Characterization of myeloid signature genes for predicting prognosis and immune landscape in Ewing sarcoma. Issue 4 (19th December 2022)
- Record Type:
- Journal Article
- Title:
- Characterization of myeloid signature genes for predicting prognosis and immune landscape in Ewing sarcoma. Issue 4 (19th December 2022)
- Main Title:
- Characterization of myeloid signature genes for predicting prognosis and immune landscape in Ewing sarcoma
- Authors:
- Zhang, Zhao
Shi, Yubo
Zhu, Zhijie
Fu, Jun
Liu, Dong
Liu, Xincheng
Dang, Jingyi
Tao, Huiren
Fan, Hongbin - Abstract:
- 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. Abstract :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. Abstract : Myeloid cell signature can predict the prognostic accuracy and immune infiltration in Ewing sarcoma patients … (more)
- Is Part Of:
- Cancer science. Volume 114:Issue 4(2023)
- Journal:
- Cancer science
- Issue:
- Volume 114:Issue 4(2023)
- Issue Display:
- Volume 114, Issue 4 (2023)
- Year:
- 2023
- Volume:
- 114
- Issue:
- 4
- Issue Sort Value:
- 2023-0114-0004-0000
- Page Start:
- 1240
- Page End:
- 1255
- Publication Date:
- 2022-12-19
- Subjects:
- Ewing sarcoma -- immune infiltration -- myeloid cell -- nomogram -- prognostic prediction
Cancer -- Periodicals
Neoplasms -- Periodicals
Research -- Periodicals
Electronic journals
616.994005 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=1347-9032;screen=info;ECOIP ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1349-7006 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/cas.15688 ↗
- Languages:
- English
- ISSNs:
- 1347-9032
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3046.603000
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- 26823.xml