Biology subjects

van Hoeck, A.

Publications and source records attributed to van Hoeck, A..

8 recordsLinked to original sources

bioRxiv2023

EXO1-mediated DNA repair by single-strand annealing is essential for BRCA1-deficient cells

Deficiency for the repair of DNA double-strand breaks (DSBs) via homologous recombination (HR) leads to chromosomal instability and diseases such as cancer. Yet, defective HR also results in vulnerabilities that can be exploited for targeted therapy. Here, we identify such a vulnerability and show that BRCA1-deficient cells are dependent on the long-range end-resection factor EXO1 for survival. EXO1 loss results in DNA replication-induced lesions decorated by poly(ADP-ribose)-chains. In cells that lack both BRCA1 and EXO1, this is accompanied by unresolved DSBs due to impaired single-strand annealing (SSA), a DSB repair process that requires the activity of both proteins. In contrast, BRCA2-deficient cells have increased SSA, also in the absence of EXO1, and hence are not dependent on EXO1 for survival. In agreement with our mechanistic data, BRCA1-mutated tumours have elevated EXO1 expression and contain more genomic signatures of SSA compared to BRCA1-proficient tumours. Collectively, our data indicate that EXO1 is a promising novel target for treatment of BRCA1-deficient tumours.

molecular biology↗

bioRxiv2022

The genome-wide mutational consequences of DNA hypomethylation

DNA methylation is important for establishing and maintaining cell identity and for genomic stability. This is achieved by regulating the accessibility of regulatory and transcriptional elements and the compaction of subtelomeric, centromeric, and other inactive genomic regions. Carcinogenesis is accompanied by a global loss in DNA methylation, which facilitates the transformation of cells. Cancer hypomethylation may also cause genomic instability, for example through interference with the protective function of telomeres and centromeres. However, understanding the role(s) of hypomethylation in tumor evolution is incomplete because the precise mutational consequences of global hypomethylation have thus far not been systematically assessed. Here we made genome-wide inventories of all possible genetic variation that accumulates in single cells upon the long-term global hypomethylation by CRISPR/CAS9-mediated conditional knockdown of DNMT1. Depletion of DNMT1 results in a genomewide reduction in DNA methylation levels. Hypomethylated cells show reduced proliferation rates, reactivation of the inactive X-chromosome and abnormal nuclear morphologies. Prolonged hypomethylation is accompanied by increased chromosomal instability. However, there is no increase in mutational burden, enrichment for certain mutational signatures or structural changes to the genome. We conclude that the primary consequence of global hypomethylation is chromosomal instability and does not necessarily lead to other small-scale or structural mutational effects.

genomics↗

bioRxiv2021

MutationalPatterns: The one stop shop for the analysis of mutational processes

BackgroundThe collective of somatic mutations in a genome represents a record of mutational processes that have been operative in a cell. These processes can be investigated by extracting relevant mutational patterns from sequencing data. ResultsHere, we present the next version of MutationalPatterns, an R/Bioconductor package, which allows in-depth mutational analysis of catalogues of single and double base substitutions as well as small insertions and deletions. Major features of the package include the possibility to perform regional mutation spectra analyses and the possibility to detect strand asymmetry phenomena, such as lesion segregation. On top of this, the package also contains functions to determine how likely it is that a signature can cause damaging mutations (i.e., mutations that affect protein function). This updated package supports stricter signature refitting on known signatures in order to prevent overfitting. Using simulated mutation matrices containing varied signature contributions, we showed that reliable refitting can be achieved even when only 50 mutations are present per signature. Additionally, we incorporated bootstrapped signature refitting to assess the robustness of the signature analyses. Finally, we applied the package on genome mutation data of cell lines in which we deleted specific DNA repair processes and on large cancer datasets, to show how the package can be used to generate novel biological insights. ConclusionsThis novel version of MutationalPatterns allows for more comprehensive analyses and visualization of mutational patterns in order to study the underlying processes. Ultimately, in-depth mutational analyses may contribute to improved biological insights in mechanisms of mutation accumulation as well as aid cancer diagnostics. MutationalPatterns is freely available at http://bioconductor.org/packages/MutationalPatterns.

genomics↗

bioRxiv2021

Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features

Tumor tissue of origin (TOO) is an important factor for guiding treatment decisions. However, TOO cannot be determined for ~3% of metastatic cancer patients and are categorized as cancers of unknown primary (CUP). As whole genome sequencing (WGS) of tumors is now transitioning from the research domain to diagnostic practice in order to address the increasing demand for biomarker detection, its use for detection of TOO in routine diagnostics also starts becoming within reach. While proof of concept for the use of genome-wide features has been demonstrated before, more complex WGS mutation features, including structural variant (SV) driver and passenger events, have never been integrated into TOO-classifiers even though they bear highly characteristic links with tumor TOO. Using a uniformly processed dataset containing 6820 whole-genome sequenced primary and metastatic tumors, we have developed Cancer of Unknown Primary Location Resolver (CUPLR), a random forest based TOO classifier that employs 502 features based on simple and complex somatic driver and passenger mutations. Our model is able to distinguish 33 cancer (sub)types with an overall accuracy of 91% and 89% based on cross-validation (n=6139) and hold out set (n=681) predictions respectively. We found that SV derived features increase the accuracy and utility of TOO classification for specific cancer types. To ensure that predictions are human-interpretable and suited for use in routine diagnostics, CUPLR reports the top contributing features and their values compared to cohort averages. The comprehensive output of CUPLR is complementary to existing histopathological procedures and may thus improve diagnostics for patients with CUP.

