Evaluating [18F]FDG and [18F]FLT Radiotracers as Biomarkers of Response for Combined Therapy Outcome in Triple-Negative and Estrogen-Receptor-Positive Breast Cancer Models.

Breast cancer (BC) is the most frequent cancer and the second leading cause of death in women. A typical feature of BC cells is the metabolic shift toward increased glycolysis, which has become an interesting therapeutic target for metabolic drugs such as metformin (MET). Recently, the administration of the antihypertensive syrosingopine (SYRO) in combination with MET has shown a synergistic effect toward a variety of cancers. However, a fundamental need remains, which is the development of in vivo biomarkers that are able to detect early clinical response. In this study, we exploited a triple-negative murine BC cell line (4T1) and a metastatic ER+ murine BC cell line (TS/A) in order to investigate, in vivo, the early response to treatment, based on MET and/or SYRO administration, evaluating [18F]FDG and [18F]FLT as potential biomarkers via PET/CT. The study provides evidence that SYRO plus MET has a synergistic effect on tumor growth inhibition in both 4T1 and TS/A experimental models and has showed the highest efficacy on the TNBC xenograft mice (4T1) via the expression reduction in the lactate transporter MCT4 and in the epithelial-mesenchymal transition biomarker Snail, promoting its potential application in therapy settings. In addition, the selective reduction in the [18F]FLT tumor uptake (at 7 dd), observed in the SYRO plus MET treated mice in comparison with the vehicle group, suggests that this radiotracer could be potentially used as a biomarker for the early detection of therapy response, in both evaluated xenografts models.

Non-Coding RNAs: New Biomarkers and Therapeutic Targets for Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy; it is considered a network disorder associated with structural changes. Incomplete knowledge of the pathological changes in TLE complicates a therapeutic approach; indeed, 30 to 50% of patients with TLE are refractory to drug treatment. Non-coding RNAs (ncRNAs), acting as epigenetic factors, participate in the regulation of the pathophysiological processes of epilepsy and are dysregulated during epileptogenesis. Abnormal expression of ncRNA is observed in patients with epilepsy and in animal models of epilepsy. Furthermore, ncRNAs could also be used as biomarkers for the diagnosis and prognosis of treatment response in epilepsy. In summary, ncRNAs can represent important mechanisms and targets for the modulation of brain excitability and can provide information on pathomechanisms, biomarkers and novel therapies for epilepsy. In this review, we summarize the latest research advances concerning mainly molecular mechanisms, regulated by ncRNA, such as synaptic plasticity, inflammation and apoptosis, already associated with the pathogenesis of TLE. Moreover, we discuss the role of ncRNAs, such as microRNAs, long non-coding RNAs and circular RNAs, in the pathophysiology of epilepsy, highlighting their use as potential biomarkers for future therapeutic approaches.

Secreted miR-153 Controls Proliferation and Invasion of Higher Gleason Score Prostate Cancer.

Prostate cancer (PC) is a male common neoplasm and is the second leading cause of cancer death in American men. PC is traditionally diagnosed by the evaluation of prostate secreted antigen (PSA) in the blood. Due to the high levels of false positives, digital rectal examination and transrectal ultrasound guided biopsy are necessary in uncertain cases with elevated PSA levels. Nevertheless, the high mortality rate suggests that new PC biomarkers are urgently needed to help clinical diagnosis. In a previous study, we have identified a network of genes, altered in high Gleason Score (GS) PC (GS ≥ 7), being regulated by miR-153. Until now, no publication has explained the mechanism of action of miR-153 in PC. By in vitro studies, we found that the overexpression of miR-153 in high GS cell lines is required to control cell proliferation, migration and invasion rates, targeting Kruppel-like factor 5 (KLF5). Moreover, miR-153 could be secreted by exosomes and microvesicles in the microenvironment and, once entered into the surrounding tissue, could influence cellular growth. Being upregulated in high GS human PC, miR-153 could be proposed as a circulating biomarker for PC diagnosis.

Identification of microRNA clusters cooperatively acting on epithelial to mesenchymal transition in triple negative breast cancer.

