TES and SLC40A1 as potential biomarkers for predicting survival in T-cell acute lymphoblastic leukemia.

BACKGROUND:Identifying patients with high-risk T-cell acute lymphoblastic leukemia (T-ALL) is crucial for personalized therapy, however, the lack of robust biomarkers hinders prognosis assessment. To address this issue, our study aimed to screen and validate genes whose expression may serve as predictive indicators of outcomes in T-ALL patients, while also investigating the underlying molecular mechanisms. METHODS:Differentially expressed genes (DEGs) between T-ALL patients and healthy controls were identified by integrating data from three independent public datasets. Functional annotation of these DEGs and protein-protein interaction were also conducted. Further, we enrolled a prospective cohort of T-ALL patients (n=20) at our center, conducting RNA-seq analysis on their bone marrow samples. Survival-based Univariate Cox Analysis was employed to identify gene expressions related to survival, and an intersection algorithm was sequentially applied. Furthermore, we validated the identified genes using cases from the Therapeutically Applicable Research to Generate Effective Treatments database, plotting Kaplan-Meier curves for secondary validation. RESULTS:Through the integration of survival-related genes with DEGs identified in T-ALL, our analysis revealed six T-ALL-specific genes, the expression levels of which were linked to prognostic value. Notably, the independent prognostic value of SLC40A1 and TES expression levels was confirmed in both an external cohort and a prospective cohort at our center. CONCLUSIONS:In summary, our preliminary study indicates that the expression levels of TES and SLC40A1 genes show promise as potential indicators for predicting survival outcomes in T-ALL patients.