Research progress in the mechanism and treatment of osteosarcoma

Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning

Early and accurate diagnosis of osteosarcomas (OS) is of great clinical significance, and machine learning (ML) based methods are increasingly adopted. However, current ML-based methods for osteosarcoma diagnosis consider only X-ray images, usually fail to generalize to new cases, and lack explainability. In this paper, we seek to explore the capability of deep learning models in diagnosing primary OS, with higher accuracy, explainability, and generality. Concretely, we analyze the added value of integrating the biochemical data, i.e., alkaline phosphatase (ALP) and lactate dehydrogenase (LDH), and design a model that incorporates the numerical features of ALP and LDH and the visual features of X-ray imaging through a late fusion approach in the feature space. We evaluate this model on real-world clinic data with 848 patients aged from 4 to 81. The experimental results reveal the effectiveness of incorporating ALP and LDH simultaneously in a late fusion approach, with the accuracy of the considered 2608 cases increased to 97.17%, compared to 94.35% in the baseline. Grad-CAM visualizations consistent with orthopedic specialists further justified the model's explainability.

Bone and Extracellular Signal-Related Kinase 5 (ERK5)

Bones are vital for anchoring muscles, tendons, and ligaments, serving as a fundamental element of the human skeletal structure. However, our understanding of bone development mechanisms and the maintenance of bone homeostasis is still limited. Extracellular signal-related kinase 5 (ERK5), a recently identified member of the mitogen-activated protein kinase (MAPK) family, plays a critical role in the pathogenesis and progression of various diseases, especially neoplasms. Recent studies have highlighted ERK5's significant role in both bone development and bone-associated pathologies. This review offers a detailed examination of the latest research on ERK5 in different tissues and diseases, with a particular focus on its implications for bone health. It also examines therapeutic strategies and future research avenues targeting ERK5.

Single-cell aggrephagy-related patterns facilitate tumor microenvironment intercellular communication, influencing osteosarcoma progression and prognosis

Osteosarcoma, a common malignant tumor in children, has emerged as a major threat to the life and health of pediatric patients. Presently, there are certain limitations in the diagnosis and treatment methods for this disease, resulting in inferior therapeutic outcomes. Therefore, it is of great importance to study its pathogenesis and explore innovative approaches to diagnosis and treatment. In this study, a non-negative matrix decomposition method was employed to conduct a comprehensive investigation and analysis of aggregated autophagy-related genes within 331,394 single-cell samples of osteosarcoma. Through this study, we have elucidated the intricate communication patterns among various cells within the tumor microenvironment. Based on the classification of aggregated autophagy-related genes, we are not only able to more accurately predict patients' prognosis but also offer robust guidance for treatment strategies. The findings of this study hold promise for breakthroughs in the diagnosis and treatment of osteosarcoma, intervention of aggrephagy is expected to improve the survival rate and quality of life of osteosarcoma patients.

What role does GPR65 play in the progression of osteosarcoma? Its mechanism and clinical significance

BACKGROUND

GPR65 is a pH-sensing G-protein-coupled receptor that acts as a key innate immune checkpoint in the human tumor microenvironment, inhibiting the release of inflammatory factors and inducing significant upregulation of tissue repair genes. However, the expression pattern and function of GPR65 in osteosarcoma (OS) remain unclear. The purpose of this study was to investigate and elucidate the role of GPR65 in the microenvironment, proliferation and migration of OS.

METHODS

Retrospective RNA-seq data analysis was conducted in a cohort of 97 patients with OS data in the TAEGET database. In addition, single-cell sequencing data from six surgical specimens of human OS patients was used to analyze the molecular evolution process during OS genesis. Tissues chips and bioinformatics results were used to verify GPR65 expression level in OS. MTT, colony formation, EdU assay, wound healing, transwell assay and F-actin assay were utilized to analyze cell proliferation and invasion of OS cancer cells. RNA-seq was used to explore the potential mechanism of GPR65's role in OS.

RESULTS

GPR65 expression was significantly low in OS, and subgroup analysis found that younger OS patients, OS patients in metastatic status, and overall survival and progression free survival OS patients had lower GPR65 expression. From ScRNA-seq data of GSE162454, we found the expression of GPR65 is significantly positively correlated with CD4 + T cells CD8 + T cells and OS related macrophage infiltration. Verification experiment found that silencing the expression of GPR65 in osteosarcoma cells U2OS and HOS could promote the proliferation and invasion process, RNA-seq results showed that the role of GPR65 in OS cells was related to immune system, metabolism and signal transduction.

CONCLUSION

The low expression of GPR65 in OS leads to high metastasis rate and poor prognosis in OS patients. The suppression of immune escape and inhibition of proliferation may be a key pathway for GPR65 to participate in the progression of OS. The current study strengthens the role of GPR65 in OS development and provides a potential biomarker for the prognosis of OS patients.