Biology subjects

Piskorz, A. M.

Publications and source records attributed to Piskorz, A. M..

10 recordsLinked to original sources

bioRxiv2026

scUnique: Measuring Ongoing Chromosomal Instability

Chromosomal instability is a hallmark of cancer that can drive tumour heterogeneity and treatment resistance. However, scalable methods to measure the dynamics of chromosomal instability are lacking and thus historic genomic scars can be hard to distinguish from markers of currently active mutational processes. Here, we introduce scUnique, a novel approach to measure ongoing chromosomal instability from single-cell whole genome sequencing (scWGS) data. scUnique performs phylogeny-aware joint segmentation to refine single-cell copy number profiles and identifies recent copy number aberrations as statistically supported changes on the leaves of the inferred phylogenetic tree. This yields a per-cell measure of ongoing chromosomal instability at genome-wide resolution. We validate scUnique in (i) a comprehensive benchmarking study, (ii) in CRISPR-Cas-based experimental systems, and (iii) single-cell derived clones of a well-characterised ovarian model. We show that scUnique distinguishes ongoing HRD and FBI mutational processes. These results show that scUnique provides quantitative, scalable, genome-level information about ongoing chromosomal instability, not available in previous studies relying on bulk DNA-sequencing or single-cell imaging. In the future, these improved measurements could refine the understanding of mechanisms of chromosomal instability and lead to dynamic biomarkers for improved treatment decisions.

cancer biology↗

bioRxiv2025

Multi-stromal organoid co-cultures model pancreatic cancer and pancreatitis epithelial cell-fibroblast heterogeneity

Malignant cell-fibroblast cross-talks modulate disease progression and therapy response of pancreatic ductal adenocarcinoma (PDAC). Our knowledge of the heterogeneous nature of PDAC cancer-associated fibroblasts (CAFs) has significantly increased over the last few years. Yet, whether CAFs in PDAC differ from fibroblasts in pancreatic inflammation remains poorly understood. Chronic pancreatitis - a prolonged inflammatory state of the pancreas - is a risk factor for PDAC and is characterised by abundant fibroblasts. Thus, dissecting pancreatic fibroblast and epithelial cell reprogramming in malignancy relative to inflammation could inform new preventative, diagnostic and therapeutic strategies for PDAC. Here, we studied how pancreatic malignancy and inflammation differently shape fibroblast heterogeneity and their crosstalk with epithelial cells. We analysed human samples and mouse models of pancreatitis and PDAC and leveraged new murine pancreatitis-derived epithelial organoids to establish pancreatitis and PDAC organoid/multi-stroma co-cultures comprising pancreatic stellate cells, fibroblasts and mesothelial cells. We demonstrate that a combination of in vitro and in vivo models better captures epithelial cell and fibroblast markers of human pancreatitis and PDAC compared to mouse models alone. Finally, we identify PDAC and pancreatitis epithelial cell-specific reprogramming of stromal cells of different origin, and we infer the contribution of these distinct stromal cell types to fibroblasts in PDAC and pancreatitis in vivo. Together, our study highlights different epithelial cell-fibroblast heterogeneity in PDAC and pancreatitis, and provides new platforms for the identification of markers and epithelial-stromal interdependencies of these diseases.

cancer biology↗

bioRxiv2025

A scalable approach for tissue microarray profiling using spatial single cell transcriptomics

Spatially resolved transcriptomics was named Method of the Year 20201 and has continued to evolve rapidly since then, providing novel insights in development, physiology, and disease processes. Many approaches now offer excellent performance in formalin-fixed paraffin embedded tissue, opening up a wealth of archived clinical samples to these high-throughput spatial biology modalities. In this Chapter, we introduce a methodology to apply 10x Xenium In Situ to FFPE tissue microarrays. Using this method we have achieved a cost-effective approach to profile hundreds of genes with subcellular resolution in over a hundred human liver samples. Our method can easily be adapted to other tumour types, diseases, or model systems.

