Recent studies posit a role for non-coding RNAs in epithelial ovarian cancer (EOC). Combining small RNA sequencing from 179 human serum samples with a neural network analysis produced a miRNA algorithm for diagnosis of EOC (AUC 0.90; 95% CI: 0.81–0.99). The model significantly outperformed CA125 and functioned well regardless of patient age, histology, or stage. Among 454 patients with various diagnoses, the miRNA neural network had 100% specificity for ovarian cancer. After using 325 samples to adapt the neural network to qPCR measurements, the model was validated using 51 independent clinical samples, with a positive predictive value of 91.3% (95% CI: 73.3–97.6%) and negative predictive value of 78.6% (95% CI: 64.2–88.2%). Finally, biologic relevance was tested using in situ hybridization on 30 pre-metastatic lesions, showing intratumoral concentration of relevant miRNAs. These data suggest circulating miRNAs have potential to develop a non-invasive diagnostic test for ovarian cancer.

BackgroundSenescence is a fundamental biological process implicated in various pathologies, including cancer. Regarding carcinogenesis, senescence signifies, at least in its initial phases, an anti-tumor response that needs to be circumvented for cancer to progress. Micro-RNAs, a subclass of regulatory, non-coding RNAs, participate in senescence regulation. At the subcellular level micro-RNAs, similar to proteins, have been shown to traffic between organelles influencing cellular behavior. The differential function of micro-RNAs relative to their subcellular localization and their role in senescence biology raises concurrent in situ analysis of coding and non-coding gene products in senescent cells as a necessity. However, technical challenges have rendered in situ co-detection unfeasible until now.MethodsIn the present report we describe a methodology that bypasses these technical limitations achieving for the first time simultaneous detection of both a micro-RNA and a protein in the biological context of cellular senescence, utilizing the new commercially available SenTraGorTM compound. The method was applied in a prototypical human non-malignant epithelial model of oncogene-induced senescence that we generated for the purposes of the study. For the characterization of this novel system, we applied a wide range of cellular and molecular techniques, as well as high-throughput analysis of the transcriptome and micro-RNAs.ResultsThis experimental setting has three advantages that are presented and discussed: i) it covers a “gap” in the molecular carcinogenesis field, as almost all corresponding in vitro models are fibroblast-based, even though the majority of neoplasms have epithelial origin, ii) it recapitulates the precancerous and cancerous phases of epithelial tumorigenesis within a short time frame under the light of natural selection and iii) it uses as an oncogenic signal, the replication licensing factor CDC6, implicated in both DNA replication and transcription when over-expressed, a characteristic that can be exploited to monitor RNA dynamics.ConclusionsConsequently, we demonstrate that our model is optimal for studying the molecular basis of epithelial carcinogenesis shedding light on the tumor-initiating events. The latter may reveal novel molecular targets with clinical benefit. Besides, since this method can be incorporated in a wide range of low, medium or high-throughput image-based approaches, we expect it to be broadly applicable.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4375-1) contains supplementary material, which is available to authorized users.

Purpose: MicroRNAs (miRNAs) were hypothesized to be robust and easily measured biomarkers of radiation exposure, which has led to multiple studies in various clinical and experimental scenarios. We sought to identify evolutionary conserved, radiation-induced circulating miRNAs through a multispecies, integrative systematic review and meta-analysis of miRNAs in radiation. Methods and Materials: The systematic review was registered in the PROSPERO database (ID: 81701). We downloaded a list of studies with the query: (circulating OR plasma OR serum) AND (miRNA or microRNA) AND (radiat* OR radiotherapy OR irradiati*) from MEDLINE (103 studies), EMBASE (364 studies), and Cochrane Database of Systematic Reviews (0 studies). After deleting 116 duplicates, the remaining 351 abstracts were reviewed. Inclusion criteria were experimental study; human, mice, rat or nonhuman primate study; and serum or plasma miRNA expression measured before and after radiation exposure. Results: The screening procedure yielded 62 research studies. After verification, 30 articles contained data on miRNA expression change after irradiation. Thus, we obtained a database of 131 miRNAs from 96 pairwise post-/preirradiation comparisons reporting 2508 fold changes (FCs) of circulating miRNAs. The meta-analysis showed 28 miRNAs with significant radiation-induced change of their expression in the serum. In metaregression analysis, 7 miRNAsdmiR-150 (FC Z 0.40; 95% confidence interval [CI], 0.35-0.45), miR-29a (FC Z 0.87; 95% CI, 0.79-0.96), miR-29b (FC Z 0.85; 95% CI,

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The developed GDR estimation model reliant on ANN allows for an optimized prediction of GDR for research and clinical purposes.