Epigenetics and Transcription of Myeloid Neoplasms

Myeloid neoplasms (MNs), including acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs), are a group of hematologic malignancies that include a substantial proportion of patients with unmet clinical needs. These diseases arise through the acquisition of somatic mutations, which may result from inherited genetic predisposition, environmental exposures, previous chemotherapy, or stochastic errors occurring during DNA replication in normal hematopoietic stem cells.

Among MNs, myelodysplastic syndromes (MDS) comprise a heterogeneous group of clonal disorders originating from hematopoietic stem cells and are characterized by ineffective hematopoiesis, morphological dysplasia, and an increased risk of progression to secondary acute myeloid leukemia (sAML). The transition from MDS to sAML is driven by complex molecular mechanisms that remain only partially understood. Although numerous studies have investigated the genetic alterations associated with disease progression, the molecular determinants that drive the evolution of low-risk MDS toward high-risk disease and ultimately sAML remain incompletely defined.

Gene expression programs in hematologic malignancies are controlled by the coordinated activity of transcription factors (TFs) acting on genomic cis-regulatory elements, including promoters and enhancers. While these regulatory networks play a fundamental role in determining cell identity and disease phenotype, their dynamic remodeling during disease progression has been comparatively less explored. We recently characterized the landscape of active cis-regulatory elements and their transcriptional consequences in a large cohort of patients with MDS and sAML, providing a comprehensive view of regulatory changes associated with leukemic transformation.

Our laboratory aims to dissect the molecular mechanisms underlying disease initiation and progression in myeloid neoplasms. To achieve this, we integrate multi-omics approaches - including epigenomics, transcriptomics, proteomics, and metabolomics - with single-cell technologies applied directly to primary patient samples. By integrating these complementary datasets, we identify disease stage-specific regulatory programs, characterize changes in transcriptional control, and uncover the molecular networks that drive disease evolution. Ultimately, our goal is to improve the biological understanding of myeloid neoplasms and identify novel biomarkers and therapeutic vulnerabilities that can be translated into better patient care.