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- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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- Kang, E. Y., et al.
(author)
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CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study
- 2023
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In: Cancer. - : Wiley. - 0008-543X .- 1097-0142. ; 129:5, s. 697-713
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Journal article (peer-reviewed)abstract
- Background: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC. Methods: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated. Results: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss. Conclusion: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.
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- Kang, E. Y., et al.
(author)
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MCM3 is a novel proliferation marker associated with longer survival for patients with tubo-ovarian high-grade serous carcinoma
- 2022
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In: Virchows Archiv. - : Springer Science and Business Media LLC. - 0945-6317 .- 1432-2307. ; 480, s. 855-871
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Journal article (peer-reviewed)abstract
- Tubo-ovarian high-grade serous carcinomas (HGSC) are highly proliferative neoplasms that generally respond well to platinum/taxane chemotherapy. We recently identified minichromosome maintenance complex component 3 (MCM3), which is involved in the initiation of DNA replication and proliferation, as a favorable prognostic marker in HGSC. Our objective was to further validate whether MCM3 mRNA expression and possibly MCM3 protein levels are associated with survival in patients with HGSC. MCM3 mRNA expression was measured using NanoString expression profiling on formalin-fixed and paraffin-embedded tissue (N = 2355 HGSC) and MCM3 protein expression was assessed by immunohistochemistry (N = 522 HGSC) and compared with Ki-67. Kaplan-Meier curves and the Cox proportional hazards model were used to estimate associations with survival. Among chemotherapy-naive HGSC, higher MCM3 mRNA expression (one standard deviation increase in the score) was associated with longer overall survival (HR = 0.87, 95% CI 0.81-0.92, p < 0.0001, N = 1840) in multivariable analysis. MCM3 mRNA expression was highest in the HGSC C5.PRO molecular subtype, although no interaction was observed between MCM3, survival and molecular subtypes. MCM3 and Ki-67 protein levels were significantly lower after exposure to neoadjuvant chemotherapy compared to chemotherapy-naive tumors: 37.0% versus 46.4% and 22.9% versus 34.2%, respectively. Among chemotherapy-naive HGSC, high MCM3 protein levels were also associated with significantly longer disease-specific survival (HR = 0.52, 95% CI 0.36-0.74, p = 0.0003, N = 392) compared to cases with low MCM3 protein levels in multivariable analysis. MCM3 immunohistochemistry is a promising surrogate marker of proliferation in HGSC.
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- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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- 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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- 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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9. |
- Escala-Garcia, Maria, et al.
(author)
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A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
- 2020
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
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10. |
- Kapoor, Pooja Middha, et al.
(author)
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Combined associations of a polygenic risk score and classical risk factors with breast cancer risk
- 2021
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 113:3, s. 329-337
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Journal article (peer-reviewed)abstract
- We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
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