| 1. |
- Clark, Andrew G., et al.
(author)
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Evolution of genes and genomes on the Drosophila phylogeny
- 2007
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 450:7167, s. 203-218
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Journal article (peer-reviewed)abstract
- Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
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| 2. |
- Lu, Yingchang, et al.
(author)
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A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
- 2018
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In: Cancer Research. - 0008-5472 .- 1538-7445. ; 78:18, s. 5419-5430
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Journal article (peer-reviewed)abstract
- .AbstractLarge-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.
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| 3. |
- Yang, Yaohua, et al.
(author)
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Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk
- 2019
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In: Cancer Research. - : AMER ASSOC CANCER RESEARCH. - 0008-5472 .- 1538-7445. ; 79:3, s. 505-517
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Journal article (peer-reviewed)abstract
- DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
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| 4. |
- Bandopadhayay, Pratiti, et al.
(author)
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BET Bromodomain Inhibition of MYC-Amplified Medulloblastoma
- 2014
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In: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 20:4, s. 912-925
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Journal article (peer-reviewed)abstract
- Purpose:MYC-amplified medulloblastomas are highly lethal tumors. Bromodomain and extraterminal (BET) bromodomain inhibition has recently been shown to suppress MYC-associated transcriptional activity in other cancers. The compound JQ1 inhibits BET bromodomain-containing proteins, including BRD4. Here, we investigate BET bromodomain targeting for the treatment of MYC-amplified medulloblastoma.Experimental Design:We evaluated the effects of genetic and pharmacologic inhibition of BET bromodomains on proliferation, cell cycle, and apoptosis in established and newly generated patient- and genetically engineered mouse model (GEMM)-derived medulloblastoma cell lines and xenografts that harbored amplifications of MYC or MYCN. We also assessed the effect of JQ1 on MYC expression and global MYC-associated transcriptional activity. We assessed the in vivo efficacy of JQ1 in orthotopic xenografts established in immunocompromised mice.Results:Treatment of MYC-amplified medulloblastoma cells with JQ1 decreased cell viability associated with arrest at G1 and apoptosis. We observed downregulation of MYC expression and confirmed the inhibition of MYC-associated transcriptional targets. The exogenous expression of MYC from a retroviral promoter reduced the effect of JQ1 on cell viability, suggesting that attenuated levels of MYC contribute to the functional effects of JQ1. JQ1 significantly prolonged the survival of orthotopic xenograft models of MYC-amplified medulloblastoma (P < 0.001). Xenografts harvested from mice after five doses of JQ1 had reduced the expression of MYC mRNA and a reduced proliferative index.Conclusion:JQ1 suppresses MYC expression and MYC-associated transcriptional activity in medulloblastomas, resulting in an overall decrease in medulloblastoma cell viability. These preclinical findings highlight the promise of BET bromodomain inhibitors as novel agents for MYC-amplified medulloblastoma.
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| 5. |
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| 6. |
- Buddenkotte, Thomas, et al.
(author)
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Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation
- 2023
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In: Computers in Biology and Medicine. - : Elsevier Ltd. - 0010-4825 .- 1879-0534. ; 163
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Journal article (peer-reviewed)abstract
- Uncertainty quantification in automated image analysis is highly desired in many applications. Typically, machine learning models in classification or segmentation are only developed to provide binary answers; however, quantifying the uncertainty of the models can play a critical role for example in active learning or machine human interaction. Uncertainty quantification is especially difficult when using deep learning-based models, which are the state-of-the-art in many imaging applications. The current uncertainty quantification approaches do not scale well in high-dimensional real-world problems. Scalable solutions often rely on classical techniques, such as dropout, during inference or training ensembles of identical models with different random seeds to obtain a posterior distribution. In this paper, we present the following contributions. First, we show that the classical approaches fail to approximate the classification probability. Second, we propose a scalable and intuitive framework for uncertainty quantification in medical image segmentation that yields measurements that approximate the classification probability. Third, we suggest the usage of k-fold cross-validation to overcome the need for held out calibration data. Lastly, we motivate the adoption of our method in active learning, creating pseudo-labels to learn from unlabeled images and human–machine collaboration.
