Advances towards genome-based acute myeloid leukemia classification: A comparative analysis of WHO-HAEM4R, WHO-HAEM5, and International Consensus Classification.
Xue ChenLili YuanYang ZhangFang WangXiaoli MaJiancheng FangPanxiang CaoYijun LiuZhixiu LiuMing LiuJiaqi ChenXiaosu ZhouMingyue LiuDavid JinTong WangKai-Yan LiuHongxing LiuPublished in: American journal of hematology (2024)
Two recent guidelines, the 5th edition of the World Health Organization Classification of Haematolymphoid Tumours (WHO-HAEM5) and the International Consensus Classification (ICC), were published to refine the diagnostic criteria of acute myeloid leukemia (AML). They both consider genomic features more extensively and expand molecularly defined AML subtypes. In this study, we compared the classifications of 1135 AML cases under both criteria. According to WHO-HAEM5 and ICC, the integration of whole transcriptome sequencing, targeted gene mutation screening, and conventional cytogenetic analysis identified defining genetic abnormalities in 89% and 90% of AML patients, respectively. The classifications displayed discrepancies in 16% of AML cases after being classified using the two guidelines, respectively. Both new criteria significantly reduce the number of cases defined by morphology and differentiation. However, their clinical implementation heavily relies on comprehensive and sophisticated genomic analysis, including genome and transcriptome levels, alongside the assessment of pathogenetic somatic and germline variations. Discrepancies between WHO-HAEM5 and ICC, such as the assignment of RUNX1 mutations, the rationality of designating AML with mutated TP53 as a unique entity, and the scope of rare genetic fusions, along with the priority of concurrent AML-defining genetic abnormalities, are still pending questions requiring further research for more elucidated insights.
Keyphrases
- acute myeloid leukemia
- genome wide
- allogeneic hematopoietic stem cell transplantation
- deep learning
- machine learning
- copy number
- clinical practice
- single cell
- gene expression
- end stage renal disease
- randomized controlled trial
- ejection fraction
- healthcare
- primary care
- rna seq
- squamous cell carcinoma
- transcription factor
- multidrug resistant
- quality improvement
- prognostic factors