Biology subjects

Zick, A.

Publications and source records attributed to Zick, A..

7 recordsLinked to original sources

bioRxiv2026

Bidirectional modulation of aging-associated cellular phenotypes by mitochondrial genome replacement

Mitochondrial dysfunction is a hallmark of cellular aging, but whether age-associated cellular decline can be functionally reversed remains unclear. Here, we applied mitochondrial genome replacement to replicative senescent fibroblasts and aged T cells derived from mice and humans. In senescent fibroblasts, replacement with mitochondria from young cells extended proliferative lifespan, whereas replacement with aged mitochondria accelerated proliferative decline, indicating bidirectional modulation of aging-associated phenotypes. In aged mouse T cells, mitochondrial genome replacement restored proliferative capacity and significantly enhanced antitumor activity following adoptive transfer into tumor-bearing mice. Similarly, mitochondrial genome replacement in aged human T cells enhanced cytokine production and shifted the transcriptomic programs toward a more youthful state. Collectively, these findings identify mitochondrial genetic integrity as a functional regulator of aging-associated cellular states and support the emerging view that mitochondria actively influence cellular aging trajectories.

Cell Biology↗

bioRxiv2026

Improved deconvolution of circulating tumor DNA from ultra-low-pass whole-genome methylation sequencing using CelFiE-ISH

Liquid biopsy using ultra-low-pass whole-genome sequencing (ULP-WGS, [~]0.25x coverage) is a promising tool to detect circulating tumor DNA (ctDNA) for cancer management, and the use of the native Oxford Nanopore (ONT) sequencing platform adds DNA methylation to the set of detectable features. Here, we test the performance of methylation-based cell-type deconvolution in ULP-WGS samples from diverse epithelial malignancies and investigate several new computational strategies using our CelFiE-ISH deconvolution framework. We find that incorporating larger numbers of markers restricted to the epithelial cell lineage can reduce the cancer fraction limit of detection down to 1.7-3.1%, matching or exceeding the 3% floor of established copy-number alteration (CNA) benchmarks. Our study provides a useful strategy for analysis of ULP-WGS ONT data and indicates that marker selection remains a key challenge for analyzing methylation-based cancer datasets.

genomics↗

bioRxiv2025

Methylation-Based Deconvolution Unveils Glioblastoma Heterogeneity and Cell-Type Composition Linked to Patient Survival

BackgroundIDH-wildtype glioblastoma (GBM) is an aggressive, heterogeneous brain tumor with limited treatment options. DNA methylation profiling allows detailed tumor characterization. This study applies methylation-based deconvolution to define GBMs cellular composition and its association with patient outcomes. MethodsWe generated oligodendroglial precursor cells at various developmental stages from enriched human neural progenitor cultures and used their DNA methylation signatures, along with published signatures of brain tumor and tumor microenvironment-relevant cell types, to deconvolve 263 adult GBMs (Heidelberg-cohort). Tumor purity was estimated using RF_Purify. An independent cohort of 199 GBMs from TCGA and GEO, all treated with standard-of-care therapy, was similarly deconvolved, followed by Kaplan-Meier survival analysis to assess the prognostic value of neoplastic component proportions. ResultsDeconvolution uncovered distinct cellular compositions, consistent with single-cell RNA sequencing findings. Tumor purity analysis showed neoplastic fractions averaged 70% of tumor bulk, predominantly oligodendrocyte-like (43%), oligodendrocyte precursor-like (27%), astrocyte-like (19%), and mesenchymal stem cell-like (11%) populations. Non-neoplastic fractions were enriched for macrophages, vascular cells, and immune populations. A higher oligodendrocyte-like signature was linked to poorer survival (median survival 14.3 vs. 15.3 months; p = 0.017), while a higher astrocyte-like signature correlated with improved outcomes (15.3 vs. 13.4 months; p = 0.044). The astrocyte-to-oligodendrocyte ratio emerged as a strong prognostic marker, with a higher ratio predicting significantly longer survival (15.8 vs. 11.9 months; p < 0.00011). ConclusionsMethylation-based deconvolution provides insight into GBM heterogeneity, highlighting the prognostic relevance of the astrocyte-to-oligodendrocyte ratio, which may guide personalized treatment strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/640603v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@942af0org.highwire.dtl.DTLVardef@18f2626org.highwire.dtl.DTLVardef@111a756org.highwire.dtl.DTLVardef@1194b_HPS_FORMAT_FIGEXP M_FIG A. We generated oligodendroglial precursor cells (OPs) at various developmental stages from enriched human neural progenitor cultures. A reference atlas of methylation signatures from 14 normal cell types, including the in vitro-generated cells, combined with published profiles of brain tumor and tumor microenvironment-relevant cell types, was applied to deconvolve 263 GBM samples based on their methylation profiles (Heidelberg cohort). Cell type proportions were analyzed with RF_Purify to estimate tumor purity and distinguish neoplastic from non-neoplastic components. B. An independent cohort of 199 GBMs from TCGA and GEO, with available clinical data and all treated with standard-of-care therapy, was similarly deconvolved based on methylation profiles. Kaplan-Meier survival analysis assessed the prognostic impact of cell type proportions, identifying the astrocyte-to-oligodendrocyte ratio as the most significant marker. (Created with BioRender.com) C_FIG Key pointsO_LIMethylation-based deconvolution incorporating in-vitro-derived oligodendrocyte precursor differentiation data reveals GBM heterogeneity C_LIO_LIGBMs neoplastic fraction is dominated by oligodendrocyte-lineage cells C_LIO_LIAstrocyte/oligodendrocyte ratio is a strong prognostic marker for patient survival C_LI Importance of the studyThis study advances neuro-oncology research by using methylation-based deconvolution to uncover the cellular heterogeneity of glioblastoma. By constructing a comprehensive reference atlas and identifying cell-type-specific methylation signatures, it provides prognostic insights into the distinct cellular compositions of glioblastoma. Combining deconvolution results with purity analysis enables the differentiation between neoplastic and non-neoplastic tumor components. This approach complements single-cell RNA sequencing while offering greater clinical applicability, as DNA methylation profiling can be performed on FFPE or fresh frozen samples, unlike the more costly and tissue-sensitive single-cell methods. Importantly, the identification of the astrocyte-to-oligodendrocyte ratio as a strong prognostic marker highlights key cellular determinants of glioblastoma survival. These findings deepen our understanding of glioblastoma biology and offer a practical tool for patient stratification.

