Biology subjects

de Jong, S.

Publications and source records attributed to de Jong, S..

6 recordsLinked to original sources

bioRxiv2025

WEE1 inhibitors trigger GCN2-mediated activation of the integrated stress response

The WEE1 kinase negatively regulates CDK1/2 to control DNA replication and mitotic entry. Genetic factors that determine sensitivity to WEE1 inhibitors (WEE1i) are largely unknown. A genome-wide insertional mutagenesis screen revealed that mutation of EIF2A, a translation regulator, sensitized to WEE1i. Mechanistically, WEE1i treatment triggers a translational shut-down, which is lethal in combination with the reduced translation of EIF2AKO cells. A genome-wide CRISPR-Cas9 screen revealed that inactivation of integrated stress response (ISR) kinases GCN1/2 rescued WEE1i-mediated cytotoxicity. WEE1i induced GCN2 activation, ATF4 upregulation, and altered ribosome dynamics. Loss of the collided ribosome sensor ZNF598 conversely increased sensitivity to WEE1i. Notably, the ISR was not required for WEE1i to induce DNA damage, premature mitotic entry or sensitization to DNA-damaging chemotherapeutics. ISR activation was independent of CDK1/2 activation. Importantly, WEE1i-mediated ISR activation was independent of WEE1 presence, pointing at off-target effects, which are shared by multiple chemically distinct WEE1i. This response was also observed in peripheral blood mononuclear cells. Importantly, low-dose WEE1 inhibition did not induce ISR activation, while it still synergized with PKMYT1 inhibition. Taken together, WEE1i triggers toxic ISR activation and translational shutdown, which can be prevented by low-dose or combination treatments, while retaining the cell cycle checkpoint-perturbing effects.

cancer biology↗

bioRxiv2024

Transcriptional pattern enriched for synaptic signaling is associated with shorter survival of patients with high-grade serous ovarian cancer

BackgroundBulk transcriptomic analyses of high-grade serous ovarian cancer (HGSOC) so far have not uncovered potential drug targets, possibly because subtle, disease-relevant transcriptional patterns are overshadowed by dominant, non-relevant ones. Our aim was to uncover disease-outcome-related patterns in HGSOC transcriptomes that may reveal novel drug targets. MethodUsing consensus-independent component analysis, we dissected 678 HGSOC transcriptomes of systemic therapy naive patients--sourced from public repositories--into statistically independent transcriptional components (TCs). To enhance c-ICAs robustness, we added 447 transcriptomes from non-serous histotypes, low-grade serous, and non- cancerous ovarian tissues. Cox regression and survival tree analysis were performed to determine the association between TC activity and overall survival (OS). Finally, we determined the activity of the OS-associated TCs in 11 publicly available spatially resolved ovarian cancer transcriptomes. ResultsWe identified 374 TCs, capturing prominent and subtle transcriptional patterns linked to specific biological processes. Six TCs, age, and tumor stage stratified patients with HGSOC receiving platinum-based chemotherapy into ten distinct OS groups. Three TCs were linked to copy-number alterations affecting expression levels of genes involved in replication, apoptosis, proliferation, immune activity, and replication stress. Notably, the TC identifying patients with the shortest OS captured a novel transcriptional pattern linked to synaptic signaling, which was active in tumor regions within all spatially resolved transcriptomes. ConclusionThe association between a synaptic signaling-related TC and OS supports the emerging role of neurons and their axons as cancer hallmark-inducing constituents of the tumor microenvironment. These constituents might offer a novel drug target for patients with HGSOC.

cancer biology↗

bioRxiv2020

Robust and independent metabolic transcriptional components in 34,494 patient-derived samples and cell lines: a resource for translational cancer research

Patient-derived expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Therefore, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. We, therefore, performed consensus Independent Component Analyses (c-ICA) with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. c-ICA enabled us to create a transcriptional metabolic landscape in which many robust metabolic transcriptional components and their activation score in individual samples were defined. Here we demonstrate how this landscape can be used to explore associations between the metabolic transcriptome and drug sensitivities, patient outcomes, and the composition of the immune tumor microenvironment. The metabolic landscape can be explored at http://www.themetaboliclandscapeofcancer.com.

bioinformatics↗

bioRxiv2020

Integrative genomic strategies applied to a lymphoblast cell line model reveal specific transcriptomic signatures associated with clozapine response

