Characterization of myeloid signature genes for predicting prognosis and immune landscape in Ewing sarcoma

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.

Downregulated annexin A1 expression correlates with poor prognosis, metastasis, and immunosuppressive microenvironment in Ewing’s sarcoma

“…The tumor microenvironment (TME) plays a key role in tumor and developmental processes and therapeutic susceptibility, and the typical immune profile of ES is a large infiltration of myeloid cells in the TME [ 34 , 35 ]. Myeloid-derived suppressor cells (MDSCs) are involved in a variety of immunosuppressive responses as immature monocytes and granulocytes, and Zhang et al [ 36 ] identified a subpopulation of MDSCs with significant immunosuppressive effects.…”

Deciphering the crosstalk of immune dysregulation between COVID-19 and idiopathic inflammatory myopathy

“…M1 macrophages are generally polarized by interferon-gamma, secrete large amounts of pro-inflammatory factors, and play an essential role in the early stages of inflammation. M2 macrophage express suppressive inflammatory factors that inhibit the inflammatory response and tissue repair ( 34 , 35 ). Watson et al.…”

“…M1 macrophages are generally polarized by interferon-gamma, secrete large amounts of pro-inflammatory factors, and play an essential role in the early stages of inflammation. M2 macrophage express suppressive inflammatory factors that inhibit the inflammatory response and tissue repair (34,35). Watson et al (69) showed that M1 macrophage were essential mediators of virus-induced myopathy and that blocking SHP-1 activation in macrophages could prevent virus-induced myofiber degeneration.…”

“…To identify key biomarkers for the occurrence of COVID-19 related IIM, we used two machine learning methods for screening (LASSO and Random forest) (32)(33)(34)(35). LASSO was performed by R package "glmnet," and the minimum lamba value was set as the threshold.…”

Blood transcriptome and machine learning identified the crosstalk between COVID-19 and fibromyalgia: a preliminary study

“…Given the large absolute number of survivors of the pandemic in these years, there are increasing reports of long COVID (21). Bioinformatics analysis as an emerging technology can integrate and analyse biological data to facilitate the researcher to understand better the common mechanism between different illnesses and make effective countermeasures (22)(23)(24). For example,…”