pathology↗

bioRxiv2025

Plant-Compatible Xenium In Situ Sequencing: Optimised Protocol for Spatial Transcriptomics in Medicago truncatula Roots and Nodules

Elucidating the spatial and temporal regulation of gene expression during plant organogenesis is crucial for enabling precise crop improvement strategies that incorporate beneficial traits into crops while avoiding adverse effects. Root nodules, specialised organs formed in symbiosis with nitrogen-fixing bacteria, provide a valuable system to study cell-type-specific gene networks in a symbiosis-induced developmental context. However, capturing these dynamics at cellular resolution in intact plant tissues remains technically challenging. Spatial transcriptomics technologies developed for animal systems are often not directly transferable to plant tissues due to fundamental differences in tissue composition between plants and animals, including rigid and heterogeneous plant cell walls, high cell wall autofluorescence, and large vacuoles in plant cells that complicate probe access and signal detection. To address these challenges, we present an optimised protocol for applying the Xenium in situ sequencing platform to formalin-fixed paraffin-embedded (FFPE) sections of plant tissues, including Medicago truncatula roots and nodules. Key technical adaptations include customised tissue preparation, optimised section thickness, hybridisation conditions, post-Xenium staining, imaging, and downstream image analysis, all tailored specifically for plant samples. To mitigate autofluorescence and enhance detection sensitivity, we employed a strategic approach to codeword selection during probe design. Furthermore, we developed a modular probe design approach combining a custom 380-gene standalone panel with a 100-gene add-on panel. This design allows flexibility for addressing diverse research questions and includes orthologous gene sequences from two Medicago ecotypes, ensuring compatibility for downstream functional validation using mutant lines available in both genetic backgrounds. We validated the protocol across nodules at multiple developmental stages using both the 50-gene panel targeting mature nodule cell identity and the extended 480-gene panel, which includes markers across different cell types and developmental stages, as well as genes of interest identified from prior single-cell and bulk RNA-seq analyses. This optimised workflow provides a reproducible and scalable method for high-resolution spatial transcriptomics in plant tissues, establishing a robust foundation for adaptation to other plant species and developmental systems.

plant biology↗

bioRxiv2024

Primary culture of high grade serous ovarian cancer cells, selection and derivation of three cell lines

Cell line models for high grade serous ovarian cancer (HGSOC) are limited in number and are poorly clinically annotated. Consequently, existing models often fail to recapitulate common features of HGSOC, inhibiting mechanistic and therapeutic discovery. We generated and characterised three spontaneously immortalized continuous HGSOC cell lines named CIOV1, CIOV2, and CIOV3 and confirmed that each cell line retained the genomic and pathologic characteristics of its parental tumour. We show that subclonal cell populations present at initiation, expanded and contracted during the culturing process before converging on a stable immortalized line. These lines are new valuable models to study acquired chemoresistance of HGSOC.

cancer biology↗

bioRxiv2022

Molecular landscape and functional characterization of centrosome amplification in ovarian cancer

High grade serous ovarian carcinoma (HGSOC) is characterised by poor outcome and extreme chromosome instability (CIN). Therapies targeting centrosome amplification (CA), a key mediator of chromosome missegregation and CIN, may have significant clinical utility in HGSOC. However, the prevalence of CA in HGSOC, its relationship to genomic biomarkers of CIN and its potential impact on therapeutic response have not been defined. Using high-throughput multi-regional microscopy on 287 clinical HGSOC tumour tissues and 73 ovarian cancer cell lines, we show that CA through centriole overduplication is a highly recurrent and heterogeneous feature of HGSOC and is strongly associated with CIN and genome subclonality. Cell-based studies showed that high prevalence CA is phenocopied in ovarian cancer cell lines, and that high CA is associated with increased multi-treatment resistance; most notably to paclitaxel which is the most common treatment used in HGSOC. CA in HGSOC may therefore present a potential driver of tumour evolution and a powerful biomarker for response to standard-of-care treatment.

cancer biology↗

bioRxiv2022

High-grade serous ovarian carcinoma organoids as models of chromosomal instability

