Background: Osteosarcoma (OS) is an aggressive bone malignancy with a poor prognosis. Dysregulated calcium homeostasis may contribute to OS progression. Methods: Various machine learning algorithms were integrated into multiple model combinations to identify key prognostic genes. Single-cell expression profiling was conducted to assess STC2 expression across different cell types within the OS microenvironment. Experimental validation was performed in OS cell lines (U2OS and 143B) using lentiviral shRNA-mediated knockdown, qPCR, proliferation assays, and migration/invasion assays. Immune infiltration and potential immunotherapy response were further explored using immune deconvolution, immune checkpoint analysis, TIDE, and SubMap. Results: Calcium homeostasis-related dysregulation was associated with osteosarcoma progression, and machine-learning analysis identified STC2 as the most important prognostic gene. Single-cell analysis revealed that STC2 was predominantly expressed in endothelial, fibroblast, and malignant cells. In vitro experiments showed that knockdown of STC2 in OS cells significantly inhibited cell proliferation, migration, and invasion. Specifically, CCK-8, colony formation, and EdU assays demonstrated decreased cell proliferation, while Transwell assays revealed reduced migratory and invasive capacities of STC2-knockdown OS cells. Moreover, TIDE and SubMap analyses suggested that low STC2 expression was computationally associated with a higher predicted likelihood of response to immune checkpoint inhibitors. Conclusions: Our findings suggest that calcium homeostasis dysregulation is involved in OS progression and that STC2 is a prioritized prognostic and functional candidate within this network. The findings suggest that STC2 may serve as a potential therapeutic target and candidate biomarker for OS, including in the context of predicted immunotherapy response, although this requires further validation.

Malignant tumors, including osteosarcoma (OS), are major non-communicable chronic diseases driven by systemic inflammation and oxidative stress. While dietary tannins possess known antioxidant and anticancer properties, their precise regulatory mechanisms and therapeutic targets in OS remain largely unexplored. This study integrated multi-omics datasets to systematically investigate the potential of dietary tannins in OS, utilizing a machine-learning framework based on 10 algorithms to construct a tannin-related risk (TRR) score. The TRR model demonstrated favorable prognostic performance in retrospective cohorts, with high-TRR patients exhibiting poorer survival, enrichment of extracellular matrix remodeling pathways, and reduced CD8+ T-cell infiltration. Furthermore, immunotherapy prediction tools suggested a lower likelihood of response to immune checkpoint blockade in the high-TRR group. TGFA was identified as a core hub gene contributing to the high-risk phenotype; single-cell and spatial transcriptomic analyses revealed that TGFA-high OS cells exhibit stem-like features and enhanced microenvironmental communication. In vitro assays confirmed that TGFA knockdown suppresses OS cell proliferation and migration while increasing apoptosis, whereas TGFA overexpression promotes these malignant behaviors. By bridging dietary polyphenol research with oncogenic management, this study identifies the TGFA-associated immune axis as a precise molecular roadmap for the structural modification of polyphenols and the design of target-specific, tannin-based functional foods for chronic disease intervention.

Cartilage repair remains challenging due to limited self-healing, poor biocompatibility, and insufficient mechanical properties of current materials. To overcome these issues, we developed a multifunctional composite hydrogel by integrating gelatine methacrylate (GelMA) with magnesium-doped bioactive glass (Mg-BG) and icariin (ICA). SEM analysis revealed that pure GelMA exhibited a highly porous yet loosely organized structure, whereas the addition of Mg-BG and ICA produced a denser, more interconnected porous network that enhances cell adhesion and nutrient diffusion. In vitro, the ICA/Mg-BG/GelMA hydrogel achieved a swelling ratio up to 430% and maintained cell viability above 80% over 5 days. Moreover, qRT-PCR and immunohistochemical analyses demonstrated that the composite hydrogel upregulated chondrogenic markers (SOX9, ACAN, and COL2A1) compared with GelMA alone. Specifically, it downregulates M1 pro-inflammatory markers (CCR7, iNOS, CD86) and upregulates M2 anti-inflammatory markers (ARG1, CD163, CD206), thereby creating a regenerative microenvironment. These results indicate that the synergistic combination of GelMA, Mg-BG, and ICA not only improves the scaffold’s mechanical support but also enhances its biological functionality, offering a promising strategy for cartilage repair. Future studies will focus on in vivo validation to further assess its clinical potential.

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.

