The identification of body fluids is an important area of forensic genetics. In particular, the susceptibility to degradation of casework samples is of crucial importance, as the traces can often be exposed to different environmental conditions over a long period of time. RNAs especially are used as molecular markers for the identification of body fluids in forensics. Messenger RNAs (mRNAs) show an increased susceptibility to degradation, e.g. under humidity and UV radiation but are highly body fluid-specific. The shorter micro RNAs (miRNAs), however, are less susceptible to degradation, but only a few body fluid-specific markers could be investigated. In this study, a self-developed mRNA/miRNA multiplex assay for capillary electrophoresis from a preliminary study was further adapted and validated. The approach was applied to casework samples, animal samples, and a storage study. The advantages and disadvantages of the mRNA/miRNA assay were investigated in order to review a possible application for forensic casework. Some miRNA markers were also detected in animal samples, which once again underlines the possible non-specificity of miRNAs. In the storage study, the different markers were detected for different lengths of time depending on the body fluid examined. For almost all body fluids, the miRNA markers were still detectable after a period of 35 days under environmental conditions compared to the mRNA markers. The mRNA peaks were often already clearly reduced or no longer detectable after 14 days. The results show the advantage of the new mRNA/miRNA assay compared to established mRNA approaches, especially for older and degraded samples, but the assay has its limitations due to the limited number of specific miRNA markers.

Genomic instability is one of the main drivers of tumorigenesis and the development of hematological malignancies. Cancer cells can remedy chemotherapeutic-induced DNA damage by upregulating DNA-repair genes and ultimately inducing therapy resistance. Nevertheless, the association between the DNA-repair genes, drug resistance, and disease relapse has not been well characterized in acute lymphoblastic leukemia (ALL). This study aimed to explore the role of the DNA-repair machinery and the molecular mechanisms by which it is regulated in early- and late-relapsing pediatric ALL patients. We performed secondary data analysis on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET)-ALL expansion phase II trial of 198 relapsed pediatric precursor B-cell ALL. Comprehensive genetic and epigenetic investigations of 147 DNA-repair genes were conducted in the study. Gene expression was assessed using Microarray and RNA-sequencing platforms. Genomic alternations, methylation status, and miRNA transcriptome were investigated for the candidate DNA-repair genes. We identified three DNA-repair genes, ALKBH3, NHEJ1, and PARP1, that were upregulated in early relapsers compared to late relapsers (p < 0.05). Such upregulation at diagnosis was significantly associated with disease-free survival and overall survival in precursor-B-ALL (p < 0.05). Moreover, PARP1 upregulation accompanied a significant downregulation of its targeting miRNA, miR-1301-3p (p = 0.0152), which was strongly linked with poorer disease-free and overall survivals. Upregulation of DNA-repair genes, PARP1 in particular, increases the likelihood of early relapse of precursor-B-ALL in children. The observation that PARP1 was upregulated in early relapsers relative to late relapsers might serve as a valid rationale for proposing alternative treatment approaches, such as using PARP inhibitors with chemotherapy.

BACKGROUND: This multi-center study aims to explore the roles of plasma exosomal microRNAs (miRNAs), ultrasound (US) radiomics, and total prostate-specific antigen (tPSA) levels in early prostate cancer detection.
METHODS: We analyzed the publicly available dataset GSE112264 to identify the differentially expressed miRNAs associated with prostate cancer. Then, PyRadiomics was used to extract image features, and least absolute shrinkage and selection operator (LASSO) was used to screen the data. Subsequently, according to strict inclusion and exclusion criteria, the internal dataset (n = 199) was used to construct a diagnostic model, and the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and DeLong test were used to evaluate its diagnostic performance. Finally, we used an external dataset (n = 158) for further validation.
RESULTS: The number of features extracted by PyRadiomics was 851, and the number of features screened by LASSO was 23. We combined the hsa-miR-320c, hsa-miR-944, radiomics, and tPSA features to construct a joint model. The area under the ROC curve of the combined model was 0.935. In the internal validation, the area under the curve (AUC) of the training set was 0.943, and the AUC of the test set was 0.946. The AUC of the external data set was 0.910. The calibration curve and decision curve were consistent with the performance of the combined model. There was a significant difference in the prediction ability between the combined prediction model and the single index prediction model, indicating the high credibility and accuracy of the combined model in predicting PCa.
CONCLUSIONS: The combined prediction model, consisting of plasma exosomal miRNAs (hsa-miR-320c and hsa-miR-944), US radiomics, and clinical tPSA, can be utilized for the early diagnosis of prostate cancer.

