Biology subjects

Pabst, C.

Publications and source records attributed to Pabst, C..

5 recordsLinked to original sources

bioRxiv2026

Leukemic Stem Cell Subtypes Drive Distinct Niche Remodeling in Acute Myeloid Leukemia

Leukemic stem cells (LSCs) sustain acute myeloid leukemia (AML) and are implicated in therapy resistance and relapse. Yet, it remains unknown how LSCs remodel the bone marrow niche. AML is known to alter stromal and vascular microenvironments, but these effects are difficult to separate from bulk leukemic burden and immune inflammation. Here, we use isogenic human AML xenografts with distinct LSC characteristics but comparable engraftment to define LSC-associated niche remodeling in vivo. Single-cell profiling revealed that LSC-high AML shifts the mesenchymal niche toward fibro-inflammatory states, expanding Fmod+ fibroblasts and Cd34+ perivascular fibroblast-like cells while suppressing osteolineage differentiation. The leukemic compartment remained heterogeneous, with a specific MEP-like LSC population expressing niche-remodeling ligands including TGFB1, IL1B, and ANGPT1. LSC-high AML activated a TGF{beta}-responsive, CREB3L1-controlled fibroblast trajectory, and perturbing TGF{beta} signaling or CREB3L1 activation reduced stromal support for AML cells. These findings identify a specific LSC subtype as a source of niche-remodeling cues that shape specialized leukemia-supportive niches.

molecular biology↗

bioRxiv2022

Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

Inter-patient variability and the similarity of healthy and leukemic stem cells have impeded the characterization of leukemic stem cells (LSCs) in acute myeloid leukemia (AML), and their differentiation landscape. Here, we introduce CloneTracer, a novel method that adds clonal resolution to single-cell RNA-seq datasets. Applied to samples from 19 AML patients, CloneTracer revealed routes of leukemic differentiation. While residual healthy cells dominated the dormant stem cell compartment, active leukemic stem cells resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors were highly aberrant and constituted the disease-defining compartment: Their gene expression and differentiation state determined both chemotherapy response and the leukemias ability to differentiate to transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers mis-regulated specifically in leukemic cells by intra-patient comparisons. Taken together, CloneTracer revealed a differentiation landscape that mimics its healthy counterpart and determines biology and therapy response in AML.

cancer biology↗

bioRxiv2021

GRaNIE and GRaNPA: Inference and evaluation of enhancer-mediated gene regulatory networks applied to study macrophages

Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their activity is regulated by a combination of transcription factors (TFs), epigenetic changes and genetic variants. Several approaches exist to link enhancers to their target genes, and others that infer TF-gene connections. However, we currently lack a framework that systematically integrates enhancers into TF-gene regulatory networks. Furthermore, we lack an unbiased way of assessing whether inferred regulatory interactions are biologically meaningful. Here we present two methods, implemented as user-friendly R packages: GRaNIE (Gene Regulatory Network Inference including Enhancers) for building enhancer-based gene regulatory networks (eGRNs) and GRaNPA (Gene Regulatory Network Performance Analysis) for evaluating GRNs. GRaNIE jointly infers TF-enhancer, enhancer-gene and TF-gene interactions by integrating open chromatin data such as ATAC-Seq or H3K27ac with RNA-seq across a set of samples (e.g. individuals), and optionally also Hi-C data. GRaNPA is a general framework for evaluating the biological relevance of TF-gene GRNs by assessing their performance for predicting cell-type specific differential expression. We demonstrate the power of our tool-suite by investigating gene regulatory mechanisms in macrophages that underlie their response to infection and cancer, their involvement in common genetic diseases including autoimmune diseases, and identify the TF PURA as putative regulator of pro-inflammatory macrophage polarisation. Availability- GRaNIE: https://bioconductor.org/packages/release/bioc/html/GRaNIE.html - GRaNPA: https://git.embl.de/grp-zaugg/GRaNPA Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

genomics↗

bioRxiv2021

Enhancer-priming in ageing human bone marrow mesenchymal stromal cells contributes to immune traits

Bone marrow mesenchymal stromal cells (BMSCs) can differentiate into adipocytes and osteoblasts, and are important regulators of the haematopoietic system. Ageing associates with an increased ratio of bone marrow adipocytes to osteoblasts and immune dysregulation. Here, we carried out an integrative multiomics analysis of ATAC-Seq, RNA-Seq and proteomics data from primary human BMSCs in a healthy cohort age between 20 - 60. We identified age-sensitive elements uniquely affecting each molecular level where transcription is mostly spared, and characterised the underlying biological pathways, revealing the interplay of age-related gene expression mechanism changes spanning multiple gene regulatory layers. Through data integration with enhancer-mediated gene regulatory network analysis, we discovered that enhancers and transcription factors influence cell differentiation potential in the ageing BMSCs. By combining our results with genome-wide association study data, we found that age-specific changes could contribute to common traits related to BMSC-derived tissues such as bone and adipose tissue, and to immune-related traits on a systemic level such as asthma. We demonstrate here that a multiomics approach is crucial for unravelling complex information, providing new insights on how ageing contributes to bone marrow- and immune-related disorders.

systems biology↗

bioRxiv2018

MutaSeq reveals the transcriptomic consequences of clonal evolution in acute myeloid leukemia

Cancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with i the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells.

genomics↗