Clozapine is an important antipsychotic drug. However, its use is often accompanied by metabolic adverse effects and, in rare instances, agranulocytosis. The molecular mechanisms underlying these adverse events are unclear. To gain more insights into the response to clozapine at the molecular level, we exposed lymphoblastoid cell lines (LCLs) to increasing concentrations of clozapine and measured genome-wide gene expression and DNA methylation profiles. We observed robust and significant changes in gene expression levels due to clozapine (n = 463 genes at FDR < 0.05) affecting cholesterol and cell cycle pathways. At the level of DNA methylation, we find significant changes upstream of the LDL receptor, in addition to global enrichments of regulatory, immune and developmental pathways. By integrating these data with human tissue gene expression levels obtained from the Genotype-Tissue Expression project (GTEx), we identified specific tissues, including liver and several tissues involved in immune, endocrine and metabolic functions, that clozapine treatment may disproportionately affect. Notably, differentially expressed genes were not enriched for genome-wide disease risk of schizophrenia or for known psychotropic drug targets. However, we did observe a nominally significant association of genetic signals related to total cholesterol and low-density lipoprotein levels. Together, these results shed light on the biological mechanisms through which clozapine functions. The observed associations with cholesterol pathways, its genetic architecture and specific tissue effects may be indicative of the metabolic adverse effects observed in clozapine users. LCLs may thus serve as a useful tool to study these molecular mechanisms further.

genomics↗

bioRxiv2017

Whole genome linkage analysis in a large Brazilian multigenerational family reveals distinct linkage signals for Bipolar Disorder and Depression.

Both common and rare genetic variation play a role in the causes for mood disorders. Very large families pose unique opportunities and analytical challenges but may provide a way to identify regions and mutations associated with mood disorders. We identified a family with a high prevalence (~30%) of mood disorders in a rural village in Brazil, featuring decreasing age of onset over generations. The pattern of inheritance was complex with 32 Bipolar type I cases, 11 Bipolar type II and 59 recurrent and/or severe Depression cases in addition to other phenotypes. We enrolled 333 participants with DNA samples from a broader pedigree of 960 subjects for genotyping using the Affymetrix 10K array. Non-parametric linkage was carried out via MERLIN and parametric with both MERLIN and MCLINKAGE. We exome sequenced a subset of the family (n=27) in order to identify rare variation within the linkage regions shared by affected family members. We identified four genome wide significant and four suggestive linkage regions on chromosomes 1, 2, 3, 11 and 12 for different phenotype definitions. However, no region received strong joint support in both the parametric and non-parametric analyses. Exome sequencing revealed potential deleterious variants in 11p15.4 for MDD and 1q21.1-1q21.3 and 12p23.1-p22.3, implicated in cell signaling, adhesion, translation and neurogenesis processes. Overall, our results suggest promising, but not definitive or confirmed evidence, that rare genetic variation contributes to the high prevalence of mood disorders in this multi-generational family. We note that a substantial role for common genetic variation is likely given the strength of the linkage signals observed.\n\nThe World Health Organisation reports depression and bipolar disorder as the second and seventh most important causes of years lost due to disability worldwide[1]. The heritability of bipolar disorder is between 60-90% with a lower but still substantial heritability for major depression (40-45%) [2]; [3]. First-degree relatives of bipolar disorder probands have a 5-10 fold increase in risk of developing the illness compared to relatives of controls but also show a three fold increase in unipolar depression, indicating that bipolar disorder does not \"breed true\" [4]. Large collaborative genome-wide association studies (GWAS) have uncovered several common genetic variants of small effect [5]. Genomewide estimates of heritability suggest that up to 60% of the genetic risk is contributed by common variants [6]. Overall, the current picture for bipolar disorder (and almost all complex traits) is a genetic architecture formed of both common and rare variants.\n\nLinkage studies have been pursued on the basis that there may be variants of greater effect shared between and within affected families. However these studies have usually focused on collections of comparatively small families or sib pairs and few consistent findings have emerged [7]. Large multigenerational families (e. g. of >30 affected individuals) theoretically offer a powerful means for mapping complex disease loci that are individually rare but common in a single family. These loci may be more highly penetrant and of larger effect than loci found with GWAS [8]. Here we report the results of the Brazilian Bipolar Family (BBF) study on a five-generation family of 639 members of which 333 were enrolled in the current analyses. Our objectives were to perform a linkage analysis with genome coverage and try to identify new genes/mutations related to bipolar and other mood disorders in the family. Here we report our findings and preliminary results of sequencing of linkage regions.

genetics↗

bioRxiv2017

Applying polygenic risk scoring for psychiatric disorders within a family context

We aim to investigate the application of polygenic risk scoring within a family context. Polygenic risk profiles could aid in unraveling the role that common variation confers on disease risk within a pedigree that would have traditionally been viewed through the prism of monogenic inheritance only. We illustrate our discussion by analyzing polygenic risk scores for schizophrenia, major depressive disorder and bipolar disorder in a large pedigree (n~260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. We apply polygenic risk scores to study patterns of assortative mating and anticipation, whereby it appears increased polygenic risk for psychiatric disorders is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations in the family. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity of a disease increases over the generations of a family. Joint analyses of both rare and common variation may be the most powerful way to understand the familial genetics of mood and psychiatric disorders.

genetics↗