MicroRNAs play important roles in many biological processes. Their aberrant expression can have oncogenic or tumor suppressor function directly participating to carcinogenesis, malignant transformation, invasiveness and metastasis. Indeed, miRNA profiles can distinguish not only between normal and cancerous tissue but they can also successfully classify different subtypes of a particular cancer. Here, we focus on a particular class of transcripts encoding polycistronic miRNA genes that yields multiple miRNA components. We describe 'clustered MiRNA Master Regulator Analysis (ClustMMRA)', a fully redesigned release of the MMRA computational pipeline (MiRNA Master Regulator Analysis), developed to search for clustered miRNAs potentially driving cancer molecular subtyping. Genomically clustered miRNAs are frequently co-expressed to target different components of pro-tumorigenic signaling pathways. By applying ClustMMRA to breast cancer patient data, we identified key miRNA clusters driving the phenotype of different tumor subgroups. The pipeline was applied to two independent breast cancer datasets, providing statistically concordant results between the two analyses. We validated in cell lines the miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative breast cancer (TNBC) phenotype through its control of proliferation and EMT.

Circulating microRNA: The Potential Novel Diagnostic Biomarkers to Predict Drug Resistance in Temporal Lobe Epilepsy, a Pilot Study.

MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as new potential epigenetic biomarkers. Here, we evaluate the efficacy of six circulating miRNA previously described in the literature as biomarkers for the diagnosis of temporal lobe epilepsy (TLE) and/or as predictive biomarkers to antiepileptic drug response. We measured the differences in serum miRNA levels by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays in a cohort of 27 patients (14 women and 13 men; mean ± SD age: 43.65 ± 17.07) with TLE compared to 20 healthy controls (HC) matched for sex, age and ethnicity (11 women and 9 men; mean ± SD age: 47.5 ± 9.1). Additionally, patients were classified according to whether they had drug-responsive (n = 17) or drug-resistant (n = 10) TLE. We have investigated any correlations between miRNAs and several electroclinical parameters. Three miRNAs (miR-142, miR-146a, miR-223) were significantly upregulated in patients (expressed as average expression ± SD). In detail, miR-142 expression was 0.40 ± 0.29 versus 0.16 ± 0.10 in TLE patients compared to HC (t-test, p < 0.01), miR-146a expression was 0.15 ± 0.11 versus 0.07 ± 0.04 (t-test, p < 0.05), and miR-223 expression was 6.21 ± 3.65 versus 1.23 ± 0.84 (t-test, p < 0.001). Moreover, results obtained from a logistic regression model showed the good performance of miR-142 and miR-223 in distinguishing drug-sensitive vs. drug-resistant TLE. The results of this pilot study give evidence that miRNAs are suitable targets in TLE and offer the rationale for further confirmation studies in larger epilepsy cohorts.

Molecular and Cellular Complexity of Glioma. Focus on Tumour Microenvironment and the Use of Molecular and Imaging Biomarkers to Overcome Treatment Resistance.

This review highlights the importance and the complexity of tumour biology and microenvironment in the progression and therapy resistance of glioma. Specific gene mutations, the possible functions of several non-coding microRNAs and the intra-tumour and inter-tumour heterogeneity of cell types contribute to limit the efficacy of the actual therapeutic options. In this scenario, identification of molecular biomarkers of response and the use of multimodal in vivo imaging and in particular the Positron Emission Tomography (PET) based molecular approach, can help identifying glioma features and the modifications occurring during therapy at a regional level. Indeed, a better understanding of tumor heterogeneity and the development of diagnostic procedures can favor the identification of a cluster of patients for personalized medicine in order to improve the survival and their quality of life.

In Silico Approach for the Definition of radiomiRNomic Signatures for Breast Cancer Differential Diagnosis.

Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling. BACKGROUND: Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype. METHODS: We describe a computational approach that correlates phenotype from magnetic resonance imaging (MRI) of breast cancer (BC) lesions with microRNAs (miRNAs), mRNAs, and regulatory networks, developing a radiomiRNomic map. We validated our approach to the relationships between MRI and miRNA expression data derived from BC patients. We obtained 16 radiomic features quantifying the tumor phenotype. We integrated the features with miRNAs regulating a network of pathways specific for a distinct BC subtype. RESULTS: We found six miRNAs correlated with imaging features in Luminal A (miR-1537, -205, -335, -337, -452, and -99a), seven miRNAs (miR-142, -155, -190, -190b, -1910, -3617, and -429) in HER2+, and two miRNAs (miR-135b and -365-2) in Basal subtype. We demonstrate that the combination of correlated miRNAs and imaging features have better classification power of Luminal A versus the different BC subtypes than using miRNAs or imaging alone. CONCLUSION: Our computational approach could be used to identify new radiomiRNomic profiles of multi-omics biomarkers for BC differential diagnosis and prognosis.