BACKGROUND: The ability to differentiate sporadic primary hyperparathyroidism (sPHPT) caused by a single parathyroid adenoma (PTA) from multiglandular disease (MGD) pre-operatively, as well as definitely diagnose sPHPT in difficult patients, would enhance surgical decision making.
OBJECTIVE: Identify miRNA (miR) signatures for MGD, single- and double-PTA, as well as cell-free miRNA (cfmiR) in plasma samples from patients with single-PTAs to use as biomarkers.
METHODS: 47 patients with sPHPT (single-PTA n=32, double-PTA n=12, MGD n=9). Pre-operative plasma samples from 16 single-PTA and 29 normal healthy donors (NHD).
METHODS: All specimens were processed and analyzed for 2,083 miRs using HTG EdgeSeq miR whole transcriptome assay and normalized using DESeq2 to identify differentially expressed (DE) miRs. MiR classifiers were identified using Random Forest.
METHODS: ROC curves and AUC.
RESULTS: MiR signatures distinguished normal parathyroid from MGD and PTA as well as MGD from PTA in tissue samples. Common miRs were found in the single-PTA and double-PTAs. Data integration identified a 27-miR signature in single-PTA tissue samples compared to the rest of the tissue samples. In plasma samples analysis, significant cfmiRs were DE in single-PTA patients compared to NHD. Of those, only 9 miRNAs/cfmiRs were found DE in both tissue and plasma samples from patients diagnosed with a single-PTA (AUC=76%).
CONCLUSIONS: Twenty-seven miRs were consistently found DE in single-PTA tissue and plasma samples. Data integration showed a 9-cfmiR signature with potential clinical utility to pre-operatively diagnose sPHPT caused by a single-PTA, which could decrease more invasive parathyroid explorations.

BACKGROUND: The identification of specific circulating miRNAs has been proposed as a valuable tool for elucidating the pathophysiology of brain damage or injury and predicting patient outcomes.
OBJECTIVE: This study aims to apply several bioinformatic tools in order to clarify miRNA interactions with potential genes involved in brain injury, emphasizing the need of using a computational approach to determine the most likely correlations between miRNAs and target genes. Specifically, this study centers on elucidating the roles of miR-34b, miR-34c, miR-135a, miR-200c, and miR-451a.
METHODS: After a careful evaluation of different software available (analyzing the strengths and limitations), we applied three tools, one to perform an analysis of the validated targets (miRTarBase), and two to evaluate functional annotations (miRBase and TAM 2.0).
RESULTS: Research findings indicate elevated levels of miR-135a and miR-34b in patients with traumatic brain injury (TBI) within the first day post-injury, while miR-200c and miR-34c were found to be upregulated after 7 days. Moreover, miR-451a and miR-135a were found overexpressed in the serum, while miRNAs 34b, 34c, and 200c, had lower serum levels at baseline post brain injury.
CONCLUSIONS: This study emphasizes the use of computational methods in determining the most likely relationships between miRNAs and target genes by investigating several bioinformatic techniques to elucidate miRNA interactions with potential genes. Specifically, this study focuses on the functions of miR-34b, miR-34c, miR-135a, miR-200c, and miR-451a, providing an up-to-date overview and suggesting future research directions for identifying theranomiRNAs related to brain injury, both at the tissue and serum levels.