cancer biology↗

bioRxiv2022

Subtyping of Small Cell Lung Cancer using plasma cell-free nucleosomes

Emerging data on small cell lung cancer (SCLC), an aggressive malignancy with exceptionally poor prognosis, support subtypes driven by distinct transcription regulators, which engender unique therapeutic vulnerabilities. However, the translational potential of these observations is limited by access to tumor biopsies. Here, we leverage chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) on 442 plasma samples from individuals with advanced SCLC, neuroendocrine carcinomas (NEC), non-SCLC cancers, and healthy adults. Beyond providing reliable estimates of SCLC circulating free DNA tumor fraction, cfChIP-seq captures the unique epigenetic states of SCLC tissue- and cell-of-origin. Comparison of cfChIP-seq signals to matched tumor transcriptomes reveals genome-wide concordance, establishing a direct link between gene expression in the tumor and plasma cell-free nucleosomes. Exploiting this link, we develop a classifier that discriminates between SCLC lineage-defining transcription factor subtypes based on cfChIP-seq data. This work sets the stage to non-invasively profile SCLC transcriptomes using plasma cfDNA histone modifications.

cancer biology↗

bioRxiv2021

Multiplexed Single-Molecule Epigenetic Analysis of Plasma-Isolated Nucleosomes for Cancer Diagnostics

The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine, providing information on pathological processes in the body. Blood cfDNA is in the form of nucleosomes, which maintain their tissue- and cancer-specific epigenetic state. We developed EPINUC, a single-molecule multi-parametric assay to comprehensively profile the Epigenetics of Plasma Isolated Nucleosomes, DNA methylation and cancer-specific protein biomarkers. Our system allows high-resolution detection of six active and repressive histone modifications, their ratios and combinatorial patterns, on millions of individual nucleosomes by single-molecule imaging. In addition, it provides sensitive and quantitative data on plasma proteins, including detection of non-secreted tumor-specific proteins such as mutant p53. Applying this analysis to a cohort of plasma samples detected colorectal cancer at high accuracy and sensitivity, even at early stages. Finally, combining EPINUC with direct single-molecule DNA sequencing revealed the tissue-of-origin of colorectal, pancreatic, lung and breast tumors. EPINUC provides multi-layered clinical-relevant information from limited liquid biopsy material, establishing a novel approach for cancer diagnostics.

cancer biology↗

bioRxiv2018

Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease

Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent cell death events in the body. Here, we present an approach for unbiased determination of the tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. The method is validated using in silico simulations as well as in vitro mixes of DNA from different tissue sources at known proportions. We show that plasma cfDNA of healthy donors originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure which can be easily adapted to study the cellular contributors to cfDNA in many settings, opening a broad window into healthy and pathologic human tissue dynamics.

molecular biology↗

bioRxiv2018

Specific detection of cell-free DNA derived from intestinal epithelial cells using methylation patterns

Epithelial cells of the intestine undergo rapid turnover and are thought to be cleared via stool. Disruption of tissue architecture, as occurs in colorectal cancer (CRC), results in the release of material from dying intestinal epithelial cells to blood. This phenomenon could be utilized for diagnosis and monitoring of intestinal diseases, if circulating cell-free DNA (cfDNA) derived from intestinal cells could be specifically identified. Here we describe two genomic loci that are unmethylated specifically in intestinal epithelial cells, allowing for sensitive and specific detection of DNA derived from such cells. As expected, intestinal DNA is found in stool, but not in plasma, of healthy individuals. Patients with inflammatory bowel disease (IBD) have minimal amounts of intestinal cfDNA in the plasma, whereas patients with advanced CRC show a strong signal. The intestinal markers are not elevated in plasma samples from patients with pancreatic ductal adenocarcinoma (PDAC), and a combination of intestine- and pancreas-specific markers allowed for robust differentiation between plasma cfDNA derived from CRC and PDAC patients. Intestinal DNA markers provide a mutation-independent tool for monitoring intestinal dynamics in health and disease.

developmental biology↗