Biology subjects

Kover, B.

Publications and source records attributed to Kover, B..

3 recordsLinked to original sources

bioRxiv2025

Phaeochromocytomas and paragangliomas harbour tumour-initiating SOX2+ stem cells

Phaeochromocytomas (PCCs) and paragangliomas (PGLs), are rare neuroendocrine tumours that arise in the neural crest (NC)-derived adrenal medulla and the paraganglia, respectively. Approximately 10%-15% of patients with PCCs and 35%-40% with PGLs go on to develop metastatic disease, leading to a reported median overall survival of 7 years. The development of prognostic markers and subsequent personal therapeutic strategies are hindered by a lack of understanding of tumourigenesis. In other organs, cells with stem-like properties are at the root of tumour initiation and maintenance, due to their ability to self- renew and give rise to differentiated cells. We have recently shown that, in the human adrenal, a subset of sustentacular cells, endowed with a support role, are in fact SOX2+ postnatal adrenomedullary stem cells, that are specified along the neural crest migratory route. In this study, we intended to determine if SOX2+ cells in PCCs and PGLs can behave as tumour-initiating stem cells. Using expression and transcriptomic studies, we demonstrate the presence of SOX2/SOX2-expressing cells across a broad range of PCCs and PGLs, irrespective of tumour aggressiveness, location, and causative mutation. In silico analyses reveal the co-expression of SOX2 and chromaffin cell markers in the tumour, and the active proliferation of these double-positive cells. Isolation of these cells in vitro in stem cell-promoting media, and their xenotransplantation on chicken chorioallantoic membranes, demonstrates that they have the potential to expand and metastasise in ovo, supporting their potential as tumour-initiating cells.

cancer biology↗

bioRxiv2024

Rapid and memory-efficient analysis and quality control of large spatial transcriptomics datasets

The 10x Visium spatial transcriptomics platform has been widely adopted due to its established analysis pipelines, robust community support, and manageable data output. However, technologies like 10x Visium have the limitation of being low-resolution, and recently spatial transcriptomics platforms with subcellular resolution have proliferated. Such high-resolution datasets pose significant computational challenges for data analysis, with regards to memory requirement and processing speed. Here, we introduce Pseudovisium, a Python-based framework designed to facilitate the rapid and memory-efficient analysis, quality control and interoperability of high-resolution spatial transcriptomics data. This is achieved by mimicking the structure of 10x Visium through hexagonal binning of transcripts. Analysis of 47 publicly available datasets concluded that Pseudovisium increased data processing speed and reduced dataset size by more than an order of magnitude. At the same time, it preserved key biological signatures, such as spatially variable genes, enriched gene sets, cell populations, and gene-gene correlations. The Pseudovisium framework allows accurate simulation of Visium experiments, facilitating comparisons between technologies and guiding experimental design. Specifically, we found high concordance between Pseudovisium (derived from Xenium or CosMx) and Visium data from consecutive tissue slices. We further demonstrate Pseudovisiums utility by performing rapid quality control on large-scale datasets from Xenium, CosMx, and MERSCOPE platforms, identifying similar replicates, as well as potentially low-quality samples and probes. The common data format provided by Pseudovisium also enabled direct comparison of metrics across 6 spatial transcriptomics platforms and 59 datasets, revealing differences in transcript capture efficiency and quality. Lastly, Pseudovisium allows merging of datasets for joint analysis, as demonstrated by the identification of shared cell clusters and enriched gene sets in the mouse brain using data from multiple spatial platforms. By lowering the computational requirements and enhancing interoperability and reusability of spatial transcriptomics data, Pseudovisium democratizes analysis for wet-lab scientists and enables novel biological insights.

bioinformatics↗

bioRxiv2023

Genetic and environmental determinants of multicellular-like phenotypes in fission yeast

Multicellular fungi have repeatedly given rise to primarily unicellular yeast species. Some of these, including Schizosaccharomyces pombe, are able to revert to multicellular-like phenotypes (MLP). Our bioinformatic analysis of existing data suggested that, besides some regulatory proteins, most proteins involved in MLP formation are not functionally conserved between S. pombe and budding yeast. We developed high-throughput assays for two types of MLP in S. pombe: flocculation and surface adhesion, which correlated in minimal medium, suggesting a common mechanism. Using a library of 57 natural S. pombe isolates, we found MLP formation to widely vary across different nutrient and drug conditions. Next, in a segregant S. pombe library generated from an adhesive natural isolate and the standard laboratory strain, MLP formation correlated with expression levels of the transcription-factor gene mbx2 and several flocculins. Quantitative trait locus mapping of MLP formation located a causal frameshift mutation in the srb11 gene encoding cyclin C, a part of the Cdk8 kinase module (CKM) of the Mediator complex. Other CKM deletions also resulted in MLP formation, consistently through upregulation of mbx2, and only in minimal media. We screened a library of 3721 gene-deletion strains, uncovering additional genes involved in surface adhesion on minimal media. We identified 31 high-confidence hits, including 19 genes that have not been associated with MLPs in fission or budding yeast. Notably, deletion of srb11, unlike deletions of the 31 hits, did not compromise cell growth, which might explain its natural occurrence as a QTL for MLP formation.

genetics↗