Integrative analysis of drug response and clinical outcome in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.

Functional genomic landscape of acute myeloid leukaemia.

The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here we report initial findings from the Beat AML programme on a cohort of 672 tumour specimens collected from 562 patients. We assessed these specimens using whole-exome sequencing, RNA sequencing and analyses of ex vivo drug sensitivity. Our data reveal mutational events that have not previously been detected in AML. We show that the response to drugs is associated with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA sequencing also revealed gene expression signatures, which predict a role for specific gene networks in the drug response. Collectively, we have generated a dataset-accessible through the Beat AML data viewer (Vizome)-that can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of AML.

YM155 potently kills acute lymphoblastic leukemia cells through activation of the DNA damage pathway.

BACKGROUND: Novel-targeted therapies are in rapid development for the treatment of acute lymphoblastic leukemia (ALL) to overcome resistance and decrease toxicity. Survivin, a member of the inhibitor of apoptosis gene family and chromosome passenger complex, is critical in a variety of human cancers, including ALL. A well-established suppressor of survivin has been the small molecule, YM155. Reports are identifying other mechanisms of action for YM155. Therefore, we sought to investigate the mode of action and role of YM155 for therapeutic use in the context of ALL. METHODS: Primary ALL samples and ALL cell lines were interrogated with YM155 to identify drug sensitivity. Ph(+)ALL harboring the BCR-ABL1 oncogene were tested for any interaction with YM155 and the multi-kinase inhibitor dasatinib. Representative ALL cell lines were tested to identify the response to YM155 using standard biochemical assays as well as RNA expression and phosphorylation arrays. RESULTS: ALL samples exhibited significant sensitivity to YM155, and an additive response was observed with dasatinib in the setting of Ph(+)ALL. ALL cells were more sensitive to YM155 during S phase during DNA replication. YM155 activates the DNA damage pathway leading to phosphorylation of Chk2 and H2AX. Interestingly, screening of primary patient samples identified unique and exquisite YM155 sensitivity in some but not all ALL specimens. CONCLUSION: These results are the first to have screened a large number of primary patient leukemic samples to identify individual variations of response to YM155. Our studies further support that YM155 in ALL induces DNA damage leading to S phase arrest. Finally, only subsets of ALL have exquisite sensitivity to YM155 presumably through both suppression of survivin expression and activation of the DNA damage pathway underscoring its potential for therapeutic development.

Kinase pathway dependence in primary human leukemias determined by rapid inhibitor screening.

Kinases are dysregulated in most cancers, but the frequency of specific kinase mutations is low, indicating a complex etiology in kinase dysregulation. Here, we report a strategy to rapidly identify functionally important kinase targets, irrespective of the etiology of kinase pathway dysregulation, ultimately enabling a correlation of patient genetic profiles to clinically effective kinase inhibitors. Our methodology assessed the sensitivity of primary leukemia patient samples to a panel of 66 small-molecule kinase inhibitors over 3 days. Screening of 151 leukemia patient samples revealed a wide diversity of drug sensitivities, with 70% of the clinical specimens exhibiting hypersensitivity to one or more drugs. From this data set, we developed an algorithm to predict kinase pathway dependence based on analysis of inhibitor sensitivity patterns. Applying this algorithm correctly identified pathway dependence in proof-of-principle specimens with known oncogenes, including a rare FLT3 mutation outside regions covered by standard molecular diagnostic tests. Interrogation of all 151 patient specimens with this algorithm identified a diversity of kinase targets and signaling pathways that could aid prioritization of deep sequencing data sets, permitting a cumulative analysis to understand kinase pathway dependence within leukemia subsets. In a proof-of-principle case, we showed that in vitro drug sensitivity could predict both a clinical response and the development of drug resistance. Taken together, our results suggested that drug target scores derived from a comprehensive kinase inhibitor panel could predict pathway dependence in cancer cells while simultaneously identifying potential therapeutic options.