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A Novel Ferroptosis-Related Gene Signature for Prognosis Prediction in Ewing Sarcoma. | LitMetric

AI Article Synopsis

  • Ferroptosis is a unique form of programmed cell death that impacts tumor growth and cancer treatments, particularly in Ewing sarcoma (ES), where a study identified 148 differentially expressed ferroptosis-related genes (FRGs) between normal and cancerous tissues.
  • Significant signaling pathways related to cancer and immune responses were highlighted through GO and KEGG analyses of these DEFRGs.
  • The study identified three key genes (AURKA, RGS4, and RIPK1) that not only predict patient prognosis and treatment response but also may serve as potential targets for therapy, ultimately leading to the development of a nomogram for clinicians to estimate survival in ES patients.

Article Abstract

Ferroptosis, as a form of programmed cell death independent of apoptosis, has been demonstrated that plays a major role in tumorigenesis and cancer treatment. A comprehensive analysis of ferroptosis-related genes (FRGs) may lead to a novel choice for the treatment of Ewing sarcoma (ES). Here, 148 differentially expressed FRGs (DEFRGs) were identified between normal and ES tissue. And the GO and KEGG analyses of DEFRGs indicated that these genes were enriched in cancer and immune-related signaling pathways. Then, the GSE17679 cohort was randomly divided into train and test cohorts. Based on the train cohort, AURKA, RGS4, and RIPK1 were identified as key genes through the univariate Cox regression analysis, the random survival forest algorithm, and the multivariate Cox regression analysis and utilized to establish a prognostic FRG signature. The validation results demonstrated that the gene signature has not only excellent prediction performance and generalization ability but is also good at predicting the response of immunotherapy and chemotherapy. Subsequent analysis indicated that all 3 key genes play key roles in tumor immunity and prognosis of ES. Of these, AURKA was highly associated with EWSR1, which was verified by a single-cell dataset (GSE130019). Therefore, the 3 genes may be potential therapeutic targets for ES. At the end of this study, we also constructed an accurate nomogram that helps clinicians to assess the survival time of ES patients. In conclusion, our study constructed an excellent gene signature, which is helpful in improving the prognosis of ES patients.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425108PMC
http://dx.doi.org/10.1155/2022/6711629DOI Listing

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