Liquid-liquid phase separation-related gene can predict prognosis and influence immune microenvironment in acute myeloid leukemia.

AIMS: Acute myeloid leukemia (AML) is a hematopoietic malignant tumor whose growth and metastasis have been found to be closely correlated with Liquid-liquid phase separation (LLPS); however, the molecular mechanisms underlying and the immunological value of LLPS in AML have not been reported.

METHODS

In this study, we aimed to develop a precise prognostic risk model based on LLPS-associated key genes in AML. We analyzed differentially expressed genes from AML versus control samples (GSE9476), intersected these with LLPS genes to identify differentially expressed LLPS-related genes, and used univariate Cox regression to find those linked to prognosis. Candidate genes were identified by overlapping prognostic differentially expressed LLPS-related genes with inter-subtype differentially expressed genes.

RESULTS

We used the least absolute selection and shrinkage operator to pinpoint three key genes-SLC4A1, SCRN1, and HOPX-for the prognostic risk model, which proved effective in assessing AML prognosis. A nomogram incorporating risk score, age, and AML risk category was developed showing promising potential for clinical utility. Immune analysis revealed variations in certain immune cells across risk groups. Drug sensitivity tests highlighted significant differences in the efficacy of several drugs among these groups.

CONCLUSION

This model integrating the three key genes offers a novel insight into AML prognosis prediction.