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterised by ubiquitous TP53 mutation, profound chromosomal instability and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs). We carried out detailed bulk transcriptomic, bulk genomic, single cell genomic, and drug sensitivity characterisation of the organoids. We show that PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide a genomic tool for studies of specific mutational processes and precision therapeutics.

cancer biology↗

bioRxiv2018

frenchFISH: Poisson models for quantifying DNA copy-number from fluorescence in situ hybridisation of tissue sections

Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. Imaging of spots generated using fluorescence in situ hybridisation (FISH) of locus specific probes is routinely used to detect copy number changes in tumour nuclei. However, it often does not perform well on solid tumour tissue sections, where partially represented or overlapping nuclei are common. To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes; or a homogenous Poisson Point Process model for automated spot counting. We benchmarked the performance of FrenchFISH against previous approaches in a controlled simulation scenario and exemplify its use in 12 ovarian cancer FFPE-tissue sections, for which we assess copy number alterations in three loci (c-Myc, hTERC and SE7). We show that FrenchFISH outperforms standard spot counting approaches and that the automated spot counting is significantly faster than manual without loss of performance. FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue.\n\nAuthor summaryCancer genomes can look very chaotic, because cancer cells are unable to fully repair errors in DNA replication during cell division. While a healthy genome has two copies of every chromosome, in a cancer genome some pieces can be lost completely and others can appear in 50 copies. To diagnose cancers and to decide on the right therapeutic strategy for a patient, it can be very important to know how many copies of a particular piece of DNA exist in a cell. The standard technique used in the clinic to assess DNA copy number is called FISH, short for fluorescence in situ hybridisation. This technique uses fluorescent probes that bind to a DNA piece of interest and show up as glowing spots in a microscopic image. Counting the spots in an image is a labour-and time-intensive process that is generally done by well-trained experts. Here we present a statistical approach to automatically count FISH spots, which outperforms previously proposed methods, and has the potential to substantially speed up clinical diagnostics.

bioinformatics↗

bioRxiv2017

Copy-number signatures and mutational processes in ovarian carcinoma

Tumours with profound copy-number aberration elude molecular stratification due to their genomic complexity. By representing this complexity as a mixture of copy-number signatures, we provide molecular explanations for differing clinical outcomes. Here we present a method for copy-number signature identification, deriving eight signatures in 117 shallow whole-genome sequenced high-grade serous ovarian cancers (HGSOC), which validated on independent cohorts of 95 deep whole-genome sequenced, and 402 SNP array-profiled cases. Three copy-number signatures predicted longer overall survival, while the others predicted poorer outcome. We found evidence for the mutational processes giving rise to copy-number change for six of the eight signatures via correlations with other genomic features. Our results provide insights into the pathogenesis of HGSOC by uncovering multiple mutational processes that shape genomes following TP53 mutation. Importantly, our work shows that most HGSOC have a mixture of mutational processes suggesting that targeting a single mutator phenotype may be therapeutically suboptimal.

cancer biology↗

bioRxiv2017

Selecting Short DNA Fragments In Plasma Improves Detection Of Circulating Tumour DNA

Introductory paragraphNon-invasive analysis of cancer genomes using cell-free circulating tumour DNA (ctDNA) is being widely implemented for clinical indications. The sensitivity for detecting the presence of ctDNA and genomic changes in ctDNA is limited by its low concentration compared to cell-free DNA of non-tumour origin. We studied the feasibility for enrichment of ctDNA by size selection, in plasma samples collected before and during chemotherapy treatment in 13 patients with recurrent high-grade serous ovarian cancer. We evaluated the effects using targeted and whole genome sequencing. Selecting DNA fragments between 90-150 bp before analysis yielded enrichment of mutated DNA fraction of up to 11-fold. This allowed identification of adverse copy number alterations, including MYC amplification, otherwise not observed. Size selection allows detection of tumour alterations masked by non-tumour DNA in plasma and could help overcome sensitivity limitations of liquid biopsy for applications in early diagnosis, detection of minimal residual disease, and genomic profiling.

genomics↗