A Nutritional Metabolism Related Prognostic Scoring System for Patients With Newly Diagnosed Osteosarcoma

Unveiling the prognostic implications of RPLP1 upregulation in osteosarcoma

Osteosarcoma, a malignant bone tumor characterized by a high rate of metastasis and poor survival, presents a critical need for identifying novel biomarkers associated with metastasis. In this study, we conducted an extensive analysis utilizing transcriptional and clinical data sourced from databases such as GEO, TCGA, CCLE, R2, and Xena. And we discovered that Ribosomal protein LP1 (RPLP1) ranked among the top upregulated genes in relation to osteosarcoma metastasis. Notably, RPLP1 exhibited significant expression in both osteosarcoma cell lines and patient samples. Moreover, multiple osteosarcoma studies revealed a strong correlation between RPLP1 overexpression and worse metastasis-free survival as well as overall survival. Additionally, we observed a consistent association between dysregulation of RPLP1 and reduced overall survival across various tumor types. Knocking down of RPLP1 led to the down-regulation of MYL5 and functional enrichment toward cell cycle and cellular interaction. Based on these findings, we propose that RPLP1 has the potential to serve as a prognostic biomarker, indicating increased metastasis and worse survival outcomes in osteosarcoma. These insights contribute to a better understanding of the disease and may pave the way for future research and therapeutic approaches.

Molecular mechanisms of osteosarcoma metastasis and possible treatment opportunities

In osteosarcoma patients, metastasis of the primary cancer is the leading cause of death. At present, management options to prevent metastasis are limited and non-curative. In this study, we review the current state of knowledge on the molecular mechanisms of metastasis and discuss promising new therapies to combat osteosarcoma metastasis. Genomic and epigenomic changes, metabolic reprogramming, transcription factors, dysregulation of physiologic pathways, and alterations to the tumor microenvironment are some of the changes reportedly involved in the regulation of osteosarcoma metastasis. Key factors within the tumor microenvironment include infiltrating lymphocytes, macrophages, cancer-associated fibroblasts, platelets, and extracellular components such as vesicles, proteins, and other secreted molecules. We conclude by discussing potential osteosarcoma-limiting agents and their clinical studies.

N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma

N1-methyladenosine methylation (m1A), as an important RNA methylation modification, regulates the development of many tumours. Metabolic reprogramming is one of the important features of tumour cells, and it plays a crucial role in tumour development and metastasis. The role of RNA methylation and metabolic reprogramming in osteosarcoma has been widely reported. However, the potential roles and mechanisms of m1A-related metabolic genes (MRmetabolism) in osteosarcoma have not been currently described. All of MRmetabolism were screened, then selected two MRmetabolism by least absolute shrinkage and selection operator and multifactorial regression analysis to construct a prognostic signature. Patients were divided into high-risk and low-risk groups based on the median riskscore of all patients. After randomizing patients into train and test cohorts, the reliability of the prognostic signature was validated in the whole, train and test cohort, respectively. Subsequently, based on the expression profiles of the two MRmetabolism, we performed consensus clustering to classify patients into two clusters. In addition, we explored the immune infiltration status of different risk groups and different clusters by CIBERSORT and single sample gene set enrichment analysis. Also, to better guide individualized treatment, we analyzed the immune checkpoint expression differences and drug sensitivity in the different risk groups and clusters. In conclusion, we constructed a MRmetabolism prognostic signature, which may help to assess patient prognosis, immunotherapy response.