A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia.
T Roderick DockingJeremy D K ParkerMartin JäderstenGerben DunsLinda ChangJihong JiangJessica A PilsworthLucas A SwansonSimon K ChanReadman ChiuKa Ming NipSamantha MarAngela MoXuan WangSergio Martinez-HøyerRyan J StubbinsKaren L MungallAndrew J MungallRichard A MooreSteven J M JonesInanc BirolMarco A MarraDonna HoggeAly KarsanPublished in: Nature communications (2021)
As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2, demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.
Keyphrases
- end stage renal disease
- rna seq
- acute myeloid leukemia
- single cell
- chronic kidney disease
- ejection fraction
- newly diagnosed
- prognostic factors
- peritoneal dialysis
- stem cells
- genome wide
- emergency department
- escherichia coli
- copy number
- acute lymphoblastic leukemia
- pseudomonas aeruginosa
- patient reported
- deep learning
- allogeneic hematopoietic stem cell transplantation
- drug delivery
- study protocol
- binding protein
- smoking cessation
- phase iii