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| 7. |
- Buddenkotte, Thomas, et al.
(author)
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Deep learning-based segmentation of multisite disease in ovarian cancer
- 2023
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In: EUROPEAN RADIOLOGY EXPERIMENTAL. - : Springer Nature. - 2509-9280. ; 7:1
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Journal article (peer-reviewed)abstract
- Purpose: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.Methods: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established “no-new-Net” framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.Results: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10–7, 3 × 10–4, 4 × 10–2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10–3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.Conclusion: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.Relevance statement: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.Key points:The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented.Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists.Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. Graphical Abstract: [Figure not available: see fulltext.]
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| 8. |
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| 9. |
- Dareng, EO, et al.
(author)
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Polygenic risk modeling for prediction of epithelial ovarian cancer risk
- 2022
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In: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
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Journal article (peer-reviewed)abstract
- Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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| 10. |
- Gustavsson, Emil K., et al.
(author)
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The annotation of GBA1 has been concealed by its protein-coding pseudogene GBAP1
- 2024
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In: Science Advances. - 2375-2548. ; 10:26, s. 1-20
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Journal article (peer-reviewed)abstract
- Mutations in GBA1 cause Gaucher disease and are the most important genetic risk factor for Parkinson’s disease. However, analysis of transcription at this locus is complicated by its highly homologous pseudogene, GBAP1. We show that >50% of short RNA-sequencing reads mapping to GBA1 also map to GBAP1. Thus, we used long-read RNA sequencing in the human brain, which allowed us to accurately quantify expression from both GBA1 and GBAP1. We discovered significant differences in expression compared to short-read data and identify currently unannotated transcripts of both GBA1 and GBAP1. These included protein-coding transcripts from both genes that were translated in human brain, but without the known lysosomal function—yet accounting for almost a third of transcription. Analyzing brain-specific cell types using long-read and single-nucleus RNA sequencing revealed region-specific variations in transcript expression. Overall, these findings suggest nonlysosomal roles for GBA1 and GBAP1 with implications for our understanding of the role of GBA1 in health and disease.
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| 11. |
- Heinze, Karolin, et al.
(author)
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Validated biomarker assays confirm ARID1A loss is confounded with MMR deficiency, CD8 TIL infiltration, and provides no independent prognostic value in endometriosis-associated ovarian carcinomas.
- 2021
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In: The Journal of pathology. - : Wiley. - 1096-9896 .- 0022-3417. ; 256:4, s. 388-401
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Journal article (peer-reviewed)abstract
- ARID1A (BAF250a) is a component of the SWI/SNF chromatin modifying complex, plays an important tumour suppressor role, and is considered prognostic in several malignancies. However, in ovarian carcinomas there are contradictory reports on its relationship to outcome, immune response, and correlation with clinicopathological features. We assembled a series of 1,623 endometriosis-associated ovarian carcinomas, including 1,078 endometrioid (ENOC) and 545 clear cell (CCOC) ovarian carcinomas through combining resources of the Ovarian Tumor Tissue Analysis (OTTA) Consortium, the Canadian Ovarian Unified Experimental Resource (COEUR), local, and collaborative networks. Validated immunohistochemical surrogate assays for ARID1A mutations were applied to all samples. We investigated associations between ARID1A loss/mutation, clinical features, outcome, CD8+ tumour-infiltrating lymphocytes (CD8+ TIL), and DNA mismatch repair deficiency (MMRd). ARID1A loss was observed in 42% of CCOC and 25% of ENOC. We found no associations between ARID1A loss and outcomes, stage, age, or CD8+ TIL status in CCOC. Similarly, we found no association with outcome or stage in endometrioid cases. In ENOC, ARID1A loss was more prevalent in younger patients (p=0.012), and associated with MMRd (p<0.001), and presence of CD8+ TIL (p=0.008). Consistent with MMRd being causative of ARID1A mutations, in a subset of ENOC we also observed an association between ARID1A loss-of-function mutation as a result of small indels (p=0.035, versus single nucleotide variants). In ENOC, the association between ARID1A loss, CD8+ TIL, and age, appears confounded by MMRd status. Although this observation does not explicitly rule out a role for ARID1A influence on CD8+ TIL infiltration in ENOC, given current knowledge regarding MMRd, it seems more likely that effects are dominated by the hypermutation phenotype. This large dataset with consistently applied biomarker assessment now provides a benchmark for the prevalence of ARID1A loss-of-function mutations in endometriosis-associated ovarian cancers and brings clarity to the prognostic significance. This article is protected by copyright. All rights reserved.