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

BACKGROUND: Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. RESULTS: We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. CONCLUSIONS: Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

In silico identification of drug target pathways in breast cancer subtypes using pathway cross-talk inhibition.

BACKGROUND: Despite great development in genome and proteome high-throughput methods, treatment failure is a critical point in the management of most solid cancers, including breast cancer (BC). Multiple alternative mechanisms upon drug treatment are involved to offset therapeutic effects, eventually causing drug resistance or treatment failure. METHODS: Here, we optimized a computational method to discover novel drug target pathways in cancer subtypes using pathway cross-talk inhibition (PCI). The in silico method is based on the detection and quantification of the pathway cross-talk for distinct cancer subtypes. From a BC data set of The Cancer Genome Atlas, we have identified different networks of cross-talking pathways for different BC subtypes, validated using an independent BC dataset from Gene Expression Omnibus. Then, we predicted in silico the effects of new or approved drugs on different BC subtypes by silencing individual or combined subtype-derived pathways with the aim to find new potential drugs or more effective synergistic combinations of drugs. RESULTS: Overall, we identified a set of new potential drug target pathways for distinct BC subtypes on which therapeutic agents could synergically act showing antitumour effects and impacting on cross-talk inhibition. CONCLUSIONS: We believe that in silico methods based on PCI could offer valuable approaches to identifying more tailored and effective treatments in particular in heterogeneous cancer diseases.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer.

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC.

MicroRNA-567 dysregulation contributes to carcinogenesis of breast cancer, targeting tumor cell proliferation, and migration.

PURPOSE: We demonstrated that Hsa-miR-567 expression is significantly downregulated in poor prognosis breast cancer, compared to better prognosis breast cancer, having a role in the control of cell proliferation and migration by regulating KPNA4 gene. METHODS AND RESULTS: In this study, based on our previously published in silico results, we proved both in vitro (cell line studies) and ex vivo (clinical studies), that Hsa-miR-567 expression is significantly downregulated in breast cancer with poor prognosis when compared to breast cancer with better prognosis. More intriguingly, we demonstrated that the ectopic expression of Hsa-miR-567 in poor prognosis breast cancer cell line strongly inhibits in vitro cell proliferation and migration. Furthermore, we showed in vivo that breast cancer cells, stably expressing Hsa-miR-567, xenografted in mouse, reduce tumor growth ability. Consistently, we found that karyopherin 4 (KPNA4), predicted target gene of Hsa-miR-567 as identified by our in silico analysis, is upregulated in highly aggressive MDA-MB-231 breast cancer cell line and patient tissues with poor prognosis with respect to good prognosis. CONCLUSIONS: Our results suggest a potential role of Hsa-miR-567 as a novel prognostic biomarker for BC and as regulator of KPNA4.

SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data.

Gene Regulatory Networks (GRNs) control many biological systems, but how such network coordination is shaped is still unknown. GRNs can be subdivided into basic connections that describe how the network members interact e.g., co-expression, physical interaction, co-localization, genetic influence, pathways, and shared protein domains. The important regulatory mechanisms of these networks involve miRNAs. We developed an R/Bioconductor package, namely SpidermiR, which offers an easy access to both GRNs and miRNAs to the end user, and integrates this information with differentially expressed genes obtained from The Cancer Genome Atlas. Specifically, SpidermiR allows the users to: (i) query and download GRNs and miRNAs from validated and predicted repositories; (ii) integrate miRNAs with GRNs in order to obtain miRNA-gene-gene and miRNA-protein-protein interactions, and to analyze miRNA GRNs in order to identify miRNA-gene communities; and (iii) graphically visualize the results of the analyses. These analyses can be performed through a single interface and without the need for any downloads. The full data sets are then rapidly integrated and processed locally.

How interacting pathways are regulated by miRNAs in breast cancer subtypes.

