Proteomic profiling based classification of CLL provides prognostication for modern therapy and identifies novel therapeutic targets.
Ti'ara L GriffenFieke W HoffYihua QiuJames W LillardAlessandra FerrajoliPhillip A ThompsonEndurance ToroKevin RuizJan A BurgerWilliam G WierdaSteven Mitchell KornblauPublished in: Blood cancer journal (2022)
Protein expression for 384 total and post-translationally modified proteins was assessed in 871 CLL and MSBL patients and was integrated with clinical data to identify strategies for improving diagnostics and therapy, making this the largest CLL proteomics study to date. Proteomics identified six recurrent signatures that were highly prognostic of survival and time to first or second treatment at three levels: individual proteins, when grouped into 40 functionally related groups (PFGs), and systemically in signatures (SGs). A novel SG characterized by hairy cell leukemia like proteomics but poor therapy response was discovered. SG membership superseded other prognostic factors (Rai Staging, IGHV Status) and were prognostic for response to modern (BTK inhibition) and older CLL therapies. SGs and PFGs membership provided novel drug targets and defined optimal candidates for Watch and Wait vs. early intervention. Collectively proteomics demonstrates promise for improving classification, therapeutic strategy selection, and identifying novel therapeutic targets.
Keyphrases
- prognostic factors
- mass spectrometry
- label free
- chronic lymphocytic leukemia
- end stage renal disease
- genome wide
- machine learning
- randomized controlled trial
- deep learning
- single cell
- ejection fraction
- acute myeloid leukemia
- peritoneal dialysis
- cell therapy
- newly diagnosed
- stem cells
- physical activity
- bone marrow
- emergency department
- patient reported outcomes
- replacement therapy
- patient reported
- free survival