Deciphering cancer genomes with GenomeSpy: a grammar-based visualization toolkit.

BACKGROUND: Visualization is an indispensable facet of genomic data analysis. Despite the abundance of specialized visualization tools, there remains a distinct need for tailored solutions. However, their implementation typically requires extensive programming expertise from bioinformaticians and software developers, especially when building interactive applications. Toolkits based on visualization grammars offer a more accessible, declarative way to author new visualizations. Yet, current grammar-based solutions fall short in adequately supporting the interactive analysis of large datasets with extensive sample collections, a pivotal task often encountered in cancer research. FINDINGS: We present GenomeSpy, a grammar-based toolkit for authoring tailored, interactive visualizations for genomic data analysis. By using combinatorial building blocks and a declarative language, users can implement new visualization designs easily and embed them in web pages or end-user-oriented applications. A distinctive element of GenomeSpy's architecture is its effective use of the graphics processing unit in all rendering, enabling a high frame rate and smoothly animated interactions, such as navigation within a genome. We demonstrate the utility of GenomeSpy by characterizing the genomic landscape of 753 ovarian cancer samples from patients in the DECIDER clinical trial. Our results expand the understanding of the genomic architecture in ovarian cancer, particularly the diversity of chromosomal instability. CONCLUSIONS: GenomeSpy is a visualization toolkit applicable to a wide range of tasks pertinent to genome analysis. It offers high flexibility and exceptional performance in interactive analysis. The toolkit is open source with an MIT license, implemented in JavaScript, and available at https://genomespy.app/.

Consortium Profile: The Methylation, Imaging and NeuroDevelopment (MIND) Consortium.

Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.

Job-related exhaustion risk variant in UST is associated with dementia and DNA methylation.

Previous genome-wide association and replication study for job-related exhaustion indicated a risk variant, rs13219957 in the UST gene. Epidemiological studies suggest connection of stress-related conditions and dementia risk. Therefore, we first studied association of rs13219957 and register-based incident dementia using survival models in the Finnish National FINRISK study surveys (N = 26,693). The AA genotype of rs13219957 was significantly associated with 40% increased risk of all-cause dementia. Then we analysed the UST locus association with brain pathology in the Vantaa 85+ cohort and found association with tau pathology (Braak stage) but not with amyloid pathology. Finally, in the functional analyses, rs13219957 showed a highly significant association with two DNA methylation sites of UST, and UST expression. Thus, the results suggest a common risk variant for a stress-related condition and dementia. Mechanisms to mediate the connection may include differential DNA methylation and transcriptional regulation of UST.

Quantification of cell death and proliferation of patient-derived ovarian cancer organoids through 3D imaging and image analysis.

Patient-derived organoids (PDOs) are ideal ex vivo model systems to study cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring drug efficacy in three-dimensional (3D) high-grade serous ovarian cancer PDO cultures through quantification of cytotoxicity using propidium iodide incorporation in dead cells. We also provide detailed steps to analyze proliferation of PDOs using the Ki67 biomarker. We describe steps for sample processing, immunofluorescent staining, high-throughput confocal imaging, and image-based quantification for 3D cultures. For complete details on the use and execution of this protocol, please refer to Lahtinen et al. (2023).1.

Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high grade serous carcinoma.

Ovarian high-grade serous carcinoma (HGSC) is typically diagnosed at an advanced stage, with multiple genetically heterogeneous clones existing in the tumors long before therapeutic intervention. Herein we integrate clonal composition and topology using whole-genome sequencing data from 510 samples of 148 patients with HGSC in the prospective, longitudinal, multiregion DECIDER study. Our results reveal three evolutionary states, which have distinct features in genomics, pathways, and morphological phenotypes, and significant association with treatment response. Nested pathway analysis suggests two evolutionary trajectories between the states. Experiments with five tumor organoids and three PI3K inhibitors support targeting tumors with enriched PI3K/AKT pathway with alpelisib. Heterogeneity analysis of samples from multiple anatomical sites shows that site-of-origin samples have 70% more unique clones than metastatic tumors or ascites. In conclusion, these analysis and visualization methods enable integrative tumor evolution analysis to identify patient subtypes using data from longitudinal, multiregion cohorts.

Kinase Inhibitors in the Treatment of Ovarian Cancer: Current State and Future Promises.

Ovarian cancer is the deadliest gynecological cancer, the high-grade serous ovarian carcinoma (HGSC) being its most common and most aggressive form. Despite the latest therapeutical advancements following the introduction of vascular endothelial growth factor receptor (VEGFR) targeting angiogenesis inhibitors and poly-ADP-ribose-polymerase (PARP) inhibitors to supplement the standard platinum- and taxane-based chemotherapy, the expected overall survival of HGSC patients has not improved significantly from the five-year rate of 42%. This calls for the development and testing of more efficient treatment options. Many oncogenic kinase-signaling pathways are dysregulated in HGSC. Since small-molecule kinase inhibitors have revolutionized the treatment of many solid cancers due to the generality of the increased activation of protein kinases in carcinomas, it is reasonable to evaluate their potential against HGSC. Here, we present the latest concluded and on-going clinical trials on kinase inhibitors in HGSC, as well as the recent work concerning ovarian cancer patient organoids and xenograft models. We discuss the potential of kinase inhibitors as personalized treatments, which would require comprehensive assessment of the biological mechanisms underlying tumor spread and chemoresistance in individual patients, and their connection to tumor genome and transcriptome to establish identifiable subgroups of patients who are most likely to benefit from a given therapy.

Pharmacoepigenetics of hypertension: genome-wide methylation analysis of responsiveness to four classes of antihypertensive drugs using a double-blind crossover study design.

