NEW YORK (GenomeWeb) – An integrated analysis of acute myeloid leukemia (AML) is revealing new recurrent mutations, functional genomic features, and drug response patterns in the blood cell cancer.
As they reported in Nature, researchers from Oregon Health & Science University used exome sequencing, RNA sequencing, and/or ex vivo drug sensitivity testing to profile up to 672 tumor samples from 562 AML patients. In addition to identifying recurrent mutations not described in the condition previously, they uncovered treatment response patterns that corresponded to specific mutation combinations or gene expression signatures.
"[O]ur dataset can be useful to see if that particular gene mutation corresponds with certain drug sensitivities," co-first author Jeffrey Tyner, a cell, developmental, and cancer biology researcher at OHSU, said in a statement. "We believe this dataset will help researchers and physicians solve those specific kinds of questions more easily."
As part of a program called Beat AML, the team did paired-end Illumina HiSeq 2500 exome sequencing on 622 of the tumor samples. It also did RNA sequencing on 451 tumor samples from 411 AML patients, and drug sensitivity testing with 122 drugs on 409 tumor samples from 363 AML patients.
"Each of these datasets alone has revealed new information about the biology and potential translational approaches in AML," the authors wrote, "and the integration of these datasets has revealed new markers and mechanisms of drug sensitivity and resistance that merit further study."
For example, the team used the exome sequence data to look at mutation frequencies in the often altered genes and genes mutated at low frequency in the collection, comparing them with the somatic gene alterations uncovered in samples from 200 AML patients assessed for the Cancer Genome Atlas.
The researchers uncovered transcriptome profiles associated with frequent tumor mutations or tumor subsets with specific cytogenetic features, as well as gene expression and mutation combinations present when tumors did or did not response to various drugs. Where drug resistance was common in tumors containing mutations in TP53, NRAS, KRAS, IDH1, or the transcriptional regulator-coding gene ASXL1, they noted that IDH2 mutation-positive tumors tended toward drug sensitivity.
The team's analysis also highlighted specific drug sensitivities corresponding with targeted treatments such as MAP kinase, PIK3C, mTOR, or JAK inhibitors. These and other data are available to other researchers online through a data viewer called Vizome.
"We want to parlay this information into clinical trials as much as we can, and we also want the broader community to use this dataset to accelerate their own work," Tyner said.