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| 12. |
- Jaiswal, Siddhartha, et al.
(author)
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Age-Related Clonal Hematopoiesis Associated with Adverse Outcomes.
- 2014
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In: New England Journal of Medicine. - 0028-4793. ; 371:26, s. 2488-2498
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Journal article (peer-reviewed)abstract
- Background The incidence of hematologic cancers increases with age. These cancers are associated with recurrent somatic mutations in specific genes. We hypothesized that such mutations would be detectable in the blood of some persons who are not known to have hematologic disorders. Methods We analyzed whole-exome sequencing data from DNA in the peripheral-blood cells of 17,182 persons who were unselected for hematologic phenotypes. We looked for somatic mutations by identifying previously characterized single-nucleotide variants and small insertions or deletions in 160 genes that are recurrently mutated in hematologic cancers. The presence of mutations was analyzed for an association with hematologic phenotypes, survival, and cardiovascular events. Results Detectable somatic mutations were rare in persons younger than 40 years of age but rose appreciably in frequency with age. Among persons 70 to 79 years of age, 80 to 89 years of age, and 90 to 108 years of age, these clonal mutations were observed in 9.5% (219 of 2300 persons), 11.7% (37 of 317), and 18.4% (19 of 103), respectively. The majority of the variants occurred in three genes: DNMT3A, TET2, and ASXL1. The presence of a somatic mutation was associated with an increase in the risk of hematologic cancer (hazard ratio, 11.1; 95% confidence interval [CI], 3.9 to 32.6), an increase in all-cause mortality (hazard ratio, 1.4; 95% CI, 1.1 to 1.8), and increases in the risks of incident coronary heart disease (hazard ratio, 2.0; 95% CI, 1.2 to 3.4) and ischemic stroke (hazard ratio, 2.6; 95% CI, 1.4 to 4.8). Conclusions Age-related clonal hematopoiesis is a common condition that is associated with increases in the risk of hematologic cancer and in all-cause mortality, with the latter possibly due to an increased risk of cardiovascular disease. (Funded by the National Institutes of Health and others.).
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| 13. |
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| 14. |
- Jiang, X., et al.
(author)
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Shared heritability and functional enrichment across six solid cancers
- 2019
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Journal article (peer-reviewed)abstract
- Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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| 15. |
- Meagher, N. S., et al.
(author)
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Gene-Expression Profiling of Mucinous Ovarian Tumors and Comparison with Upper and Lower Gastrointestinal Tumors Identifies Markers Associated with Adverse Outcomes
- 2022
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In: Clinical Cancer Research. - 1078-0432. ; 28:24, s. 5383-5395
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Journal article (peer-reviewed)abstract
- Purpose: Advanced-stage mucinous ovarian carcinoma (MOC) has poor chemotherapy response and prognosis and lacks biomarkers to aid stage I adjuvant treatment. Differentiating primaryMOC from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathologic and geneexpression data were analyzed to identify prognostic and diagnostic features. Experimental Design: Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n = 333), mucinous borderline ovarian tumors ( MBOT, n = 151), and upper GI (n = 65) and lower GI tumors (n = 55). Results: Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2 years from diagnosis, compared with expansile pattern in stage I MOC [hazard ratio ( HR), 2.77; 95% confidence interval (CI), 1.04-7.41, P = 0.042]. Increased expression of THBS2 and TAGLN was associated with shorter OS in MOC patients (HR, 1.25; 95% CI, 1.04-1.51, P = 0.016) and (HR, 1.21; 95% CI, 1.01-1.45, P = 0.043), respectively. ERBB2 (HER2) amplification or high mRNA expression was evident in 64 of 243 (26%) of MOCs, but only 8 of 243 (3%) were also infiltrative (4/39, 10%) or stage III/IV (4/31, 13%). Conclusions: An infiltrative growth pattern infers poor prognosis within 2 years from diagnosis and may help select stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confers an adverse prognosis and is upregulated in the infiltrative subtype, which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies.