Background The present study aims to explore the metastasis-related signatures in connection with tumor microenvironment (TME), revealing new molecular targets promising in improving osteosarcoma (OS) patients’ outcomes. Methods The high-throughput sequencing data was downloaded from the TARGET database and performed the ESTIMATE algorithm. Metastasis-related information was obtained from the GSE21257 dataset. Differentially expressed genes (DEGs) associated with the stromal and immune cell infiltration patterns were identified. DEGs with similar biological functions were grouped into the same module by Gene Ontology (GO) analysis and MCODE analysis. Prognostic DEGs were selected in two datasets through survival analysis. Weighted gene co-expression network analysis (WGCNA) was performed to find metastasis-related modules and genes. RT-PCR was utilized to evaluate the expression of the key prognostic DEGs associated with metastasis in OS patients. Results The median scores of the stromal and immune groups of OS samples were 58 and -416, and a total of 200 overlapping DEGs were identified. These DEGs basically played fundamental roles in immune response relevant GO terms and were clustered into 9 different modules. Among them, 24 metastasis-related DEGs were selected from the GSE21257 dataset which contains the stromal and immune cell infiltration patterns. Finally, IRF8, HLA-DMA, and HLA-DMB were proved to exhibit significant higher expression levels in cancerous tissues than in para-cancerous tissues for OS patients. Conclusion We identified three principal genes as promising signatures for predicting the survival the prognosis of OS patients. Exploration of metastasis-related signatures in TME may be valuable for enhancing treatment strategies for OS.

Background Breast cancer (BC) patients tend to suffer from distant metastasis, especially bone metastasis. Methods All the analysis based on open-accessed data was performed in R software, dependent on multiple algorithms and packages. The RNA levels of specific genes were detected using quantitative Real-time PCR as a method of detecting the RNA levels. To assess the ability of BC cells to proliferate, we utilized the CCK8 test, colony formation, and the 5-Ethynyl-20-deoxyuridine assay. BC cells were evaluated for invasion and migration by using Transwell assays and wound healing assays. Results In our study, we identified the molecules involved in BC bone metastasis based on the data from multiple BC cohorts. Then, we comprehensively investigated the effect pattern and underlying biological role of these molecules. We found that in the identified molecules, the EMP1, ACKR3, ITGA10, MMP13, COL11A1, and THY1 were significantly correlated with patient prognosis and mainly expressed in CAFs. Therefore, we explored the CAFs in the BC microenvironment. Results showed that CAFs could activate multiple carcinogenic pathways and most of these pathways play an important role in cancer metastasis. Meanwhile, we noticed the interaction between CAFs and malignant, endothelial, and M2 macrophage cells. Moreover, we found that CAFs could induce the remodeling of the BC microenvironment and promote the malignant behavior of BC cells. Then, we identified MMP13 for further analysis. It was found that MMP13 can enhance the malignant phenotype of BC cells. Meanwhile, biological enrichment and immune infiltration analysis were conducted to present the effect pattern of MMP13 in BC. Conclusions Our result can improve the understanding of researchers on the underlying mechanisms of BC bone metastasis.

This study was designed to investigate the biological functions of LINC00482 in prostate cancer (PCa) with bone metastasis. TCGA dataset of PCa was applied for LINC00482 expression analysis and real time PCR was used to verify the expression level of LINC00482 in PCa tissues as well as PCa bone metastatic tissues. To detect the biological functions of LINC00482 in vitro, various assays were used including CCK-8, EdU, colony formation and transwell assays. The biological functions of LINC00482 were also identified in vivo by inoculating PCa cells into the left cardiac ventricle of mice, followed by evaluating the osteolytic lesions and osteolytic score. In addition, Starbase and Lncbase databases were applied for predicting the potential target miRNA of LINC00482, while TargetScan and Starbase databases were used for predicting the potential target of miRNA. The luciferase reporter assay was utilized to determine the interactions among these molecules and western blotting was employed to verified the targeted proteins. Results showed that high expression level of LINC00482 was observed in bone metastatic PCa tissues and associated with PCa progression. Silencing of LINC00482 inhibited cell proliferation, migration and invasion in PCa. Furthermore, LINC00482 was proved to act as a competing endogenous RNA by sponging miR-2467-3p to activate Wnt/β-catenin signaling pathway, which may be a promising therapeutic target for PCa with bone metastasis.