genomics↗

bioRxiv2020

Pan-cancer landscape of homologous recombination deficiency

Homologous recombination deficiency (HRD) results in impaired double strand break repair and is a frequent driver of tumorigenesis. Here, we developed a genome-wide mutational scar-based pan-cancer Classifier of HOmologous Recombination Deficiency (CHORD) that can discriminate BRCA1- and BRCA2-subtypes. Analysis of a metastatic (n=3,504) and primary (n=1,854) pan-cancer cohort revealed HRD was most frequent in ovarian and breast cancer, followed by pancreatic and prostate cancer. Biallelic inactivation of BRCA1, BRCA2, RAD51C or PALB2 was the most common genetic cause of HRD, with RAD51C and PALB2 inactivation resulting in BRCA2-type HRD. While the specific genetic cause of HRD was cancer type specific, biallelic inactivation was predominantly associated with loss-of-heterozygosity (LOH), with increased contribution of deep deletions in prostate cancer. Our results demonstrate the value of pan-cancer genomics-based HRD testing and its potential diagnostic value for patient stratification towards treatment with e.g. poly ADP-ribose polymerase inhibitors (PARPi).

cancer biology↗

bioRxiv2019

5-Fluorouracil treatment induces characteristic T>G mutations in human cancer

5-Fluorouracil (5-FU) is a chemotherapeutic drug component that is commonly used for the treatment of solid cancers. It is proposed that 5-FU possesses anticancer properties via the interference with nucleotide synthesis and incorporation into DNA. As both mechanisms may have a mutational impact on both surviving tumor and healthy cells, we treated intestinal organoids with 5-FU followed by whole genome sequencing analysis and uncovered a highly characteristic mutational pattern that is dominated by T>G substitutions in a CTT context. Analysis of tumor whole genome sequencing data confirmed that this signature can also be identified in vivo in colorectal and breast cancer patients that have undergone treatment with 5-FU. We also found that more 5-FU mutations are induced in TP53 null backgrounds which may be of clinical relevance. Taken together, our results demonstrate that 5-FU is mutagenic and may drive tumor evolution and increase the risk of secondary malignancies. Furthermore, the identified signature shows a strong resemblance to COSMIC signature 17, the hallmark signature of treatment-naive esophageal and gastric tumors, which indicates that distinct endogenous and exogenous triggers can converge onto highly similar mutational signatures.

cancer biology↗

bioRxiv2018

Mutational impact of culturing human pluripotent and adult stem cells

Genetic changes acquired during in vitro culture pose a potential risk for the successful application of stem cells in regenerative medicine. To assess mutation accumulation risks induced by culturing, we determined genetic aberrations in individual human induced pluripotent stem cells (iPS cells) and adult stem cells (ASCs) by whole genome sequencing analyses. Individual iPS cells, intestinal ASCs and liver ASCs accumulated 3.5{+/-}0.5, 7.2{+/-}1.0 and 8.4{+/-}3.6 base substitutions per population doubling, respectively. The annual in vitro mutation accumulation rate of ASCs adds up to [~]1600 base pair substitutions, which is [~]40-fold higher than the in vivo rate of [~]40 base pair substitutions per year. Mutational analysis revealed a distinct in vitro induced mutational signature that is irrespective of stem cell type and distinct from the in vivo mutational signature. This in vitro signature is characterized by C to A changes that have previously been linked to oxidative stress conditions. Additionally, we observed stem cell-specific mutational signatures and differences in transcriptional strand bias, indicating differential activity of DNA repair mechanisms between stem cell types in culture. We demonstrate that the empirically defined mutation rates, spectra, and genomic distribution enable risk assessment by modelling the accumulation of specific oncogenic mutations during typical in vitro expansion, manipulation or screening experiments using human stem cells. Taken together, we have here for the first time accurately quantified and characterized in vitro mutation accumulation in human iPS cells and ASCs in a direct comparison. These results provide insights for further optimization of culture conditions for safe in vivo utilization of these cell types for regenerative purposes.

genomics↗

bioRxiv2018

Pan-cancer whole genome analyses of metastatic solid tumors

Metastatic cancer is one of the major causes of death and is associated with poor treatment efficiency. A better understanding of the characteristics of late stage cancer is required to help tailor personalised treatment, reduce overtreatment and improve outcomes. Here we describe the largest pan-cancer study of metastatic solid tumor genomes, including 2,520 whole genome-sequenced tumor-normal pairs, analyzed at a median depth of 106x and 38x respectively, and surveying over 70 million somatic variants. Metastatic lesions were found to be very diverse, with mutation characteristics reflecting those of the primary tumor types, although with high rates of whole genome duplication events (56%). Metastatic lesions are relatively homogeneous with the vast majority (96%) of driver mutations being clonal and up to 80% of tumor suppressor genes bi-allelically inactivated through different mutational mechanisms. For 62% of all patients, genetic variants that may be associated with outcome of approved or experimental therapies were detected. These actionable events were distributed across various mutation types underlining the importance of comprehensive genomic tumor profiling for cancer precision medicine.

cancer biology↗