Immunophenotypic clustering in paediatric acute myeloid leukaemia.
Hui LiuKefei WuWenting HuXiaoxiao ChenYanjing TangYani MaChangcheng ChenYangyang XieLisha YuJun HuangShuhong ShenXiang WangPublished in: British journal of haematology (2024)
Acute myeloid leukaemia (AML) is a highly heterogeneous disease, exhibiting diverse subtypes according to the characteristics of tumour cells. The immunophenotype is one of the aspects acquired routinely through flow cytometry in the diagnosis of AML. Here, we characterized the antigen expression in paediatric AML cases across both morphological and molecular genetic subgroups. We discovered a subgroup of patients with unfavourable prognosis that can be immunologically characterized, irrespective of morphological FAB results or genetic aberrations. Cox regression analysis unveiled key antigens influencing the prognosis of AML patients. In terms of underlying genotypes, we observed that the antigenic profiles and outcomes of one specific group, primarily composed of CBFA2T3::GLIS2 and FUS::ERG, were analogous to the reported RAM phenotype. Overall, our data highlight the significance of immunophenotype to tailor treatment for paediatric AML.
Keyphrases
- acute myeloid leukemia
- allogeneic hematopoietic stem cell transplantation
- flow cytometry
- intensive care unit
- liver failure
- emergency department
- end stage renal disease
- dendritic cells
- copy number
- induced apoptosis
- respiratory failure
- genome wide
- chronic kidney disease
- newly diagnosed
- poor prognosis
- bone marrow
- aortic dissection
- drug induced
- type diabetes
- clinical trial
- signaling pathway
- big data
- dna methylation
- electronic health record
- oxidative stress
- adipose tissue
- acute lymphoblastic leukemia
- cell proliferation
- endoplasmic reticulum stress
- deep learning
- binding protein
- single molecule
- weight loss
- machine learning
- artificial intelligence