BACKGROUND:Bladder urothelial carcinoma (BLCA) is one of the most common urinary system malignancies with a high metastasis rate. Cancer stem cells (CSCs) play an important role in the occurrence and progression of BLCA, however, its roles in bone metastasis and the prognostic stemness biomarkers have not been identified in BLCA.METHOD:In order to identify the roles of CSC in the tumorigenesis, bone metastasis and prognosis of BLCA, the RNA sequencing data of patients with BLCA were retrieved from The Cancer Genome Atlas (TCGA) databases. The mRNA expression-based stemness index (mRNAsi) and the differential expressed genes (DEGs) were evaluated and identified. The associations between mRNAsi and the tumorigenesis, bone metastasis, clinical stage and overall survival (OS) were also established. The key prognostic stemness-related genes (PSRGs) were screened by Lasso regression, and based on them, the predict model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve and the risk score. Additionally, in order to explore the key regulatory network, the relationship among differentially expressing TFs, PSRGs, and absolute quantification of 50 hallmarks of cancer were also identified by Pearson correlation analysis. To verify the identified key TFs and PSRGs, their expression levels were identified by our clinical samples via immunohistochemistry (IHC).RESULTS:A total of 8,647 DEGs were identified between 411 primary BLCAs and 19 normal solid tissue samples. According to the clinical stage, mRNAsi and bone metastasis of BLCA, 2,383 stage-related DEGs, 3,680 stemness-related DEGs and 716 bone metastasis-associated DEGs were uncovered, respectively. Additionally, compared with normal tissue, mRNAsi was significantly upregulated in the primary BLCA and also associated with the prognosis (P = 0.016), bone metastasis (P < 0.001) and AJCC clinical stage (P < 0.001) of BLCA patients. A total of 20 PSRGs were further screened by Lasso regression, and based on them, we constructed the predict model with a relatively high accuracy (AUC: 0.699). Moreover, we found two key TFs (EPO, ARID3A), four key PRSGs (CACNA1E, LINC01356, CGA and SSX3) and five key hallmarks of cancer gene sets (DNA repair, myc targets, E2F targets, mTORC1 signaling and unfolded protein response) in the regulatory network. The tissue microarray of BLCA and BLCA bone metastasis also revealed high expression of the key TFs (EPO, ARID3A) and PRSGs (SSX3) in BLCA.CONCLUSION:Our study identifies mRNAsi as a reliable index in predicting the tumorigenesis, bone metastasis and prognosis of patients with BLCA and provides a well-applied model for predicting the OS for patients with BLCA based on 20 PSRGs. Besides, we also identified the regulatory network between key PSRGs and cancer gene sets in mediating the BLCA bone metastasis.

BackgroundBone metastases (BM) represents a common complication of cancer, patients with BM may experience skeletal complications, such as pathological fractures, spinal cord compression, hypercalcemia, and persisting pain. Currently, there are a large number of publications available on this topic. The purpose of this study was to identify and analyze the 100 most-cited publications on BM research. MethodAll databases from the Web of Science were searched in a three-step approach. First, the 100 most-cited BM studies were identified using only one term “bone metastases” to allow for comprehensive keyword identification. Second, ten keywords identified from the results of the first search were used to conduct a second search of the databases to yield a separate list of the top 100 cited BM publications. Finally, the results of the two searches were overlapped and duplicated articles were removed. After overlapping, the top 100 most-cited articles on BM were selected for further analysis of title, authorship, source journal, publication year, geographic origin, research institution, number of citations, and subspecialty. ResultsThe 100 most-cited articles were published from 1959 to 2014 in 44 different journals and were cited from 250 to 1707 times. The most influential period was from 2001–2010, which produced 50 out of the top 100 publications. A total of 12 countries contributed to the 100 articles, and the United States topped the list with 48 articles. The majority of publications were in Journal of Clinical Oncology , which published 16 articles. In terms of institutional support, a total of 13 institutions each supported at least 2 articles, and the first ranked institution was University of Texas M. D. Anderson Cancer Center (USA) with 8 articles. Regarding subspecialty of the studies, the most frequent studies were “clinical description” with 30 articles, followed by “clinical trial” with 20 articles. ConclusionIn this comprehensive review, we identified and analyzed the 100-most-cited articles on BM research by measuring their citation number, and recognized some of the most important contributions by authors, institutions and countries. Furthermore, our study will help researchers and orthopedic surgeons understand the research trends for BM and as an efficient guide for future BM-related research.