Biology subjects

Bieg, M.

Publications and source records attributed to Bieg, M..

3 recordsLinked to original sources

bioRxiv2021

Deep molecular characterization linked to drug response profiling of pancreatic ductal adenocarcinoma using patient-derived organoids.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high drug resistance and poor prognosis. Novel therapeutic and stratification strategies are urgently needed. Here, we present an integration of in-depth genomic and transcriptomic characterization with drug screening and clinical outcome based on a catalogue of 51 patient-derived tumor organoids (PDOs) from resected PDAC. Known PDAC molecular subtypes and their prognostic value are conserved in organoids. Integration of transcriptomic and drug response profiles suggest a metabolism-mediated modulations of drug resistance. Copy number alterations on chromosome 13q and wild-type status of TP53 emerged as potential novel genomic biomarkers for sensitivity to 5-FU and oxaliplatin treatment, respectively. Functional testing of targeted drugs in PDOs revealed its additional value for genome-driven personalized oncology. Co-deletion of TP53/POLR2A increased vulnerability to RNA polymerase II inhibition, pointing to a promising target for personalized treatment in PDAC. SignificancePatient-derived PDAC organoids hold great promise as surrogate tumor models for personalized oncology. By integrating highly granular molecular, drug sensitivity and clinical data, we demonstrate that PDOs are valid models for molecular characterization and response prediction that also enable identification of novel drug sensitivity biomarkers and resistance mechanisms in PDAC.

cancer biology↗

bioRxiv2019

Whole-genome fingerprint of the DNA methylome during chemically induced differentiation of the human AML cell line HL-60/S4

BackgroundMyeloid differentiation gives rise to a plethora of immune cells in the human body. This differentiation leaves strong signatures in the epigenome through each differentiated state of genetically identical cells. The leukemic HL-60/S4 promyelocytic cell can be easily differentiated from its undifferentiated promyelocyte state into neutrophil-and macrophage-like cell states, making it an excellent system for studying myeloid differentiation. In this study, we present the underlying genome and epigenome architecture of HL-60/S4 through its undifferentiated and differentiated cell states.\n\nResultsWe performed whole genome bisulphite sequencing of HL-60/S4 cells and their differentiated counterparts. With the support of karyotyping, we show that HL-60/S4 maintains a stable genome throughout differentiation. Analysis of differential CpG methylation reveals that most methylation changes occur in the macrophage-like state. Differential methylation of promoters was associated with immune related terms. Key immune genes, CEBPA, GFI1, MAFB and GATA1 showed differential expression and methylation. However, we observed strongest enrichment of methylation changes in enhancers and CTCF binding sites, implying that methylation plays a major role in large scale transcriptional reprogramming and chromatin reorganisation during differentiation. Correlation of differential expression and distal methylation with support from chromatin capture experiments allowed us to identify putative proximal and long-range enhancers for a number of immune cell differentiation genes, including CEBPA and CCNF. Integrating expression data, we present a model of HL-60/S4 differentiation in relation to the wider scope of myeloid differentiation.\n\nConclusionsFor the first time, we elucidate the genome and CpG methylation landscape of HL-60/S4 during differentiation. We identify all differentially methylated regions and positions. We link these to immune function and to important factors in myeloid differentiation. We demonstrate that methylation plays a more significant role in modulating transcription via enhancer reprogramming, rather than by promoter regulation. We identify novel regulatory regions of key components in myeloid differentiation that are regulated by differential methylation. This study contributes another layer of \"omics\" characterisation of the HL-60/S4 cell line, making it an excellent model system for studying rapid in vitro cell differentiation.\n\nSummary statementEpigenomics plays a major role in cell identity and differentiation. We present the DNA methylation landscape of leukemic cells during in-vitro differentiation, to add another omics layer to better understand the mechanisms behind differentiation.

genomics↗

bioRxiv2018

Impact of cancer mutational signatures on transcription factor motifs in the human genome

BackgroundSomatic mutations in cancer genomes occur through a variety of molecular mechanisms, which contribute to different mutational patterns. To summarize these, mutational signatures have been defined using a large number of cancer genomes, and related to distinct mutagenic processes. Each cancer genome can be compared to this reference dataset and its exposure to one or the other signature be determined. Given the very different mutational patterns of these signatures, we anticipate that they will have distinct impact on genomic elements, in particular motifs for transcription factor binding sites (TFBS).\n\nResultsIn this work, we build the link between mutational signatures and TFBS motif alterations. We investigated and computed the theoretical impact of mutational signatures on 512 TFBS motifs, hence translating the trinucleotide mutation frequencies of the signatures into alteration frequencies of specific TFBS motifs, leading either to creation of disruption of these motifs. We further build a theoretical prediction of the alteration patterns for different cancer types based on the exposure of these cancer types to the mutation signatures. For certain motifs, a high correlation is observed between the TFBS motif creation and disruption events related to the information content of the motif.\n\nConclusionOur results show that the mutational signatures have different impact on the binding motifs of transcription factors and that for certain high complexity motifs there is a strong correlation between creation and disruption, related to the information content of the motif. This study represents a background estimation of the alterations due purely to mutational signatures in the absence of additional contributions, e.g. from evolutionary processes.

bioinformatics↗