Publications by authors named "R E FORTNER"
Identifying metabolomic mediators of the physical activity and colorectal cancer relationship.
Cancer Epidemiol Biomarkers Prev
January 2025
Background: Current evidence suggests higher physical activity (PA) levels are associated with a reduced risk of colorectal cancer (CRC). However, the mediating role of the circulating metabolome in this relationship remains unclear.
Methods: Targeted metabolomics data from 6,055 participants in the EPIC cohort were used to identify metabolites associated with PA and derive a metabolomic signature of PA levels.
Cancer diagnosis and therapy cause stress to the body. Preclinical studies have shown that stress hormones can stimulate tumor progression and metastasis by interacting with β-adrenergic receptors, and that β-blockers can inhibit those processes. We assessed if β-blocker use was associated with survival in a nationwide cohort of women with epithelial ovarian cancer (EOC).
View Article and Find Full Text PDFAims: Reproductive history conveys information about potential health risks later in adulthood. This study aimed to examine the validity of self-reported number of pregnancies and maternal age at first birth (AFB) among females attending BreastScreen Norway.
Methods: Participants were identified through the Janus Serum Bank cohort in Norway and were eligible for this cross-sectional validation study if they participated in a health survey issued by BreastScreen Norway between 2006 and 2015.
Background: Inflammation and immune dysregulation are hypothesized contributors to endometrial carcinogenesis; however, the precise underlying mechanisms remain unclear.
Methods: We measured pre-diagnostically 152 plasma protein biomarkers in 624 endometrial cancer case-control pairs nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Odds ratios (ORs) were estimated using conditional logistic regression, accounting for confounding and multiple comparisons.
Article Synopsis
- Effective strategies for early detection of epithelial ovarian cancer are currently insufficient; this study assessed a panel of 14 circulating microRNAs to differentiate between ovarian cancer cases diagnosed less than 2 years and those diagnosed 2-7 years after serum collection.
- The study involved 80 ovarian cancer cases and used the XGBoost algorithm to create a binary classification model, training it on 70% of the data and testing it on the remaining 30%.
- Results showed the microRNA panel performed well, with a median AUC of 0.771, and identified four specific miRNAs that were significantly upregulated closer to the diagnosis, indicating potential for robust early detection of ovarian cancer.