This investigation delves into the influence of predicted microRNAs on DNA methyltransferases (DNMTs) and the PODXL gene within the NB4 cell line, aiming to elucidate their roles in the pathogenesis of acute myeloid leukemia (AML). A comprehensive methodological framework was adopted to explore the therapeutic implications of 6-gingerol on DNMTs. This encompassed a suite of bioinformatics tools for protein structure prediction, docking, molecular dynamics, and ADMET profiling, alongside empirical assessments of miRNA and PODXL expression levels. Such a multifaceted strategy facilitated an in-depth understanding of 6-gingerol\'s potential efficacy in DNMT modulation. The findings indicate a nuanced interplay where 6-gingerol administration modulated miRNA expression levels, decreasing in DNMT1 and DNMT3A expression in NB4 cells. This alteration indirectly influenced PODXL expression, contributing to the manifestation of oncogenic phenotypes. The overexpression of DNMT1 and DNMT3A in NB4 cells may contribute to AML, which appears modulable via microRNAs such as miR-193a and miR-200c. Post-treatment with 6-gingerol, DNMT1 and DNMT3A expression alterations were observed, culminating in the upregulation of miR-193a and miR-200c. This cascade effect led to the dysregulation of tumor suppressor genes in cancer cells, including downregulation of PODXL, and the emergence of cancerous traits. These insights underscore the therapeutic promise of 6-gingerol in targeting DNMTs and microRNAs within the AML context.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) are commonly coexisting clinical entities with still growing incidence worldwide. Recently, circulating microRNAs (miRNAs) have emerged as novel molecular players in cardiometabolic diseases. This study aimed to identify a specific miRNA signature as a candidate biomarker for CAD in T2DM and to delineate potential miRNA-dependent mechanisms contributing to diabetic atherosclerosis.
METHODS: A total of 38 plasma samples from T2DM patients with and without CAD, CAD patients and healthy controls were collected for expression profiling of 2,578 miRNAs using microarrays. To investigate the regulatory role of differentially expressed (DE)-miRNA target genes, functional annotation and pathway enrichment analyses were performed utilizing multiple bioinformatics tools. Then, protein-protein interaction networks were established leveraging the STRING database in Cytoscape software, followed by cluster analysis and hub gene identification. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was carried out for microarray data validation in the larger replication cohort of 94 participants. Receiver operating characteristic analysis was applied to evaluate the diagnostic values of miRNAs. Multivariate logistic regression analysis was used to develop miRNA-based diagnostic models.
RESULTS: In the discovery stage, overexpression of hsa-miR-4505, hsa-miR-4743-5p, hsa-miR-6846-5p, and down-regulation of hsa-miR-3613-3p, hsa-miR-4668-5p, hsa-miR-4706, hsa-miR-6511b-5p, hsa-miR-6750-5p, hsa-miR-4750-3p, hsa-miR-320e, hsa-miR-4717-3p, hsa-miR-7850-5p were detected in T2DM-CAD patients. The DE-miRNA target genes were significantly enriched in calcium ion binding, regulation of actin cytoskeleton, and gene expression. hsa-miR-4505, hsa-miR-4743-5p, and hsa-miR-4750-3p were found to be involved in fatty acid metabolism, leukocyte transendothelial migration, and neurotrophin signaling pathway. Dysregulation of hsa-miR-4505, hsa-miR-4743-5p, and hsa-miR-4750-3p in T2DM-CAD patients compared with T2DM subjects and controls (all p < 0.001) was further confirmed by RT-qPCR. All validated miRNAs demonstrated good discriminatory values for T2DM-CAD (AUC = 0.833-0.876). The best performance in detecting CAD in T2DM was achieved for a combination of three miRNAs (AUC = 0.959, 100% sensitivity, 86.67% specificity).
CONCLUSIONS: Our study revealed a unique profile of plasma-derived miRNAs in T2DM patients with CAD. Potential miRNA-regulated pathways were also identified, exploring the underlying pathogenesis of CAD in T2DM. We developed a specific three-miRNA panel of hsa-miR-4505, hsa-miR-4743-5p and hsa-miR-4750-3p, that could serve as a novel non-invasive biomarker for CAD in patients with T2DM.

Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, delusions, thought disorder and movement disorder. These symptoms are in common with some other psychiatric disorders such as bipolar disorder, major depressive disorder and mood spectrum disorder. As patients would require immediate treatment, an on-time diagnosis is critical. This study explores the use of omics data in diagnosis of schizophrenia. Transcriptome, miRNA and epigenome data are used in diagnosis of patients with schizophrenia with the aid of machine learning algorithms. As the data is in high dimension, mutual information and feature importance are independently used for selecting relevant features for the study. Selected sets of features (biomarkers) are individually used with different machine learning algorithms and their performances are compared to select the best-performing model. This study shows that the top 140 miRNA features selected using mutual information along with support vector machines give the highest accuracy (0.86 ± 0.07) in the diagnosis of schizophrenia. All reported accuracies are validated using 5-fold cross validation. They are further validated using leave one out cross validation and the accuracies are reported in the supplementary material.

