MiRNA-guided diagnostics is a powerful molecular approach for evaluating clinical samples through miRNA detection and/or visualization. To date, this approach has been successfully used to diagnose, manage, and/or monitor a wide range of neoplastic and non-neoplastic diseases. Despite the promise of miRNA-guided diagnostics, particularly in the field of minimally invasive biomarkers, several knowledge and practical issues confound or hinder translation into routine clinical practice including: miRNA sequence database errors, suboptimal RNA extraction methods, detection assay variability, a vast array of online resources for bioinformatic analyses, and non-standardized statistical analyses for miRNA clinical testing. In this review, we raise awareness of these issues and recommend research directions to help specialists in endocrinology and metabolism integrate miRNA testing into clinical decision-making.

Sex and age associated differences in the tumor immune microenvironment of non-muscle invasive bladder (NMIBC) cancer and associated clinical outcomes are emerging indicators of treatment outcomes. The incidence of urothelial carcinoma of the bladder is four times higher in males than females; however, females tend to present with a more aggressive disease, a poorer response to immunotherapy and suffer worse clinical outcomes. Recent findings have demonstrated sex differences in the tumor immune microenvironment of non-muscle invasive and muscle invasive bladder cancer and associated clinical outcomes. However, a significant gap in knowledge remains with respect to the current pre-clinical modeling approaches to more precisely recapitulate these differences towards improved therapeutic design. Given the similarities in mucosal immune physiology between humans and mice, we evaluated the sex and age-related immune alterations in healthy murine bladders. Bulk-RNA sequencing and multiplex immunofluorescence-based spatial immune profiling of healthy murine bladders from male and female mice of age groups spanning young to old showed a highly altered immune landscape that exhibited sex and age associated differences, particularly in the context of B cell mediated responses. Spatial profiling of healthy bladders, using markers specific to macrophages, T cells, B cells, activated dendritic cells, high endothelial venules, myeloid cells and the PD-L1 immune checkpoint showed sex and age associated differences. Bladders from healthy older female mice also showed a higher presence of tertiary lymphoid structures (TLSs) compared to both young female and male equivalents. Spatial immune profiling of N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) carcinogen exposed male and female bladders from young and old mice revealed a similar frequency of TLS formation, sex differences in the bladder immune microenvironment and, age associated differences in latency of tumor induction. These findings support the incorporation of sex and age as factors in pre-clinical modeling of bladder cancer and will potentially advance the field of immunotherapeutic drug development to improve clinical outcomes.

Lung neuroendocrine neoplasms (NENs) can be challenging to classify due to subtle histologic differences between pathological types. MicroRNAs (miRNAs) are small RNA molecules that are valuable markers in many neoplastic diseases. To evaluate miRNAs as classificatory markers for lung NENs, we generated comprehensive miRNA expression profiles from 14 typical carcinoid (TC), 15 atypical carcinoid (AC), 11 small cell lung carcinoma (SCLC), and 15 large cell neuroendocrine carcinoma (LCNEC) samples, through barcoded small RNA sequencing. Following sequence annotation and data preprocessing, we randomly assigned these profiles to discovery and validation sets. Through high expression analyses, we found that miR-21 and -375 are abundant in all lung NENs, and that miR-21/miR-375 expression ratios are significantly lower in carcinoids (TC and AC) than in neuroendocrine carcinomas (NECs; SCLC and LCNEC). Subsequently, we ranked and selected miRNAs for use in miRNA-based classification, to discriminate carcinoids from NECs. Using miR-18a and -155 expression, our classifier discriminated these groups in discovery and validation sets, with 93% and 100% accuracy. We also identified miR-17, -103, and -127, and miR-301a, -106b, and -25, as candidate markers for discriminating TC from AC, and SCLC from LCNEC, respectively. However, these promising findings require external validation due to sample size.

Complex high-dimensional datasets that are challenging to analyze are frequently produced through ‘-omics’ profiling. Typically, these datasets contain more genomic features than samples, limiting the use of multivariable statistical and machine learning-based approaches to analysis. Therefore, effective alternative approaches are urgently needed to identify features-of-interest in ‘-omics’ data. In this study, we present the molecular feature selection tool, a novel, ensemble-based, feature selection application for identifying candidate biomarkers in ‘-omics’ data. As proof-of-principle, we applied the molecular feature selection tool to identify a small set of immune-related genes as potential biomarkers of three prostate adenocarcinoma subtypes. Furthermore, we tested the selected genes in a model to classify the three subtypes and compared the results to models built using all genes and all differentially expressed genes. Genes identified with the molecular feature selection tool performed better than the other models in this study in all comparison metrics: accuracy, precision, recall, and F1-score using a significantly smaller set of genes. In addition, we developed a simple graphical user interface for the molecular feature selection tool, which is available for free download. This user-friendly interface is a valuable tool for the identification of potential biomarkers in gene expression datasets and is an asset for biomarker discovery studies.

Type 1 von Willebrand disease (VWD) is associated with a reduction in qualitatively normal von Willebrand factor (VWF). Current diagnostic guidelines only take into consideration the contribution of basal VWF levels, despite a lack of correlation with bleeding severity. Defects in stimulated VWF release, which occurs after hemostatic challenge, may contribute to bleeding in type 1 VWD, but the pathogenic mechanisms are poorly defined. In this study, a layered multiomic approach including messenger RNA (mRNA) and microRNA (miRNA) sequencing was used to evaluate transcriptome-wide differences between type 1 VWD- and control-derived endothelial colony forming cells (ECFCs) during basal and stimulated VWF release. ECFCs from 8 patients with type 1 VWD and 4 other patients were included in this study as controls. VWF protein analysis revealed heterogenous responses to stimulation among type 1 VWD and control ECFCs. During basal VWF release, 64 mRNAs and 7 miRNAs were differentially regulated between type 1 VWD and control ECFCs, and 65 putatively pathogenic miRNA-mRNA interactions were identified. During stimulated VWF release, 190 mRNAs and 5 mRNAs were differentially regulated between type 1 VWD and control ECFCs, and 110 putatively pathogenic miRNA-mRNA interactions were identified. Five gene ontology terms including coagulation, regulation of cell shape, and regulation of cell signaling were also differentially regulated in type 1 VWD ECFCs during stimulated release. To our knowledge, we have shown for the first time that transcriptome-wide differences exist between type 1 VWD and control ECFCs. These differences may contribute to bleeding in type 1 VWD, and further investigation may reveal novel biomarkers and therapeutic targets.