Biology subjects

Capper, D.

Publications and source records attributed to Capper, D..

6 recordsLinked to original sources

bioRxiv2025

Cryo-mtscATAC-seq for single-cell mitochondrial DNA genotyping and clonal tracing in archived human tissues

High-throughput clonal tracing of primary human samples relies on naturally occurring barcodes, such as somatic mitochondrial DNA (mtDNA) mutations detected via single-cell ATAC-seq (mtscATAC-seq). Fresh-frozen clinical specimens preserve tissue architecture but compromise cell integrity, thereby precluding their use in multi- omic approaches such as mitochondrial genotyping at single-cell resolution. Here, we introduce Cryo-mtscATAC-seq, a broadly applicable method for diverse pathophysiological contexts to isolate nuclei with their associated mitochondria ("CryoCells") from frozen samples for high-throughput clonal analysis. We applied Cryo-mtscATAC-seq to the neurodegenerated human brain, glioblastoma (GBM), pediatric neuroblastoma, and human aorta, and implemented mitobender, a computational tool to reduce ambient mtDNA in single-cell assays. Our approach revealed regional clonal gliogenesis and microglial expansions in amyotrophic lateral sclerosis (ALS), persistence of oligodendrocyte progenitor cell (OPC)-like clones in GBM recurrence, mtDNA depth heterogeneity after neuroblastoma chemotherapy, and oligoclonal proliferation of smooth muscle cells in human aorta. In conclusion, Cryo-mtscATAC-seq broadly extends mtDNA genotyping to archival frozen specimens across tissue types, opening new avenues for investigation of cell state- informed clonality in human health and disease.

systems biology↗

bioRxiv2025

SteMClass: A Novel DNA Methylation-Based Classifier for iPSC In Vitro Differentiation States.

Human induced pluripotent stem cells (iPSCs) hold great promise for regenerative medicine, disease modelling, and drug discovery, but most downstream applications require differentiation into specialised cell types not covered by current quality control assays. Here, we present "SteMClass", a proof-of-concept DNA methylation-based classifier that standardises iPSC differentiation state identification across protocols with one test. We curated a reference cohort of 15 iPSC lines differentiated into seven distinct states (n = 97), performed array-based DNA methylation profiling, and trained a random forest model to classify the eight distinct differentiation states. In nested cross-validation, SteMClass achieved a Brier score of 0.018, and on an independent cohort (n = 58) attained 96.5% accuracy (Cohens K = 0.959) with a 3% rejection rate. Applied to external data (n = 249), SteMClass achieved 85.1% overall accuracy (Cohens K = 0.687) with a 12.9% rejection rate. Among classified samples (n = 217), accuracy was 97.7% (Cohens K = 0.93). SteMClass is compatible with all Illumina methylation array versions, and accessible via an interactive web interface that supports classification and exploration of DNA methylation profiles. By providing a harmonised, single-assay framework for iPSC-derived differentiation state characterisation, SteMClass improves reproducibility and comparability across studies, paving the way for robust quality control standards and accelerating clinical translation.

cell biology↗

bioRxiv2023

Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.

neuroscience↗

bioRxiv2021

Distribution of GOPC:ROS1 and other ROS1 fusions in glioma types

The ROS proto-oncogene 1 (ROS1) gene is rearranged in various cancers. The translated fusion protein presents an attractive therapeutic target, since specific inhibitors have been approved for several tumor types. In glioma, ROS1 fusions are frequent within infantile hemispheric glioma, and single case reports on occurrences in other glioma types exist. However, a comprehensive analysis spanning the full width of glioma types and subtypes is lacking. We here assessed the spectrum and distribution of ROS1 fusions by screening >20,000 glioma cases for typical chromosomal alterations, with subsequent RNA-sequencing for confirmation of candidate cases. ROS1 fusions were identified in 16 cases, from low grade pilocytic astrocytoma WHO grade 1 to glioblastoma, IDH wildtype WHO grade 4. Thus, despite being enriched in some tumor types, ROS1 fusions are not pathognomonic for specific glioma types and may consitute a relevant target in a variety of cases.

genomics↗

bioRxiv2021

Recurrent fusions in PLAGL1 define a distinct subset of pediatric-type supratentorial ependymoma

Ependymomas encompass a heterogeneous group of central nervous system (CNS) neoplasms that occur along the entire neuroaxis. In recent years, extensive (epi-)genomic profiling efforts have identified several molecular groups of ependymoma that are characterized by distinct molecular alterations and/or patterns. Based on unsupervised visualization of a large cohort of genome-wide DNA methylation data, we identified a highly distinct group of pediatric-type tumors (n = 40) forming a cluster separate from all established CNS tumor types, of which a high proportion were histopathologically diagnosed as ependymoma. RNA sequencing revealed recurrent fusions involving the pleomorphic adenoma gene-like 1 (PLAGL1) gene in 19 of 20 of the samples analyzed, with the most common fusion being EWSR1:PLAGL1 (n = 13). Five tumors showed a PLAGL1:FOXO1 fusion and one a PLAGL1:EP300 fusion. High transcript levels of PLAGL1 were noted in these tumors, with concurrent overexpression of the imprinted genes H19 and IGF2, which are regulated by PLAGL1. Histopathological review of cases with sufficient material (n = 16) demonstrated a broad morphological spectrum of largely ependymoma-like tumors. Immunohistochemically, tumors were GFAP-positive and OLIG2- and SOX10-negative. In 3/16 of the cases, a dot-like positivity for EMA was detected. Consistent with other fusion-positive ependymal groups, all tumors in our series were located in the supratentorial compartment. Median age of the patients at the time of diagnosis was 6.2 years. Analysis of time to progression or recurrence revealed survival times comparable to those of patients with ZFTA:RELA-fused ependymoma. In summary, our findings suggest the existence of a novel group of supratentorial ependymomas that are characterized by recurrent PLAGL1 fusions and enriched for pediatric patients.

cancer biology↗

bioRxiv2020

An Integrative Genetic, Epigenetic and Proteomic Characterization of Pancreatic Neuroendocrine Neoplasms (PanNENs) defines Distinct Molecular Features of α- and β-cell like Subgroups

Pancreatic Neuroendocrine Carcinomas (PanNECs) are high-grade, poorly-differentiated tumors grouped together with Pancreatic Neuroendocrine Tumors (PanNETs) and placed within the Pancreatic Neuroendocrine Neoplasms (PanNENs) WHO tumor classification. Despite recent studies suggesting the endocrine origin of low-grade PanNETs, high-grade PanNEC origin remains unknown. DNA methylation analysis using the Illumina 850K beadchip array was conducted on 57 PanNEN samples, including 14 PanNECs. Distinct methylation profiles separated PanNEN samples into two major groups, clearly distinguishing high-grade PanNECs from other PanNETs including high-grade NETG3. DNA mutations, copy number changes and Immunohistochemistry of pancreatic cell-type markers PDX1, ARX and SOX9 were utilized to further characterize PanNECs and their hierarchical cell of origin in the pancreas. Phylo-epigenetic and cell-type signature features using methylation data from normal alpha, beta, acinar and ductal adult cells indicate an exocrine cell of origin for PanNECs, thus separating them in cell lineage from other PanNENs of endocrine origin. Our study provides a robust and clinically relevant method relying on methylation profiles to clearly distinguish PanNECs from PanNETG3s to improve patient stratification and treatment.

cancer biology↗