Polygenic risk modeling for prediction of epithelial ovarian cancer risk

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

FOXO4 regulates metastasis by binding to and suppressing RUNX2 transactivation ability.

<p><b>A.</b> Promoter regions of <i>RUNX2, PIP, PGC, PLA2G16</i> and <i>CAMK2N1</i> showing potential FOXO (DBE) and RUNX2 (RBS) binding sites relative to first exons. <b>B.</b> Matrigel invasion assay of LNCaP cells expressing control, FOXO4 or FOXO4 plus RUNX2 shRNAs. Error bars, S.E. of triplicate experiments. **, P<0.02. <b>C.</b> Relative RUNX2 RNA levels, as assessed by qRT-PCR in control shRNA vs. shFOXO4 LNCaP cells, primary tumors or LN metastases. RNA levels in each control condition were set to 1. Error bars, S.E. of triplicate experiments. n.s., not significant. Lysates of HEK293T cells transfected with HA-RUNX2 and Myc-FOXO4 were either analyzed by IB for HA, Myc or GAPDH, or immunoprecipitated with anti-myc and blotted with anti-HA (<b>D</b>), or immunoprecipitated with anti-HA and blotted with anti-Myc (<b>E</b>). <b>F.</b> Chromatin from LNCaP[vector] (control) or LNCaP[shFOXO4] cells were immunoprecipitated with control IgG or RUNX2 Ab, and the precipitated DNA subjected to qPCR using PIP promoter primers (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0101411#pone.0101411.s007" target="_blank">Table S2</a>). Error bars, S.E. of triplicates. **, P<0.01. <b>G.</b> Chromatin from HEK293T cells transfected with expression plasmids for RUNX2, RUNX2+FOXO4 or empty vector were immunoprecipitated with control IgG or HA Ab, then analyzed for PIP DNA by qPCR as in <b>F</b>.</p

Perceived outcomes of spiritual healing and explanations - a qualitative study on the perspectives of German healers and their clients

Background Limited research has been conducted on contemporary spiritual healing in European countries. The aim of this article is to report how German healers and their clients experienced and perceived the outcomes of spiritual healing and which explanations they use to describe the perceived effects. Methods Semistructured interviews and participatory observation was used to collect data from spiritual healers and their clients. Analyses were based on the methodological concept of directed qualitative content analysis. Data was analyzed using MAXQDA software, discussed and reviewed by a multidisciplinary research team consisting of medical anthropologists, medical doctors and a religious studies scholar. Results In total 15 healers and 16 clients participated in this study, 24 interviews with healers, 20 interviews with clients and 8 participatory observations were analyzed. Healers and clients reported outcomes as positively perceived body sensations, increased well-being, positive emotions and symptomatic relief of medical complaints. Clients often described changes in their self-concepts and adapted life values. Explanations for perceived effects included connecting with transcendent sources, construction of meaning, as a result of the client-healer relationship, and as empowerment to make changes. Because the interviewed clients were recruited by the healers, a selection bias towards positive healing experiences is possible. Conclusion We hypothesize that concepts of meaning construction, resource activation and the utilization of the clients’ expectations help to explain the data. Grounded in the emic perspective, we propose to use the following outcomes for further prospective studies: positive body sensations, changes of self-concepts and values, changes of medical symptoms and complaints. From the etic perspective, physical, emotional, social and spiritual wellbeing, sense of coherence, meaningfulness of life, empowerment, resource activation, change and symptom control should be further explored as potential outcomes

CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study.

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

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

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