Discovering gene expression signatures responding to tyrosine kinase inhibitor treatment in chronic myeloid leukemia.
BACKGROUND
Tyrosine kinase inhibitor (TKI)-based therapy is a recommended treatment for patients with chronic myeloid leukemia (CML). However, a considerable group of CML patients do not respond well to the TKI therapy. Challenging to overcome this problem, we tried to discover molecular signatures in gene expression profiles to discriminate the responders and non-responders of TKI therapy.


METHODS
We collected three microarray datasets of CML patients having total 73 responders and 38 non-responders. Statistical analysis was performed to identify differentially expressed genes (DEGs) as gene signature candidates from integrated microarray datasets. The classification performance of these genes and further selected discriminator gene sets was tested by using random forest and iterative backward variable selection methods.


RESULTS
We identified a set of genes including CTBP2, NADK, AZU1, CTSH, FSTL1, and HDLBP showing the highest accuracy more than 69.44 % to classify TKI response in CML patients. Interestingly, four genes of them are on the signaling pathway of cell proliferation. This set of genes showed much higher performance than the average performance of other genes in downstream signaling of TKI target, BCR-ABL.


CONCLUSIONS
In this study, we could find a set of potential companion diagnostic markers for TKI treatment and, at the same time, the potential of gene expression analysis to enhance the coverage of companion diagnostics.
['Cha|Kihoon|K|', 'Li|Yi|Y|', 'Yi|Gwan-Su|GS|']
D014408:Biomarkers, Tumor D055808:Drug Discovery D020869:Gene Expression Profiling D006801:Humans D015464:Leukemia, Myelogenous, Chronic, BCR-ABL Positive D020411:Oligonucleotide Array Sequence Analysis D047428:Protein Kinase Inhibitors D011505:Protein-Tyrosine Kinases D017211:Treatment Failure
Gene expression signature Chronic myeloid leukemia (CML) Random forest Meta-analysis Tyrosine kinase inhibitor (TKI)