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Introduction: Effective strategies for early detection of epithelial ovarian cancer are lacking. We evaluated whether a panel of 14 previously established circulating microRNAs could discriminate between cases diagnosed <2 years after serum collection and those diagnosed 2-7 years after serum collection. miRNA sequencing data from subsequent ovarian cancer cases were obtained as part of the ongoing multi-cancer JanusRNA project, utilizing pre-diagnostic serum samples from the Janus Serum Bank and linked to the Cancer Registry of Norway for cancer outcomes. Methods: We included a total of 80 ovarian cancer cases contributing 80 serum samples and compared 40 serum samples from cases with samples collected <2 years prior to diagnosis with 40 serum samples from cases with sample collection =2 to 7 years. We employed the extreme gradient boosting (XGBoost) algorithm to train a binary classification model using 70% of the available data, while the model was tested on the remaining 30% of the dataset. Results: The performance of the model was evaluated using repeated holdout validation. The previously established set of miRNAs achieved a median area under the receiver operating characteristic curve (AUC) of 0.771 in the test sets. Four out of 14 miRNAs (hsa-miR-200a-3p, hsa-miR-1246, hsa-miR-203a-3p, hsa-miR-23b-3p) exhibited higher expression levels closer to diagnosis, consistent with the previously reported upregulation in cancer cases, with statistical significance observed only for hsa-miR-200a-3p (beta=0.14; p=0.04). Discussion: The discrimination potential of the selected models provides evidence of the robustness of the miRNA signature for ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: It has been hypothesized that poorly functioning Leydig and/or Sertoli cells of the testes, indicated by higher levels of serum gonadotropins and lower levels of androgens, are related to the development of testicular germ cell tumors (TGCT). To investigate this hypothesis, we conducted a nested case-control study within the Janus Serum Bank cohort. Methods: Men who developed TGCT (n = 182) were matched to men who did not (n = 364). Sex steroid hormones were measured using LC/MS. Sex hormone binding globulin, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were quantified by direct immunoassay. Multivariable logistic regression was used to calculate ORs and 95% confidence intervals (CI) for associations between hormone levels and TGCT risk. Results: Higher FSH levels [tertile (T) 3 vs. T2: OR = 2.89, 95% CI = 1.83-4.57] were associated with TGCT risk, but higher LH levels were not (OR = 1.26, 95% CI = 0.81-1.96). The only sex steroid hormone associated with risk was androstane-3a, 17ß-diol-3G (3a-diol-3G; OR = 2.37, 95% CI = 1.46-3.83). Analysis by histology found that increased FSH levels were related to seminoma (OR = 3.55, 95% CI = 2.12-5.95) but not nonseminoma (OR = 1.19, 95% CI = 0.38-3.13). Increased levels of 3a-diol-3G were related to seminoma (OR = 2.29, 95% CI = 1.35-3.89) and nonsignificantly related to nonseminoma (OR = 2.71, 95% CI = 0.82-8.92). Conclusions: Higher FSH levels are consistent with the hypothesis that poorly functioning Sertoli cells are related to the development of TGCT. In contrast, higher levels of 3a-diol-3G do not support the hypothesis that insufficient androgenicity is related to risk of TGCT. Impact: Clarifying the role of sex hormones in the development of TGCT may stimulate new research hypotheses. [ABSTRACT FROM AUTHOR]

For cancers and other pathologies, early diagnosis remains the most promising path to survival. Profiling of longitudinal cohorts facilitates insights into trajectories of biomarkers. We measured microRNA expression in 240 serum samples from patients with colon, lung, and breast cancer and from cancer-free controls. Each patient provided at least two serum samples, one prior to diagnosis and one following diagnosis. The median time interval between the samples was 11.6 years. Using computational models, we evaluated the circulating profiles of 21 microRNAs. The analysis yielded two sets of biomarkers, static ones that show an absolute difference between certain cancer types and controls and dynamic ones where the level over time provided higher diagnostic information content. In the first group, miR-99a-5p stands out for all three cancer types. In the second group, miR-155-5p allows to predict lung cancers and colon cancers. Classification in samples from cancer and non-cancer patients using gradient boosted trees reached an average accuracy of 79.9%. The results suggest that individual change over time or an absolute value at one time point may predict a disease with high specificity and sensitivity. [ABSTRACT FROM AUTHOR]

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.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. Retrospective self-reported survey information on number of pregnancies and AFB in years was validated against prospectively collected information from the Medical Birth Registry of Norway (MBRN) using the Spearman rank (rs) and intraclass correlation coefficients (ICC) with 95% confidence intervals (CI).After exclusions, 51,598 subjects were included in the analysis on number of pregnancies and 46,919 in the analysis on AFB. On average, study subjects were 59–60 years old when completing the health survey and had become first-time mothers roughly 36 years earlier. Survey-based information about number of pregnancies was highly correlated and demonstrated high agreement with the registry data (rs=0.967, 95% CI 0.964–0.969; ICC=0.884, 95% CI 0.882–0.885). Survey-based information about AFB demonstrated even higher correlation and very high agreement with the registry data (rs=0.975, 95% CI 0.973–0.976; ICC=0.974, 95% CI 0.974–0.975). Retrospectively recalled survey-based information about number of pregnancies and AFB was highly accurate when validated against prospectively collected information in the MBRN. These survey-based data are valuable for future epidemiological research, and linkage to the MBRN may not be required when these data are available. [ABSTRACT FROM AUTHOR]