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| 16. |
- O'Keefe, James H., et al.
(author)
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Omega-3 Blood Levels and Stroke Risk : A Pooled and Harmonized Analysis of 183 291 Participants From 29 Prospective Studies
- 2024
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In: Stroke. - : American Heart Association. - 0039-2499 .- 1524-4628. ; 55:1, s. 50-58
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Journal article (peer-reviewed)abstract
- BACKGROUND:The effect of marine omega-3 PUFAs on risk of stroke remains unclear.METHODS:We investigated the associations between circulating and tissue omega-3 PUFA levels and incident stroke (total, ischemic, and hemorrhagic) in 29 international prospective cohorts. Each site conducted a de novo individual-level analysis using a prespecified analytical protocol with defined exposures, covariates, analytical methods, and outcomes; the harmonized data from the studies were then centrally pooled. Multivariable-adjusted HRs and 95% CIs across omega-3 PUFA quintiles were computed for each stroke outcome.RESULTS:Among 183 291 study participants, there were 10 561 total strokes, 8220 ischemic strokes, and 1142 hemorrhagic strokes recorded over a median of 14.3 years follow-up. For eicosapentaenoic acid, comparing quintile 5 (Q5, highest) with quintile 1 (Q1, lowest), total stroke incidence was 17% lower (HR, 0.83 [CI, 0.76–0.91]; P<0.0001), and ischemic stroke was 18% lower (HR, 0.82 [CI, 0.74–0.91]; P<0.0001). For docosahexaenoic acid, comparing Q5 with Q1, there was a 12% lower incidence of total stroke (HR, 0.88 [CI, 0.81–0.96]; P=0.0001) and a 14% lower incidence of ischemic stroke (HR, 0.86 [CI, 0.78–0.95]; P=0.0001). Neither eicosapentaenoic acid nor docosahexaenoic acid was associated with a risk for hemorrhagic stroke. These associations were not modified by either baseline history of AF or prevalent CVD.CONCLUSIONS:Higher omega-3 PUFA levels are associated with lower risks of total and ischemic stroke but have no association with hemorrhagic stroke.
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| 17. |
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| 18. |
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| 19. |
- Roy, Sushmita, et al.
(author)
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Identification of functional elements and regulatory circuits by Drosophila modENCODE.
- 2010
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In: Science (New York, N.Y.). - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 330:6012, s. 1787-1797
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Journal article (peer-reviewed)abstract
- To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
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| 20. |
- van Setten, Jessica, et al.
(author)
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PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity
- 2018
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 9
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Journal article (peer-reviewed)abstract
- Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genomewide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are overrepresented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of similar to 105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ionchannel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development.
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| 21. |
- Wiedmann, Mareike M., et al.
(author)
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Development of Cell-Permeable, Non-Helical Constrained Peptides to Target a Key Protein-Protein Interaction in Ovarian Cancer
- 2017
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In: Angewandte Chemie International Edition. - : Wiley. - 1433-7851 .- 1521-3773. ; 56:2, s. 524-529
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Journal article (peer-reviewed)abstract
- There is a lack of current treatment options for ovarian clear cell carcinoma (CCC) and the cancer is often resistant to platinum-based chemotherapy. Hence there is an urgent need for novel therapeutics. The transcription factor hepatocyte nuclear factor 1 beta (HNF1 beta) is ubiquitously overexpressed in CCC and is seen as an attractive therapeutic target. This was validated through shRNA-mediated knockdown of the target protein, HNF1 beta, in five high-and low-HNF1 beta-expressing CCC lines. To inhibit the protein function, cellpermeable, non-helical constrained proteomimetics to target the HNF1 beta-importin a protein-protein interaction were designed, guided by X-ray crystallographic data and molecular dynamics simulations. In this way, we developed the first reported series of constrained peptide nuclear import inhibitors. Importantly, this general approach may be extended to other transcription factors.
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