Essential hypertension remains the leading risk factor of global disease burden, but its treatment goals are often not met. We investigated whether DNA methylation is associated with antihypertensive responses to a diuretic, a beta-blocker, a calcium channel blocker or an angiotensin receptor antagonist. In addition, since we previously showed an SNP at the transcription start site (TSS) of the catecholamine biosynthesis-related ACY3 gene to associate with blood pressure (BP) response to beta-blockers, we specifically analysed the association of methylation sites close to the ACY3 TSS with BP responses to beta-blockers. We conducted an epigenome-wide association study between leukocyte DNA methylation and BP responses to antihypertensive monotherapies in two hypertensive Finnish cohorts: the GENRES (https://clinicaltrials.gov/ct2/show/NCT03276598; amlodipine 5 mg, bisoprolol 5 mg, hydrochlorothiazide 25 mg, or losartan 50 mg daily) and the LIFE-Fin studies (https://clinicaltrials.gov/ct2/show/NCT00338260; atenolol 50 mg or losartan 50 mg daily). The monotherapy groups consisted of approximately 200 individuals each. We identified 64 methylation sites to suggestively associate (P < 1E-5) with either systolic or diastolic BP responses to a particular study drug in GENRES. These associations did not replicate in LIFE-Fin . Three methylation sites close to the ACY3 TSS were associated with systolic BP responses to bisoprolol in GENRES but not genome-wide significantly (P < 0.05). No robust associations between DNA methylation and BP responses to four different antihypertensive drugs were identified. However, the findings on the methylation sites close to the ACY3 TSS may support the role of ACY3 genetic and epigenetic variation in BP response to bisoprolol.

Differential DNA methylation in recovery from shift work disorder.

The human DNA methylome is responsive to our environment, but its dynamics remain underexplored. We investigated the temporal changes to DNA methylation (DNAme) in relation to recovery from a shift work disorder (SWD) by performing a paired epigenome-wide analysis in an occupational cohort of 32 shift workers (25 men, age = 43.8 ± 8.8 years, 21 SWD cases). We found that the effect of vacation on DNAme was more prominent in the SWD-group as compared to controls, with respect to the amount of significantly differentially methylated positions (DMPs; Punadj < 0.05) 6.5 vs 3.7%, respectively. The vast majority (78%) of these DMPs were hypomethylated in SWD but not in controls (27%) during the work period. The Gene Ontology Cellular component "NMDA glutamate receptor" (PFDR < 0.05) was identified in a pathway analysis of the top 30 genes in SWD. In-depth pathway analyses revealed that the Reactome pathway "CREB phosphorylation through the activation of CaMKII" might underlie the recovery. Furthermore, three DMPs from this pathway, corresponding to GRIN2C, CREB1, and CAMK2B, correlated with the degree of recovery (Punadj < 0.05). Our findings provide evidence for the dynamic nature of DNAme in relation to the recovery process from a circadian disorder, with biological relevance of the emerging pathways.

A distinctive DNA methylation pattern in insufficient sleep.

Short sleep duration or insomnia may lead to an increased risk of various psychiatric and cardio-metabolic conditions. Since DNA methylation plays a critical role in the regulation of gene expression, studies of differentially methylated positions (DMPs) might be valuable for understanding the mechanisms underlying insomnia. We performed a cross-sectional genome-wide analysis of DNA methylation in relation to self-reported insufficient sleep in individuals from a community-based sample (79 men, aged 39.3 ± 7.3), and in relation to shift work disorder in an occupational cohort (26 men, aged 44.9 ± 9.0). The analysis of DNA methylation data revealed that genes corresponding to selected DMPs form a distinctive pathway: "Nervous System Development" (FDR P value < 0.05). We found that 78% of the DMPs were hypomethylated in cases in both cohorts, suggesting that insufficient sleep may be associated with loss of DNA methylation. A karyoplot revealed clusters of DMPs at various chromosomal regions, including 12 DMPs on chromosome 17, previously associated with Smith-Magenis syndrome, a rare condition comprising disturbed sleep and inverse circadian rhythm. Our findings give novel insights into the DNA methylation patterns associated with sleep loss, possibly modifying processes related to neuroplasticity and neurodegeneration. Future prospective studies are needed to confirm the observed associations.

Common Genetic Variation Near Melatonin Receptor 1A Gene Linked to Job-Related Exhaustion in Shift Workers.

Study Objectives: Tolerance to shift work varies; only some shift workers suffer from disturbed sleep, fatigue, and job-related exhaustion. Our aim was to explore molecular genetic risk factors for intolerance to shift work. Methods: We assessed intolerance to shift work with job-related exhaustion symptoms in shift workers using the emotional exhaustion subscale of the Maslach Burnout Inventory-General Survey, and carried out a genome-wide association study (GWAS) using Illumina's Human610-Quad BeadChip (n = 176). The most significant findings were further studied in three groups of Finnish shift workers (n = 577). We assessed methylation in blood cells with the Illumina HumanMethylation450K BeadChip, and examined gene expression levels in the publicly available eGWAS Mayo data. Results: The second strongest signal identified in the GWAS (p = 2.3 × 10E-6) was replicated in two of the replication studies with p < .05 (p = 2.0 × 10E-4 when combining the replication studies) and indicated an association of job-related exhaustion in shift workers with rs12506228, located downstream of the melatonin receptor 1A gene (MTNR1A). The risk allele was also associated with reduced in silico gene expression levels of MTNR1A in brain tissue and suggestively associated with changes in DNA methylation in the 5' regulatory region of MTNR1A. Conclusions: These findings suggest that a variant near MTNR1A may be associated with job-related exhaustion in shift workers. The risk variant may exert its effect via epigenetic mechanisms, potentially leading to reduced melatonin signaling in the brain. These results could indicate a link between melatonin signaling, a key circadian regulatory mechanism, and tolerance to shift work.