Gankyrin activates the hedgehog signalling to drive metastasis in osteosarcoma

The OSR9 Regimen: A New Augmentation Strategy for Osteosarcoma Treatment Using Nine Older Drugs from General Medicine to Inhibit Growth Drive

As things stand in 2023, metastatic osteosarcoma commonly results in death. There has been little treatment progress in recent decades. To redress the poor prognosis of metastatic osteosarcoma, the present regimen, OSR9, uses nine already marketed drugs as adjuncts to current treatments. The nine drugs in OSR9 are: (1) the antinausea drug aprepitant, (2) the analgesic drug celecoxib, (3) the anti-malaria drug chloroquine, (4) the antibiotic dapsone, (5) the alcoholism treatment drug disulfiram, (6) the antifungal drug itraconazole, (7) the diabetes treatment drug linagliptin, (8) the hypertension drug propranolol, and (9) the psychiatric drug quetiapine. Although none are traditionally used to treat cancer, all nine have attributes that have been shown to inhibit growth-promoting physiological systems active in osteosarcoma. In their general medicinal uses, all nine drugs in OSR9 have low side-effect risks. The current paper reviews the collected data supporting the role of OSR9.

Research progress in the mechanism and treatment of osteosarcoma

ABSTRACT

Osteosarcoma (OS) is the most common primary malignant bone tumor that more commonly occurs in children and adolescents. The most commonly used treatment for OS is surgery combined with chemotherapy, but the treatment outcomes are typically unsatisfactory. High rates of metastasis and post-treatment recurrence rates are major challenges in the treatment of OS. This underlines the need for studying the in-depth characterization of the pathogenetic mechanisms of OS and development of more effective therapeutic modalities. Previous studies have demonstrated the important role of the bone microenvironment and the regulation of signaling pathways in the occurrence and development of OS. In this review, we discussed the available evidence pertaining to the mechanisms of OS development and identified therapeutic targets for OS. We also summarized the available treatment modalities for OS and identified future priorities for therapeutics research.

A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma

Background

Anoikis resistance is a prerequisite for the successful development of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes (ARGs) correlates with OS prognosis remains unclear. This study aimed to investigate the feasibility of using ARGs as prognostic tools for the risk stratification of OS.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided transcriptome information relevant to OS. The GeneCards database was used to identify ARGs. Differentially expressed ARGs (DEARGs) were identified by overlapping ARGs with common differentially expressed genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and GSE99671 datasets. Anoikis-related clusters of patients were obtained by consistent clustering, and gene set variation analysis (GSVA) of the different clusters was completed. Next, a risk model was created using Cox regression analyses. Risk scores and clinical features were assessed for independent prognostic values, and a nomogram model was constructed. Subsequently, a functional enrichment analysis of the high- and low-risk groups was performed. In addition, the immunological characteristics of OS samples were compared between the high- and low-risk groups, and their sensitivity to therapeutic agents was explored.

Results

Seven DEARGs between OS and normal samples were obtained by intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly differentially expressed between both clusters (P<0.05) and were identified as prognosis-related genes. The risk model showed that the risk score and tumor metastasis were independent prognostic factors of patients with OS. A nomogram combining risk score and tumor metastasis effectively predicted the prognosis. In addition, patients in the high-risk group had low immune scores and high tumor purity. The levels of immune cell infiltration, expression of human leukocyte antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower in the high-risk group than those in the low-risk group. The low-risk group was sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group exhibited lower inhibitory concentration values by 50% for 24 drugs, including AG.014699, AMG.706, and AZD6482.

Conclusion

The prognostic stratification framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead to more efficient clinical management.

Gankyrin activates the hedgehog signalling to drive metastasis in osteosarcoma

Gankyrin is a regulatory subunit of the 26-kD proteasome complex and promotes the occurrence and progression of many malignancies. However, the role of gankyrin in osteosarcoma (OS) metastasis remains unclear. Hedgehog signalling has been shown to regulate stem cell homeostasis and cancer metastasis, but the mechanisms that activate this pathway in OS are still poorly understood. Here, a series of in vitro and in vivo assays were carried out to explore the function and mechanism of gankyrin regulating Hedgehog signalling in OS. We demonstrated that gankyrin promotes migration, invasion and regulates the expression of some stemness factors by up-regulating Gli1 in OS. Importantly, our data showed an interaction between gankyrin and Gli1. Moreover, gankyrin suppresses the ubiquitin-mediated degradation of Gli1 protein in OS. Gankyrin also significantly promotes the lung metastasis of OS in vivo. Our findings suggest that gankyrin drives metastasis and regulates the expression of some stemness factors in osteosarcoma by activating Hedgehog signalling, indicating that drug screening for compounds targeting gankyrin may contribute to the development of novel and effective therapies for OS.