ArticleCancer science2023
Characterization of myeloid signature genes for predicting prognosis and immune landscape in Ewing sarcoma.
Article in Cancer science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Decoding the immune landscape in Ewing sarcoma pathogenesis: The role of tumor infiltrating immune cells and immune milieu.Journal of bone oncology · 2025Review
- Cell-in-cell associated lncRNA signature predicts prognosis and immunotherapy response in gastric cancer.Frontiers in oncology · 2025Article
- Disulfidptosis-associated LncRNA signature predicts prognosis and immune response in kidney renal clear cell carcinoma.Biology direct · 2024Article
- Stratifying osteosarcoma patients using an epigenetic modification-related prognostic signature: implications for immunotherapy and chemotherapy selection.Translational cancer research · 2024Article
- Engagement of CD99 Activates Distinct Programs in Ewing Sarcoma and Macrophages.Cancer immunology research · 2024Article
- Prospects and Advances in Adoptive Natural Killer Cell Therapy for Unmet Therapeutic Needs in Pediatric Bone Sarcomas.International journal of molecular sciences · 2023Review
- Characterization of myeloid signature genes for predicting prognosis and immune landscape in Ewing sarcoma.Cancer science · 2023Article
- Article
- Deciphering the crosstalk of immune dysregulation between COVID-19 and idiopathic inflammatory myopathy.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Myeloid cells as a highly heterogeneous subpopulation of the tumor microenvironment (TME) are intimately associated with tumor development. Ewing sarcoma (EWS) is characterized by abundant myeloid cell infiltration in the TME. However, the correlation between myeloid signature genes (MSGs) and the prognosis of EWS patients was unclear. In this research, we synthetically characterized the expression of MSGs in a training cohort and classified EWS patients into two subtypes. Immune cell infiltration analysis revealed that MSGs subtypes correlated closely with different immune statuses. Furthermore, a three-gene prognostic model (CTSD, SIRPA, and FN1) was constructed by univariate, LASSO, and multivariate Cox analysis, and it showed excellent prognostic accuracy in EWS patients. We also developed a nomogram for better predicting the long-term survival of EWS. Functional enrichment analysis showed immune-related pathways were distinctly different in the high- and low-risk groups. Further analysis revealed that patients in the high-risk group were tightly associated with an immunosuppressive microenvironment. Finally, we validated the expression of these candidate genes by Western blot (WB), qPCR, and immunohistochemistry (IHC) analysis. To sum up, our study identified that the MSGs model was strongly linked to prognostic prediction and immune infiltration in EWS patients, providing novel insights into the clinical treatment and management of EWS patients.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.