Endoplasmic reticulum stress-related signature predicts prognosis and immune infiltration analysis in acute myeloid leukemia

Objectives To construct an endoplasmic reticulum stress-related prognostic risk score (RS) model to predict prognosis and perform a preliminary analysis of immune infiltration in patients with acute myeloid leukemia (AML). Methods The whole-genome expression data for AML and endoplasmic reticulum stress (ER stress)-related genes were downloaded from the GEO and GSEA databases, respectively. The samples were divided into death and survival groups, combined with clinical prognosis information. LASSO regression was used to construct a prognostic RS model. The Kaplan-Meier curve method was used to evaluate the association between different risk groups and actual survival prognosis information. A cox regression analysis was used to screen for independent survival prognostic clinical factors and construct a nomogram. CIBERSORT and ssGSEA was used for immune-related analysis. Results Eighteen ER-stress related genes were identified and a comprehensive network was constructed. Further, 5 CC, 8 MF, 17 BP, and 2 KEGG pathways were enriched. Ten optimal DEGs were obtained and a prognostic risk model was constructed. Compared to the low RS group, the OS values of the high RS group were significantly lower. A significant correlation between the different risk groups and the actual prognosis was demonstrated. Ten immune cells with significantly different distributions in different risk groups were screened. KEGG enrichment analysis showed that there were 5 signaling pathways in the high-risk group. Conclusions The RS model can effectively predict the prognosis and has clinical implications for the prognosis of AML, combined with the correlation between different RS groups and the immune microenvironment.

Automated summary

This study constructed an endoplasmic reticulum stress-related prognostic risk score (RS) model to predict prognosis and performed a preliminary analysis of immune infiltration in acute myeloid leukemia (AML) patients. The RS model effectively predicted prognosis and had clinical implications for AML prognosis, combined with the correlation between different RS groups and the immune microenvironment. The study identified genes and pathways related to ER stress and demonstrated that immune cells have significantly different distributions in different risk groups.