A Novel Glutamine Metabolism-Related Gene Signature in Prognostic Prediction of Osteosarcoma

Global research trends and hotspots in metabolomics of osteosarcoma: a decade-spanning bibliometric and visualized analysis

Object

Osteosarcoma is a malignant tumor originating from the bones, commonly found in children and adolescents, especially in rapidly growing bone areas such as the knees and upper arms. In this study, we aim to delineate the evolution and convergence of research themes in osteosarcoma metabolomics over the past decade, identify major contributors, and forecast emerging trends that could direct future research efforts.

Method

The bibliometric method has been applied to systematically analyze the literature in the field of osteosarcoma metabolomics. The relevant literatures were collected from the Web of Science Core Collection, spanning from January 1, 2014, to December 31, 2023. Tools such as CiteSpace, Bibliometrix, and VOSviewer were used for the visual analysis of the collected literatures. The focused information includes institutions, journals, countries, authors, keywords, and citations.

Result

Various aspects in the field of osteosarcoma metabolism were analyzed. Shanghai Jiao Tong University has published the most papers in the past ten years, followed by Central South University and Zhejiang University. Among the sources, the international journal of molecular sciences publishes the most articles, and oncotarget is the journal with the highest H index. According to Bradford's law, there are 34 core journals identified. A total of 5501 authors participated in the creation of papers in this field. The distribution of authors follows Lotka`s Law, and 85.3% of authors have only one article. 46% of the corresponding authors are from China, but most of these corresponding authors are not good at international cooperation. China also has the largest number of publications, followed by the United States. It can be confirmed that China dominates this field. Among the keywords, "expression" is the keyword that has received the most attention in the past ten years. All keywords can be divided into 9 clusters. Based on the explosive words and hot topics each year, we speculate that future research will focus on the tumor microenvironment, molecular mechanisms and autophagy, targeted therapies and inhibitors.

Conclusion

In summary, this study comprehensively analyzed the current state of research in the field of osteosarcoma metabolism through bibliometric methods. The findings revealed the development trends and research hotspots in this field, which may provide valuable references for future research directions.

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

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.

Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma

Amino acid metabolization is verified to be a part in the progression of cancer. However, genes related to the amino acid metabolism have not been identified in colon adenocarcinoma (COAD). A systematic prognostic model of COAD becomes a pressing need. Among genes related to the amino acid metabolism, RIMKLB, ASPG, TH, MTAP, AZIN2, PSMB2, HDC, ACMSD, and PSMA8 were identified to construct a risk model. Kaplan–Meier (K–M) analyses demonstrated that the high-risk group achieved a poor prognosis. Area under the respective ROC (AUC) values indicated the robustness of the model. To highlight its clinical value, multivariate Cox was used to obtain the optimal variables to construct a nomogram. A higher tumor mutation burden was observed in the high-risk group. However, the low-risk group had a stronger immune infiltration. Seven molecular subtypes were found by consensus cluster. Twenty-two hub genes were identified related to the ESTIMATE score using WGCNA. In brief, our research constructed a stable prognostic model related to the amino acid metabolism in COAD, revealing its connection to the immune microenvironment. The model guided the outcome of COAD and the direction of immunotherapy.