Decoding the genetic symphony: Profiling protein-coding and long noncoding RNA expression in T-acute lymphoblastic leukemia for clinical insights.
PNAS Nexus
; 3(2): pgae011, 2024 Feb.
Article
en En
| MEDLINE
| ID: mdl-38328782
ABSTRACT
T-acute lymphoblastic leukemia (T-ALL) is a heterogeneous malignancy characterized by the abnormal proliferation of immature T-cell precursors. Despite advances in immunophenotypic classification, understanding the molecular landscape and its impact on patient prognosis remains challenging. In this study, we conducted comprehensive RNA sequencing in a cohort of 35 patients with T-ALL to unravel the intricate transcriptomic profile. Subsequently, we validated the prognostic relevance of 23 targets, encompassing (i) protein-coding genes-BAALC, HHEX, MEF2C, FAT1, LYL1, LMO2, LYN, and TAL1; (ii) epigenetic modifiers-DOT1L, EP300, EML4, RAG1, EZH2, and KDM6A; and (iii) long noncoding RNAs (lncRNAs)-XIST, PCAT18, PCAT14, LINC00202, LINC00461, LINC00648, ST20, MEF2C-AS1, and MALAT1 in an independent cohort of 99 patients with T-ALL. Principal component analysis revealed distinct clusters aligning with immunophenotypic subtypes, providing insights into the molecular heterogeneity of T-ALL. The identified signature genes exhibited associations with clinicopathologic features. Survival analysis uncovered several independent predictors of patient outcomes. Higher expression of MEF2C, BAALC, HHEX, and LYL1 genes emerged as robust indicators of poor overall survival (OS), event-free survival (EFS), and relapse-free survival (RFS). Higher LMO2 expression was correlated with adverse EFS and RFS outcomes. Intriguingly, increased expression of lncRNA ST20 coupled with RAG1 demonstrated a favorable prognostic impact on OS, EFS, and RFS. Conclusively, several hitherto unreported associations of gene expression patterns with clinicopathologic features and prognosis were identified, which may help understand T-ALL's molecular pathogenesis and provide prognostic markers.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
PNAS Nexus
Año:
2024
Tipo del documento:
Article
País de afiliación:
India