Biology subjects

Koering, C.

Publications and source records attributed to Koering, C..

4 recordsLinked to original sources

bioRxiv2026

Gene Regulatory Network Inference reveals tcf4 as a key a player in neuroblastoma gene expression circuitry

Neuroblastoma (NB), a pediatric cancer arising from disrupted sympathetic neuron differentiation, exhibits marked heterogeneity and limited therapeutic options. To better understand its molecular circuitry dynamics, we applied CardamomOT, a novel Gene Regulatory Network (GRN) inference framework, to single-cell RNA-seq data from patient-derived tumoroids. This approach models gene regulation via piecewise deterministic Markov processes, capturing transcriptional bursting and protein-mediated feedback, overcoming limitations of RNA velocity (e.g., gene independence and lack of biological time). We identified a continuous chromaffin-to-sympathoblast differentiation trajectory along which we selected 85 dynamically relevant genes enriched in cell cycle and DNA replication functions. Notably, 9 genes overlapped with those driving normal sympathoadrenal differentiation, underscoring tumor-normal tissue similarity. The inferred 85-genes network reproduced quite well experimental gene expression patterns in silico, and allowed to predict protein-level dynamics. Furthermore, it allowed to predict the effect of perturbations (both knock-out and overexpression) of hub genes (e.g., tcf4 and PLK1). We show that those perturbations significantly altered cell fate proportions in silico, with tcf4 KO increasing chromaffin-like cells and reducing proliferative late sympathoblasts. Predictions regarding tcf4 were tested using drug inhibition as a proxy for the gene KO. Using the BET inhibitor JQ1 indeed induced profound effect on the transcriptomic identity of our tumoroids. All of the 50 predicted tcf4 target genes were found to be significantly altered by JQ1 treatment. Finally cell fate proportions were also altered ex vivo closely resembling the predicted output. Our work therefore demonstrates that NB tumoroids retain a dynamic, differentiation-like architecture amenable to GRN modeling. Predicted druggable targets offer testable therapeutic avenues, including repurposing BET inhibitors or PLK1 inhibitors, potentially in combination.

cancer biology↗

bioRxiv2025

Multiscale modeling of the spatial structure of stem cells in neuroblastoma patient-derived tumoroids reveals a critical role for a short-range diffusive process

Neuroblastomas are heterogeneous pediatric tumors of the sympathetic nervous system for which treatments are still limited. Fundamental and applied approaches have been enabled thanks to the generation of patient-derived tumoroids (PDTs), ex vivo 3D structures used as avatars of the original tumor. We generated neuroblastoma PDTs and quantified the spatial distribution of CD133+ cancer stem cells using immunohistochemistry. We observed that those cells tend to aggregate in the PDT. In order to better understand the set of rules needed for generating such structures, we implemented a multiscale agent-based neuroblastoma tumoroid model. Model rules specify single cells fate based on its intracellular content, which dynamically evolves according to a stochastic gene regulatory network. The state of this network can be modulated by cell-to-cell signalling through neighbor cells fate decisions and, possibly, spatial location. We first observed that in the absence of any spatial rules for inter-cellular interactions, no spatial structure emerged. The addition of simple rules (signalling by cell-to-cell contact or differential cell adhesion) only marginally improved the quantitative agreement to the experimental dataset. In sharp contrast, the addition of short-range pro-stem cell diffusive signalling among stem cells produced very realistic 3D PDT-like structures. This works highlights the power of our multiscale approach to discard too simplistic rules and to propose a minimal set of hypotheses required to reproduce qualitatively and quantitatively experimentally observed spatial structures. In the case of neuroblastomas-derived PDTs, short-range spatial diffusion of stem-to-stem cell signalling proved to play a key role in successfully reconstructing the spatial structure.

cancer biology↗

bioRxiv2024

MYC shapes ER-mitochondria calcium transfer by directly targeting ITPR1: implications for MYC-induced safeguard mechanisms and cancer

The MYC and NMYC transcription factors (TFs) play a key role in cell proliferation and are overexpressed in most cancer cells. However, in normal cells their overexpression triggers safeguard mechanisms promoting cell death and cellular senescence, which are bypassed in cancer cells. The mechanisms of action of this TF family are only partially understood. Here, we reveal that in normal cells MYC binds to the Inositol 1,4,5-Trisphosphate Receptor type 1 (ITPR1) gene and upregulates its expression, triggering an ER-mitochondria calcium (Ca2+) transfer, which is involved in MYC-induced cell death and senescence. Supporting a tumor suppressive role of MYC/ITPR1 axis, ITPR1 expression is generally decreased in cancer and reactivation of this pathway induces cancer cell death. Nevertheless, some cancer cells, generally expressing high levels of MYCN and/or MYC, also express high level of ITPR1, which correlates with high expression of BCL2, encoding an inhibitor of ITPR1. Strikingly, in high-risk MYCN-amplified neuroblastoma, ITPR1 expression is controlled by NMYC and its level correlates with worse patient survival. In these cells, blocking the interaction between BCL2 and ITPR1 induces mitochondrial Ca2+ accumulation and cell death, and decreases tumor size. Collectively these data highlight a new function of MYC factors by controlling Ca2+ signaling, which could constitute an unsuspected vulnerability for some cancer cells, including high-risk MYCN-amplified neuroblastoma cells.

cancer biology↗

bioRxiv2022

Differentiation is accompanied by a progressive loss in transcriptional memory

Cell differentiation requires the integration of two opposite processes, a stabilizing cellular memory, especially at the transcriptional scale, and a burst of gene expression variability which follows the differentiation induction. Therefore, the actual capacity of a cell to undergo phenotypic change during a differentiation process relies upon a modification in this balance which favors change-inducing gene expression variability. However, there are no experimental data providing insight on how fast the transcriptomes of identical cells would diverge on the scale of the very first two cell divisions during the differentiation process. In order to quantitatively address this question, we developed different experimental methods to recover the transcriptomes of related cells, after one and two divisions, while preserving the information about their lineage at the scale of a single cell division. We analyzed the transcriptomes of related cells from two differentiation biological systems (human CD34+ cells and T2EC chicken primary erythrocytic progenitors) using two different single-cell transcriptomics technologies (sc-RT-qPCR and scRNA-seq). We identified that the gene transcription profiles of differentiating sister-cells are more similar to each-other than to those of non related cells of the same type, sharing the same environment and undergoing similar biological processes. More importantly, we observed greater discrepancies between differentiating sister-cells than between self-renewing sister-cells. Furthermore, a continuous increase in this divergence from first generation to second generation was observed when comparing differentiating cousin-cells to self renewing cousin-cells. Our results are in favor of a continuous and gradual erasure of transcriptional memory during the differentiation process.

cell biology↗