PHILADELPHIA—Super-enhancer profiling can unearth biomarkers and therapeutic targets for acute myeloid leukemia (AML), according to research presented at the AACR conference Hematologic Malignancies: Translating Discoveries to Novel Therapies.
Researchers used high-throughput ChIP sequencing to identify super-enhancer domains in a cohort of AML patients.
And this revealed both known and previously unknown genes that are important for AML disease biology.
Eric Olson, PhD, and his colleagues from Syros Pharmaceuticals in Watertown, Massachusetts, presented this research during one of the meeting’s poster sessions.
The investigators explained that super-enhancers are a class of densely clustered cis-regulatory elements that are key to initiating and maintaining cell-type-specific gene expression in cancer and other settings. Tumor cells acquire super-enhancers at key oncogenes and at genes that participate in the acquisition of hallmark capabilities in cancer.
So the researchers set out to identify and characterize super-enhancer domains in a cohort of AML patients.
The team collected primary AML samples and performed chromatin fragmentation, chromatin immunoprecipitation, and DNA purification and sequencing.
They then mapped enhancer regions and characterized enhancer profiles. This revealed AML-specific super-enhancers and associated genes.
For example, in one patient, the investigators identified 392 AML-specific super-enhancers, which were associated with 11 genes important for AML disease biology: HOXA7, LMO2, HLX, MYADM, ETV6, AFF1, RUNX1, GFI1, SPI1, MEIS1, and MYB.
In another patient, the team identified 279 AML-specific super-enhancers that were associated with 9 genes: MLLT10, AKT3, FLT3, ETV6, KLF13, RELA, FOSB, BMI1, and RUNX1.
The researchers said these findings suggest that super-enhancer profiling provides a new option for identifying biomarkers and therapeutic targets in AML and other malignancies.
“Syros’s gene control platform can systematically and efficiently identify known and previously unrecognized tumor biomarkers and cancer dependencies directly from patient tissue,” Dr Olson said. “Our data demonstrate unique gene control elements in AML patient subsets that hold promise in the classification and treatment of AML.”