnomedicines for clearing away heat and toxins, removing blood stasis, and promoting blood circulation, diuresis, and detumescence.

AIM OF THE STUDY

The aim of the present study was to determine the active ingredients in SB and OD extracts and to investigate whether these extracts can inhibit the growth of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) cell lines (HepG2.2.15 and Hep3B) in vitro and in vivo, as well as to explore their mechanisms of action.

MATERIALS AND METHODS

We determined the levels of total flavonoids, luteolin, and apigenin in SB and OD extracts via ultraviolet-visible spectrophotometry and high-performance liquid chromatography. The effects of SB and OD extracts on HBV-associated HCC cell growth were assessed by HepG2.2.15 and Hep3B cells phenotype and RNA sequencing of Hep3B cells in vitro, and xenograft models in vivo.

RESULTS

The extracts of SB and OD contained total flavonoids. There were active ingredients of luteolin and apigenin in SB, but not in OD. The extracts of SB and OD significantly inhibited HCC growth, migration, invasion, and HBV activity in vitro and in vivo, as well as altered circRNA expression in Hep3B cells. Moreover, we constructed a circRNA-miRNA-mRNA co-expression network.

CONCLUSIONS

The extracts of SB and OD may inhibit HCC cell growth and HBV activity in vitro and in vivo through altering circRNA-miRNA-gene expression and that the efficacies of these extracts may be related to the presence of luteolin and apigenin.

Pannexin 3 channels in health and disease

Pannexin 3 (PANX3) is a member of the pannexin family of single membrane channel-forming glycoproteins. Originally thought to have a limited localization in cartilage, bone, and skin, PANX3 has now been detected in a variety of other tissues including skeletal muscle, mammary glands, the male reproductive tract, the cochlea, blood vessels, small intestines, teeth, and the vomeronasal organ. In many cell types of the musculoskeletal system, such as osteoblasts, chondrocytes, and odontoblasts, PANX3 has been shown to regulate the balance of proliferation and differentiation. PANX3 can be induced during progenitor cell differentiation, functioning at the cell surface as a conduit for ATP and/or in the endoplasmic reticulum as a calcium leak channel. Evidence in osteoblasts and monocytes also highlight a role for PANX3 in purinergic signalling through its function as an ATP release channel. PANX3 is critical in the development and ageing of bone and cartilage, with its levels temporally regulated in other tissues such as skeletal muscle, skin, and the cochlea. In diseases such as osteoarthritis and intervertebral disc degeneration, PANX3 can have either protective or detrimental roles depending on if the disease is age-related or injury-induced. This review will discuss PANX3 function in tissue growth and regeneration, its role in cellular differentiation, and how it becomes dysregulated in disease conditions such as obesity, Duchenne's muscular dystrophy, osteosarcoma, and non-melanoma skin cancer, where most of the findings on PANX3 function can be attributed to the characterization of Panx3 KO mouse models.

Single-cell RNA sequencing of human femoral head in vivo

The homeostasis of bone metabolism depends on the coupling and precise regulation of various types of cells in bone tissue. However, the communication and interaction between bone tissue cells at the single-cell level remains poorly understood. Thus, we performed single-cell RNA sequencing (scRNA-seq) on the primary human femoral head tissue cells (FHTCs). Nine cell types were identified in 26,574 primary human FHTCs, including granulocytes, T cells, monocytes, B cells, red blood cells, osteoblastic lineage cells, endothelial cells, endothelial progenitor cells (EPCs) and plasmacytoid dendritic cells. We identified serine protease 23 (PRSS23) and matrix remodeling associated protein 8 (MXRA8) as novel bone metabolism-related genes. Additionally, we found that several subtypes of monocytes, T cells and B cells were related to bone metabolism. Cell-cell communication analysis showed that collagen, chemokine, transforming growth factor and their ligands have significant roles in the crosstalks between FHTCs. In particular, EPCs communicated with osteoblastic lineage cells closely via the "COL2A1-ITGB1" interaction pair. Collectively, this study provided an initial characterization of the cellular composition of the human FHTCs and the complex crosstalks between them at the single-cell level. It is a unique starting resource for in-depth insights into bone metabolism.

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.

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.

Potential role of m6A RNA methylation regulators in osteosarcoma and its clinical prognostic value

BACKGROUND

Osteosarcoma is a disease with high mortality in children and adolescents, and metastasis is one of the important clinical features of osteosarcoma. N6-Methyladenosine (m6A) is the most abundant methylation modification in mRNA, which is regulated by m6A regulators. It is reported that it is related to the occurrence and development of tumors. However, the mechanism of its action in osteosarcoma is rarely known. The purpose of this study was to identify the potential role of m6A regulatory factor in osteosarcoma and its clinical prognostic value.

METHODS

Here, we used The Cancer Genome Atlas (TCGA) to comprehensively analyze the relationship between m6A regulatory factors and osteosarcoma (metastasis group and non-metastasis group). We analyzed their survival relationship and analyzed all the m6A regulatory factors in TCGA tumor data set by using the univariate Cox proportional hazard regression model. Finally, we selected two survival-related methylation regulators (FTO and IGF2BP2) as risk gene signature.

RESULTS

According to the median risk, patients were divided into low-risk group and high-risk group. Multivariate Cox regression analysis showed that these two risk genes were considered to be the key factors independently predicting the prognosis of patients with osteosarcoma. In addition, we verified their characteristics with gene expression omnibus (GEO) DataSets and confirmed that they are related to tumor and immune-related signaling pathways through gene set enrichment analysis (GESA) and immune infiltration analysis.

CONCLUSIONS

In conclusion, m6A regulators might play an important role in the metastasis of osteosarcoma and have potential important value for the prognosis and treatment strategy of osteosarcoma patients.