Endogenous retroviruses Suppressyn and Syncytin-2 as innovative prognostic biomarkers in Acute Myeloid Leukemia.

Autor: Jiaxin Shen, Xiaofen Wen, Xueyang Xing, Fozza, Claudio, Sechi, Leonardo Antonio
Předmět:
Zdroj: Frontiers in Cellular & Infection Microbiology; 2024, p1-15, 15p
Abstrakt: Introduction: Emerging evidence has proven that human endogenous retroviruses (HERVs) play a critical role in the pathogenesis of Acute Myeloid Leukemia (AML), whereas the specific HERVs influencing the prognosis of AML patients have yet to be fully understood. Methods: In this study, a systematic exploration was achieved to identify potential prognostic HERVs for AML, sourced from TCGA and GTEx database. Differential analysis and functional enrichment studies were conducted using GO, KEGG, GSEA, and GSVA. The ESTIMATE algorithm was applied to explore the immune infiltration of HERVs in AML. A prognostic risk-score model was evaluated with predicted yearly accuracy using ROC analysis. Results: Two HERVs Suppressyn and Syncytin-2, were identified as promising prognostic biomarkers, with high discrimination ability based on ROC analysis between AML and healthy cohorts from TCGA. Their expression was notably higher in AML patients compared to those in healthy individuals but correlates with favorable clinical outcomes in sub-groups such as white race, lower WBC counts, favorable and intermediate risks, and NPM1 or IDH1 mutation. Suppressyn and Syncytin-2 participated in immune-related pathways and exhibited correlations with multiple immune infiltration cells, such as T cells, mast cells, and tumor-associated macrophages. Finally, we developed a prognostic risk-scoring model combining Suppressyn and Syncytin-2, where a high risk-score is associated with better prognosis. Discussion: Collectively, our findings revealed that Suppressyn and Syncytin-2 may act as valuable diagnostic and prognostic biomarkers for individuals with AML, while highlighting links between HERV activation, immunogenicity, and future therapeutic targets. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index