Biology subjects

Ylstra, B.

Publications and source records attributed to Ylstra, B..

8 recordsLinked to original sources

bioRxiv2025

TET CpG sequence context specific DNA demeth-ylation shapes progression of IDH-mutant gliomas

BackgroundTreatment decisions in IDH-mutant oligodendrogliomas are shaped by tumor aggressiveness, underscoring the need for objective grading of these malignant brain tumors. Material and MethodsWe collected 302 primary and recurrent resections from oligodendrogliomas and performed Ki-67 staining, proteomics and DNA methylation profiling. Results & conclusionDuring tumor progression, DNA methylation of oligodendrogliomas changed along a continuum. This continuum is linked to increased epigenetic aging, methylation of transcription factors and Ki-67+ cell density, and to large scale DNA demethylation. Demethylation was correlated with CpGs flanking sequences preferred by TET enzymes. We confirmed these findings in previously profiled astrocytomas, indicating IDH-mutant gliomas progress along a shared epigenetic axis. We developed an objective DNA methylation based prognostic continuous grading coefficient (CGC{psi}) that captured these changes and outperformed WHO grading for oligodendrogliomas. Our findings underscore the potential of DNA methylation-based grading to more accurately reflect tumor biology and inform clinical decision-making in IDH-mutant gliomas.

cancer biology↗

bioRxiv2024

Evolutionary trajectories of IDH-mutant astrocytoma identify molecular grading markers related to cell cycling

1To study the evolutionary processes that drive malignant progression of IDH-mutant astrocytomas, we performed multi-omics on a large cohort of matched initial and recurrent tumor samples. The overlay of genetic, epigenetic, transcriptomic and proteomic data, combined with single-cell analysis, have identified overlapping features associated with malignant progression. These features are derived from three molecular mechanisms and provide a rationale of the underlying biology of tumor malignancy: cell-cycling, tumor cell (de-)differentiation and remodeling of the extracellular matrix. Specifically, DNA-methylation levels decreased over time, predominantly in tumors with malignant transformation and co-occurred with poor prognostic genetic events. DNA-methylation was lifted from specific loci associated with DNA replication and was associated with an increased RNA and protein expression of cell cycling associated genes. All results were validated on samples of newly diagnosed IDH-mutant astrocytoma patients included the CATNON randomized phase 3 clinical trial. Importantly, malignant progression was hardly affected by radio- or chemotherapy, indicating that treatment does not affect the course of disease. Our results culminate in a DNA-methylation based signature for objective tumor grading.

cancer biology↗

bioRxiv2024

Karyotype Evolution in Response to Chemoradiotherapy and Upon Recurrence of Esophageal Adenocarcinomas.

The genome of esophageal adenocarcinoma (EAC) is highly unstable and might evolve over time. Here, we track karyotype evolution in EACs in response to treatment and upon recurrence through multi-region and longitudinal analysis. To this end, we introduce L-PAC, a bio-informatics technique that allows inference of absolute copy number aberrations (CNA) of low-purity samples by leveraging information of high-purity samples from the same cancer. Quantitative analysis of matched absolute CNAs reveals that the amount of karyotype evolution induced by chemoradiotherapy (CRT) is predictive for early recurrence and depends on the initial level of karyotype intra-tumor heterogeneity. We observe that CNAs acquired in response to CRT are partially reversed back to the initial state upon recurrence. CRT hence alters the fitness landscape to which tumors can adjust by adapting their karyotype. Together, our results indicate that karyotype plasticity contributes to therapy resistance of EACs.

bioinformatics↗

bioRxiv2022

Multi-scale spatial modeling of immune cell distributions enables survival prediction in primary central nervous system lymphoma

To understand the clinical significance of the tumor microenvironment (TME), it is essential to study the interactions between malignant and non-malignant cells in clinical specimens. Here, we established a computational framework for a multiplex imaging system to comprehensively characterize spatial contexts of the TME at multiple scales, including close and long-distance spatial interactions between cell type pairs. We applied this framework to a total of 1,393 multiplex imaging data newly generated from 88 primary central nervous system lymphomas with complete follow-up data and identified significant prognostic subgroups mainly shaped by the spatial context. A supervised analysis confirmed a significant contribution of spatial context in predicting patient survival. In particular, we found an opposite prognostic value of macrophage infiltration depending on its proximity to specific cell types. Altogether, we provide a comprehensive framework to analyze spatial cellular interaction that can be broadly applied to other technologies and tumor contexts.

systems biology↗

bioRxiv2021

The epigenetic evolution of gliomas is determined by their IDH1 mutation status and treatment regimen

Tumor adaptation or selection is thought to underlie therapy resistance of gliomas. To investigate the longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 143 matched initial and recurrent patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) gliomas. IDHwt gliomas showed a longitudinally stable epigenome with relatively low levels of global methylation, whereas the epigenome of IDHmut gliomas showed initial high levels genome-wide of DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. By integrating DNA methylation and gene expression data, adaptive changes of putative master regulators of the cell cycle and of differentiation were seen in IDHmut recurrent tumors. Furthermore, relapses of IDHmut tumors were accompanied by histological progression which in turn influenced survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment differed between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neo-angiogenesis and T-cell infiltration upon treatment for IDHmut gliomas. Our study provides one of the largest cohorts of paired glioma samples profiled with epigenomics, transcriptomics and genomics; and our results demonstrate that the treatment of IDHmut gliomas reshapes the epigenome towards an IDHwt-like phenotype. Accordingly, the prevalent practice of early genotoxic treatment in this patient population may need to be revisited.

genomics↗

bioRxiv2020

Engineering large chromosomal deletions by CRISPR-Cas9

Arm-level chromosomal deletions are a prevalent and defining feature of cancer. A high degree of tumor-type and subtype specific recurrencies suggest a selective oncogenic advantage. However, due to their large size it has been difficult to pinpoint the oncogenic drivers that confer this advantage. Suitable functional genomics approaches to study the oncogenic driving capacity of arm-level deletions are limited. Here we present an effective technique to engineer arm-level deletions by CRISPR-Cas9 and create isogenic cell line models. We simultaneously induce double-strand breaks (DSBs) at two ends of a chromosomal arm and select the cells that have lost the intermittent region. Using this technique, we induce arm-level deletions on chromosome 11q (65 MB) and chromosome 6q (53 MB) in neuroblastoma cell lines. Such isogenic models enable further research on the role of arm-level deletions in tumor development and growth and their possible therapeutic potential.

genetics↗

bioRxiv2020

A multi-platform reference for somatic structural variation detection

Accurate detection of somatic structural variation (SV) in cancer genomes remains a challenging problem. This is in part due to the lack of high-quality gold standard datasets that enable the benchmarking of experimental approaches and bioinformatic analysis pipelines for comprehensive somatic SV detection. Here, we approached this challenge by genome-wide somatic SV analysis of the paired melanoma and normal lymphoblastoid COLO829 cell lines using four different technologies: Illumina HiSeq, Oxford Nanopore, Pacific Biosciences and 10x Genomics. Based on the evidence from multiple technologies combined with extensive experimental validation, including Bionano optical mapping data and targeted detection of candidate breakpoint junctions, we compiled a comprehensive set of true somatic SVs, comprising all SV types. We demonstrate the utility of this resource by determining the SV detection performance of each technology as a function of tumor purity and sequence depth, highlighting the importance of assessing these parameters in cancer genomics projects and data analysis tool evaluation. The reference truth somatic SV dataset as well as the underlying raw multi-platform sequencing data are freely available and are an important resource for community somatic benchmarking efforts.

genomics↗

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↗