Biology subjects

Langenau, D. M.

Publications and source records attributed to Langenau, D. M..

6 recordsLinked to original sources

bioRxiv2026

Synergistic targeting of EP300/CBP and EYA co-activators collapses the rhabdomyosarcoma core regulatory circuit

Rhabdomyosarcoma (RMS) is a multi-subtype, high-risk pediatric sarcoma with a low mutational burden. The mutations found in RMS often alter genes involved in transcriptional control. Approaches to target dysregulated RMS transcription have remained elusive. Here, we develop a novel approach to target RMS transcription comprising simultaneous targeting of two distinctly acting transcriptional co-activators. We discover a common identity-controlling pan-RMS core regulatory circuit (CRC) composed of oncogenic and lineage-specific myogenic master transcription factors (mTFs). Using a super-enhancer-based reporter screen, we identify the EP300/CBP inhibitor A485 as a potent inhibitor of the pan-RMS CRC, though with efficacy-limiting toxicities. To enhance efficacy, we identify the mTF-binding co-activator EYA2 as a co-factor of this pan-RMS CRC and exploit a new second-generation EYA1/2 inhibitor, LG1-34, to disrupt its function. Combined co-activator inhibition inactivates the CRC and synergistically reduces RMS growth. This strategy dually targets CRC-associated co-activators to cooperatively suppress the RMS transcriptome and enforce cell death.

cancer biology↗

bioRxiv2023

Single cell transcriptomic profiling identifies tumor-acquired and therapy-resistant cell states in pediatric rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric tumor that resembles undifferentiated muscle cells; yet the extent to which cell state heterogeneity and molecular features are shared with human development have not been fully ascribed. Here, we report a single-cell/nucleus RNA sequencing atlas derived from 72 datasets that includes patient tumors, patient-derived xenografts, primary in vitro cultures, and established cell lines. We report four dominant muscle-lineage cell states in RMS: progenitors, proliferative, differentiated, and ground cells. We stratify these RMS cells along the continuum of human muscle development and show that RMS cells share expression patterns with fetal/embryonal myogenic precursors rather than postnatal satellite cells. Indeed, fusion-negative RMS (FN-RMS) have a discrete stem cell hierarchy that faithfully recapitulates fetal muscle development. We also identify therapy-resistant FN-RMS progenitor cells that share transcriptomic similarity with bipotent skeletal mesenchymal cells, while a subset of fusion-positive (FP) RMS have tumor-acquired cells states, including a neuronal cell state, that are not found in development. Chemotherapy induced upregulation of progenitor signatures in FN-RMS while the neuronal gene programs were retained after therapy in FP-RMS. Taken together, this work identifies new cell state heterogeneity including unique treatment-resistant and tumor-acquired cell states that differ across RMS subtypes.

cancer biology↗

bioRxiv2022

Pyro-Velocity: Probabilistic RNA Velocity inference from single-cell data

Single-cell RNA Velocity has dramatically advanced our ability to model cellular differentiation and cell fate decisions. However, current preprocessing choices and model assumptions often lead to errors in assigning developmental trajectories. Here, we develop, Pyro-Velocity, a Bayesian, generative, and multivariate RNA Velocity model to estimate the uncertainty of cell future states. This approach models raw sequencing counts with the synchronized cell time across all expressed genes to provide quantifiable and improved information on cell fate choices and developmental trajectory dynamics.

bioinformatics↗

bioRxiv2020

Inflammation potentiates JMML-like blood defects in Shp2 mutant Noonan syndrome

Gain-of-function mutations in the protein-tyrosine phosphatase SHP2 are the most frequently occurring mutations in sporadic juvenile myelomonocytic leukemia (JMML) and JMML-like myeloproliferative neoplasm (MPN) associated with Noonan syndrome (NS). Hematopoietic stem and progenitor cells (HSPCs) are the disease propagating cells of JMML. Here, we explored transcriptomes of HSPCs with Shp2 mutations derived from JMML patients and a novel NS zebrafish model. In addition to major NS traits, CRISPR/Cas9 knock-in Shp2D61G mutant zebrafish recapitulated a JMML-like MPN phenotype, including myeloid lineage hyperproliferation, ex vivo growth of myeloid colonies and in vivo transplantability of HSPCs. Single cell mRNA sequencing of HSPCs from Shp2D61G zebrafish embryos and bulk sequencing of HSPCs from JMML patients revealed an overlapping inflammatory gene expression pattern. Strikingly, an anti-inflammatory agent rescued JMML-like MPN in Shp2D61G zebrafish embryos. Our results indicate that a common inflammatory response was triggered in the HSPCs from sporadic JMML patients and syndromic NS zebrafish, which potentiated MPN and may represent a future target for JMML therapies.

developmental biology↗

bioRxiv2019

The macrophage-expressed gene (mpeg) 1 identifies a subpopulation of B cells in the adult zebrafish

The mononuclear phagocytic system (MPS) consists of many cells, in particular macrophages, scattered throughout the body. However, there is increasing evidence for the heterogeneity of tissue-resident macrophages, leading to a pressing need for new tools to discriminate MPS subsets from other hematopoietic lineages. Mpeg1.1 is an evolutionary conserved gene encoding perforin-2, a pore-forming protein associated with host defense against pathogens. Zebrafish mpeg1.1:GFP and mpeg1.1:mCherry reporters were originally established to specifically label macrophages. Since, more than 100 peer-reviewed publications have made use of mpeg1.1-driven transgenics for in vivo studies, providing new insights into key aspects of macrophage ontogeny, activation and function. However, while the macrophage-specific expression pattern of the mpeg1.1 promoter has been firmly established in the zebrafish embryo, it is currently not known whether this specificity is maintained through adulthood. Here we report direct evidence that beside macrophages, a subpopulation of B-lymphocytes is marked by mpeg1.1 reporters in most adult zebrafish organs. These mpeg1.1+ lymphoid cells endogenously express mpeg1.1 and can be separated from mpeg1.1+ macrophages by virtue of their light-scatter characteristics using FACS. Remarkably, our analyses also revealed that B-lymphocytes, rather than mononuclear phagocytes, constitute the main mpeg1.1-positive population in irf8null myeloid-defective mutants, which were previously reported to recover tissue-resident macrophages in adulthood. One notable exception are skin macrophages, whose development and maintenance appear to be independent from irf8, similar to mammals. Collectively, our findings demonstrate that irf8 functions in myelopoiesis are evolutionary conserved and highlight the need for alternative macrophage-specific markers to study the MPS in adult zebrafish. SUMMARY SENTENCEMpeg1 is not a restricted macrophage marker, but also labels B cells in the adult zebrafish. Therefore, previously identified irf8-independent macrophages likely consist of B lymphocytes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=183 SRC="FIGDIR/small/836098v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@128a738org.highwire.dtl.DTLVardef@1fa6097org.highwire.dtl.DTLVardef@db61b2org.highwire.dtl.DTLVardef@eb2e2e_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2018

STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.

genomics↗