Background. Despite tremendous advances in treating osteosarcoma (OS), the survival rates of patients have failed to improve dramatically over the past decades. Ferroptosis, a newly discovered iron-dependent type of regulated cell death, is implicated in tumors, and its features in OS remain unascertained. We designed to determine the involvement of ferroptosis subcluster-related modular genes in OS progression and prognosis. Methods. The OS-related datasets retrieved from GEO and TARGET database were clustered for identifying molecular subclusters with different ferroptosis-related genes (FRGs) expression patterns. Weighted gene coexpression network analysis (WGCNA) was applied to identify modular genes from FRG subclusters. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariable Cox regression analysis were adopted to develop the prognostic model. Potential mechanisms of development and prognosis in OS were explored by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Then, a comprehensive analysis was conducted for immune checkpoint markers and assessment of predictive power to drug response. The protein expression levels of the three ferroptosis subcluster-related modular genes were verified by immunohistochemistry. Results. Two independent subclusters presenting diverse expression profiles of FRGs were obtained, with significantly different survival states. Ferroptosis subcluster-related modular genes were screened with WGCNA, and the GESA results showed that ferroptosis subcluster-related modular genes could affect the cellular energy metabolism, thus influencing the development and prognosis of osteosarcoma. A prognostic model was established by incorporating three ferroptosis subcluster-related modular genes (LRRC1, ACO2, and CTNNBIP1) and a nomogram by integrating clinical features, and they were evaluated for the predictive power on OS prognosis. The 20 immune checkpoint-related genes confirmed the insensitivity to tumor immunotherapy in high-risk patients. IC50s of Axitinib and Cytarabine suggested a higher sensitivity to the targeted drug. Finally, the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemistry were consistent with bioinformatics analysis. Conclusion. Ferroptosis are closely associated with the OS prognosis. The risk-scoring model incorporating three ferroptosis subcluster-related modular genes has shown outstanding advantages in predicting patient prognosis.

Background. Soft tissue sarcomas (STS) are rare malignancies arising from mesenchymal tissue and interlacing ectodermal nerve tissue. Immunotherapy plays an important role in the prognosis and survival of STS patients. However, there is insufficient evidence to confirm the prognostic value of m6A-related genes and to evaluate the efficacy of immunotherapy for STS. Methods. We analyzed 23 m6A regulators from STS samples using R software and defined the modification patterns for three STS m6A regulators. Then, we constructed the m6A scores and divided the samples into high and low subgroups. Finally, we used data from the GEO database to verify the results. Results. We found that the m6A clusters differed in the overall survival (OS), progression-free survival (PFS), and immune infiltration rate. Additionally, the m6A score was positively correlated with the contents of activated B cells, activated dendritic cells, CD56 bright natural killer cells, helper T cells, and regulatory T cells. The group with a higher m6A score also presented higher OS and PFS rates. Regarding immunotherapy, STS patients with a high m6A score presented better results. Consistently, we found similar results in another dataset with patients that received anti-PD-1/PD-L1 therapy. Conclusion. Our current results indicated that the m6A score can be used to assess the survival rate of STS patients and guide immunotherapy and predict its effects. The analysis of different m6A patterns of STS samples contributed to the understanding of the diversity and complexity of the tumor microenvironment (TME) and provided new ideas for the clinical development of personalized immunotherapy and prediction of the prognosis of STS patients.

Objective Protein kinase C-delta (PKC-δ) is involved in apoptosis. This study aimed to establish whether PKC-δ can further promote IL-1β-induced chondrocyte apoptosis by mediating the phosphorylation of the JNK and p38 mitogen-activated protein kinase (MAPK) signaling pathways In osteoarthritis (OA). Methods We employed chondrocyte staining to determine the extent of cartilage degeneration. PKC-δ and p38 signal expressions were used in the immunohistochemical (IHC) test and apoptosis was assayed at the TUNEL test in human osteoarthritic and controls. We stimulated rat cartilage cells using IL-1β (10 ng/ml)/rottlerin (10 μM) or lentivirus. To determine the apoptosis rate, we employed flow cytometry. The mRNA of both BCL2-related X (BAX) and cysteine aspartate protease 3 (caspase-3) could be measured via qRT-PCR. Western blot measured the protein levels of BAX, caspase-3, PKC-δ, p-JNK/JNK and p-p38/p38. Results The positive rate of PKC-δ and the apoptotic rate of chondrocytes in OA were higher than controls. The manifestation of PKC-δ was positively related to the degree of cartilage degeneration, p38 protein expression, and apoptosis rate. IL-1β exposure upregulated PKC-δ expression in chondrocytes in a dose-dependent manner. Decreasing PKC-δ expression and its phosphorylation in OA can inhibit MAPK signaling pathway activation (phosphorylation) by downregulating JNK and p38 protein phosphorylation and expression. This inhibition decreases caspase-3 and BAX levels, consequently lowering the apoptosis rate in chondrocytes. Conclusion PKC-δ activation by IL-1β in OA promotes chondrocyte apoptosis via activation of the JNK and p38 MAPK signal pathways, thereby promoting the OA progression.