Somatic mutation-associated risk index based on lncRNA expression for predicting prognosis in acute myeloid leukemia.
Qiang XuTao GuoPublished in: Hematology (Amsterdam, Netherlands) (2022)
Objectives: Genomic instability has several implications for acute myeloid leukemia (AML) prognosis. This article aims to construct a somatic mutation-associated risk index (SMRI) of genomic instability for AML to predict prognosis and explore the potential determinants of AML prognosis. Methods: We obtained differentially expressed lncRNAs from genomic instability subtypes and selected six lncRNAs to construct the SMRI through multivariate Cox regression analysis. The median SMRI classified patients into high and low SMRI groups. Kaplan-Meier survival analysis was used to clarify the prognostic differences of SMRI subtypes. Receiver operating characteristic curve analysis was performed to elucidate the value of SMRI as a prognostic indicator. Gene set variation analysis, tumor mutation burden (TMB) analysis, immune infiltration, and immune checkpoint expression analysis were performed to investigate possible causes for the differences in prognosis of SMRI subtypes. Results: The high SMRI group exhibited a poor prognosis, which was characterized by elevated levels of TMB, mutation counts (TP53, NPM1, DNMT3A, and FLT3-TKD), CD8 + T cell infiltration, and immune checkpoint (PD-1, PD-L2, CTLA4, LAG3) expression. The SMRI was still associated with prognosis, even after adjustment for age, sex, cytogenetic risk, DNMT3A status, FLT3 status, and NPM1 status. Gene set variation analysis showed that AML with FLT3-ITD mutation, CEBPA mutation, and LSCs (leukemia stem cells) were enriched in the high SMRI group. Conclusion: Our research suggests that the SMRI derived from genomic instability subtypes is a useful biomarker for predicting prognosis and may be beneficial for improving the clinical outcome of patients with AML.
Keyphrases
- acute myeloid leukemia
- poor prognosis
- stem cells
- copy number
- allogeneic hematopoietic stem cell transplantation
- long non coding rna
- dna methylation
- end stage renal disease
- gene expression
- chronic kidney disease
- bone marrow
- prognostic factors
- ejection fraction
- transcription factor
- tyrosine kinase
- cell therapy
- genome wide identification
- data analysis
- climate change