Description:
Summary
The current technology is a novel set of biomarkers derived from the largest ever genomic and transcriptomic data set for acute myeloid leukemia (AML), which includes a novel single gene biomarker capable of strongly predicting AML prognosis.
Technology Overview
Acute myeloid leukemia (AML) is an aggressive hematologic malignancy with an incidence of over 20,000 cases per year in the US. Complex genetic and biological features of AML contribute to frequent drug resistance and disease relapse, with only a small percentage of patients achieving durable remission.
Using a dataset containing genomic and transcriptomic information from over 800 patients, researchers at Oregon Health & Science University have identified novel biomarkers to aid in the treatment and management of AML. This includes gene signatures associated both with sensitivity and resistance to various classes of chemotherapies.
In addition, this dataset identified platelet endothelial aggregation receptor 1 (PEAR1) as a single-gene predictor of AML patient survival. PEAR1 expression strongly predicts survival across all subsets of AML patients and performs equivalently to the best prior multi-gene signatures (LSC17). Additionally, in young AML patients PEAR1 expression is predictive independently of other prognostic algorithms, such as the European LeukemiaNet staging system. Similar to LSC17, tests developed to measure PEAR1 have the potential to be used to improve patient care, by allowing for upfront risk-adapted management specifically for young patients with AML.
Publication
Bottomly D, et al. Integrative analysis of drug response and clinical outcome in acute myeloid leukemia. Cancer Cell. 2022 Aug 8;40(8):850-864.e9. Link
Licensing Opportunity
This technology is available for licensing.