Biology subjects

Gronbaek, K.

Publications and source records attributed to Gronbaek, K..

4 recordsLinked to original sources

bioRxiv2026

Cholesterol Biosynthesis is a Targetable Vulnerability of CEBPA-mutant Acute Myeloid Leukemia

Bi-allelic CEBPA mutations occur in 5-15% of acute myeloid leukemia (AML) patients. The precise molecular consequences of CEBPA mutations, especially in combination with frequently co-occurring mutations in TET2, WT1, and GATA2, remain incompletely understood. Here, we present a robust human model of CEBPA-mutant AML through gene editing of healthy bone marrow-derived hematopoietic stem cells. Loss of the CEBPA-p42 isoform expressed in healthy cells with concomitant upregulation of the leukemic CEBPA-p30 isoform resulted in a myeloproliferative phenotype. Concurrent loss-of-function mutations in TET2 or WT1 drove full leukemic transformation, while GATA2 haploinsufficiency promoted erythroid precursor accumulation without overt AML. Single-cell transcriptomics and low-input proteomics revealed enhanced myeloid output, increased interferon signaling and elevated cholesterol biosynthesis in leukemic cells. Targeting cholesterol synthesis enhanced chemosensitivity, highlighting a potential therapeutic vulnerability, particularly relevant for CEBPA-mutant patients harboring co-mutations in TET2 or WT1, which have poor outcomes. Statement of significanceInduction of CEBPA-p30 by CRISPR/Cas gene editing in healthy human BM HSCs drives overt AML in vivo. TET2 and WT1 loss accelerate leukemogenesis, while GATA2 haploinsufficiency redirects differentiation toward erythroid precursors potentially driving acute erythroid leukemia. CEBPA-p30 AML exhibits cholesterol biosynthesis dependency, revealing a therapeutic vulnerability to statins.

cancer biology↗

bioRxiv2024

Bone marrow microenvironment signatures associate with patient survival after guadecitabine and atezolizumab therapy in HMA-resistant MDS

Almost 50% of patients with myelodysplastic syndrome (MDS) are refractory to first-line hypomethylating agents (HMAs), which presents a significant clinical challenge considering the lack of options for salvage. Past work revealed that immune checkpoint molecules on peripheral myeloblasts and immune cells are up-regulated after HMA treatment. Therefore, we conducted a Phase I/II clinical trial combining guadecitabine (an HMA) and atezolizumab (an immune checkpoint inhibitor) to treat HMA-relapsed or refractory (HMA-R/R) MDS patients. This combination therapy showed median overall survival of 15.1 months relative to historical controls (4-6 months). Here, we profiled the cell composition and gene expression signatures of cells from bone marrow aspirates from trial participants with short-term (<15 months) or long-term (>15 months) survival at single-cell resolution. Long-term survivors showed a significant reduction of immunosuppressive monocytes, and an expansion of effector lymphocytes after combination therapy. Further immune profiling suggests that gamma delta T cell activation through primed dendritic cells was associated with global interferon activation in the bone marrow microenvironment of long-term survivors. Short-term survivors exhibited elevated inflammation and senescence-like gene signatures that were not resolved by combination therapy. We propose that distinct bone marrow microenvironment features, such as senescence-associated inflammation or immunosuppressive monocyte presence, could improve patient stratification for HMA and immunotherapy combinations in HMA-R/R MDS patients.

cancer biology↗

bioRxiv2024

Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

cell biology↗

bioRxiv2021

COMPARE, an ultra-fast and robust suite for multiparametric screening, identifies phenotypic drug responses in acute myeloid leukemia

Multiparametric phenotypic screening of cells, for example assessing their responses to small molecules or knockdown/knockout of specific genes, is a powerful approach to understanding cellular systems and identifying potential new therapeutic strategies. However, automated tools for analyzing similarities and differences between a large number of tested conditions have not been readily available. Methods designed for clustering cells cannot identify differences between samples effectively. We introduce O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW for ultra-fast and robust analysis of multiparametric high-throughput screening. Applying a mass-aware gridding algorithm using hypercubes, O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW performs automatic and effective similarity comparison for hundreds to thousands of tests and provides information about the treatment effect. Particularly for screening data, O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW is equipped with modules to remove various sources of bias. Benchmarking tests show that O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW can circumvent batch effects and perform a similarity analysis substantially faster than conventional analysis tools. Applying O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW to high-throughput flow cytometry screening data, we were able to distinguish subtle phenotypic drug responses in a human sample and a genetically engineered mouse model with acute myeloid leukemia (AML). O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW revealed groups of drugs with similar responses even though their mechanisms are distinct from each other. In another screening, O_SCPLOWCOMPAC_SCPLOWRO_SCPLOWEC_SCPLOW effectively circumvented batch effects and grouped samples from AML and myelodysplastic syndrome (MDS) patients using clinical flow cytometry data.

cancer biology↗