The laying hen is the spontaneous model of ovarian tumor. A comprehensive comparison based on RNA-seq from hens and women may shed light on the molecular mechanisms of ovarian cancer. We performed next-generation sequencing of microRNA and mRNA expression profiles in 9 chicken ovarian cancers and 4 normal ovaries, which has been deposited in GSE246604. Together with 6 public datasets (GSE21706, GSE40376, GSE18520, GSE27651, GSE66957, TCGA-OV), we conducted a comparative transcriptomics study between chicken and human. In the present study, miR-451, miR-2188-5p, and miR-10b-5p were differentially expressed in normal ovaries, early- and late-stage ovarian cancers. We also disclosed 499 up-regulated genes and 1,061 down-regulated genes in chicken ovarian cancer. The molecular signals from 9 cancer hallmarks, 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and 369 Gene Ontology (GO) pathways exhibited abnormalities in ovarian cancer compared to normal ovaries via Gene Set Enrichment Analysis (GSEA). In the comparative analysis across species, we have uncovered the conservation of 5 KEGG and 76 GO pathways between chicken and human including the mismatch repair and ECM receptor interaction pathways. Moreover, a total of 174 genes contributed to the core enrichment for these KEGG and GO pathways were identified. Among these genes, the 22 genes were found to be associated with overall survival in patients with ovarian cancer. In general, we revealed the microRNA profiles of ovarian cancers in hens and updated the mRNA profiles previously derived from microarrays. And we also disclosed the molecular pathways and core genes of ovarian cancer shared between hens and women, which informs model animal studies and gene-targeted drug development.

BACKGROUND: Hexavalent chromium (Cr(Ⅵ)) is classified as a group 1 human carcinogen and increases the risk of lung cancer. Non-coding RNAs (ncRNAs) have key regulatory roles in lung cancer, but less is known about their relation to Cr(Ⅵ) exposure.
OBJECTIVE: We aimed to 1) measure the expression of lung cancer-related circulating ncRNAs in exposed workers and controls; 2) assess associations between ncRNAs expression and Cr concentrations in red blood cells (RBC) and urine; and 3) evaluate correlations between the ncRNAs.
METHODS: The study included 111 Cr(VI) exposed workers and 72 controls recruited from the SafeChrom project. Cr concentrations were measured in RBC (biomarker of long-term exposure) and urine (biomarker of short-term exposure) samples. Long ncRNA (lncRNA) and microRNA (miRNA) were extracted from plasma followed by deoxyribonuclease treatment, complementary DNA synthesis, and quantitative real-time polymerase chain reaction using target-specific assays for three lncRNAs (H19, MALAT1, NORAD), and four miRNAs (miR-142-3p, miR-15b-5p, miR-3940-5p, miR-451a).
RESULTS: Expression levels of lncRNAs MALAT1 and NORAD, and all four miRNAs, were significantly lower in Cr(VI) exposed workers compared with controls, and correlated significantly with RBC-Cr concentrations (rS = -0.16 to -0.38). H19 was non-significantly increased in exposed workers but significantly correlated with miR-142-3p (rS = -0.33) and miR-15b-5p (rS = -0.30), and NORAD was significantly positively correlated with all four miRNAs (rS = 0.17 to 0.46). In multivariate regression models adjusting for confounders, expressions of lncRNAs MALAT1 and NORAD and all miRNAs were still significantly lower in the exposed group compared with controls, and the expression decreased with increasing RBC-Cr concentrations.
CONCLUSIONS: Cr(VI) exposure was inversely and in a dose-response manner associated with the expression of circulating non-coding RNA, which suggests ncRNAs as potential biomarkers for Cr(VI)-induced toxicity. Correlations between miRNAs and lncRNAs suggest that they participate in the same lncRNA-miRNA-messenger RNA regulatory axes, which may play important roles in Cr(VI) carcinogenesis.