BACKGROUND: An important challenge in cancer biology is to understand the complex aspects of the disease. It is increasingly evident that genes are not isolated from each other and the comprehension of how different genes are related to each other could explain biological mechanisms causing diseases. Biological pathways are important tools to reveal gene interaction and reduce the large number of genes to be studied by partitioning it into smaller paths. Furthermore, recent scientific evidence has proven that a combination of pathways, instead than a single element of the pathway or a single pathway, could be responsible for pathological changes in a cell. RESULTS: In this paper we develop a new method that can reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways. We applied the method to subtypes of breast cancer. The basic idea is the identification of pathways significantly enriched with differentially expressed genes among the different breast cancer subtypes and normal tissue. Looking at the pairs of pathways that were found to be functionally related, we created a network of dependent pathways and we focused on identifying miRNAs that could act as miRNA drivers in a coordinated regulation process. CONCLUSIONS: Our approach enables miRNAs identification that could have an important role in the development of breast cancer.

MicroRNAs as Biomarkers for Diagnosis, Prognosis and Theranostics in Prostate Cancer.

Prostate cancer (PC) includes several phenotypes, from indolent to highly aggressive cancer. Actual diagnostic and prognostic tools have several limitations, and there is a need for new biomarkers to stratify patients and assign them optimal therapies by taking into account potential genetic and epigenetic differences. MicroRNAs (miRNAs) are small sequences of non-coding RNA regulating specific genes involved in the onset and development of PC. Stable miRNAs have been found in biofluids, such as serum and plasma; thus, the measurement of PC-associated miRNAs is emerging as a non-invasive tool for PC detection and monitoring. In this study, we conduct an in-depth literature review focusing on miRNAs that may contribute to the diagnosis and prognosis of PC. The role of miRNAs as a potential theranostic tool in PC is discussed. Using a meta-analysis approach, we found a group of 29 miRNAs with diagnostic properties and a group of seven miRNAs with prognostic properties, which were found already expressed in both biofluids and PC tissues. We tested the two miRNA groups on The Cancer Genome Atlas dataset of PC tissue samples with a machine-learning approach. Our results suggest that these 29 miRNAs should be considered as potential panel of biomarkers for the diagnosis of PC, both as in vivo non-invasive test and ex vivo confirmation test.

A novel AMPK activator reduces glucose uptake and inhibits tumor progression in a mouse xenograft model of colorectal cancer.

The anticancer activity of a novel pure 1,4-Diaryl-2-azetidinone (1), endowed with a higher solubility than the well known Combretastatin A4, is tested in mice. We previously reported that Compound (1) showed specific antiproliferative activity against duodenal and colon cancer cells, inducing activation of AMP-activated protein kinase and apoptosis. Here we estimate that the maximum tolerated dose in a mouse model is 40 mg/kg; the drug is well tolerated both in single dose and in repeated administration schedules. The drug displays a significant antitumor activity and a tumor growth delay when administered at the MTD both in single and fractionated i.v. administration in a mouse xenograft model of colorectal cancer. Arrest of tumor growth and relapse after drug suspension are parallel to modification in glucose demand as shown by PET studies with [(18)F] FDG. These data strongly support Compound (1) as a promising molecule for in vivo treatment of colorectal cancer.

Characterization of cell cycle, inflammation, and oxidative stress signaling role in non-communicable diseases: Insights into genetic variants, microRNAs and pathways.

Non-Communicable Diseases (NCDs) significantly impact global health, contributing to over 70% of premature deaths, as reported by the World Health Organization (WHO). These diseases have complex and multifactorial origins, involving genetic, epigenetic, environmental and lifestyle factors. While Genome-Wide Association Study (GWAS) is widely recognized as a valuable tool for identifying variants associated with complex phenotypes; the multifactorial nature of NCDs necessitates a more comprehensive exploration, encompassing not only the genetic but also the epigenetic aspect. For this purpose, we employed a bioinformatics-multiomics approach to examine the genetic and epigenetic characteristics of NCDs (i.e. colorectal cancer, coronary atherosclerosis, squamous cell lung cancer, psoriasis, type 2 diabetes, and multiple sclerosis), aiming to identify novel biomarkers for diagnosis and prognosis. Leveraging GWAS summary statistics, we pinpointed Single Nucleotide Polymorphisms (SNPs) independently associated with each NCD. Subsequently, we identified genes linked to cell cycle, inflammation and oxidative stress mechanisms, revealing shared genes across multiple diseases, suggesting common functional pathways. From an epigenetic perspective, we identified microRNAs (miRNAs) with regulatory functions targeting these genes of interest. Our findings underscore critical genetic pathways implicated in these diseases. In colorectal cancer, the dysregulation of the "Cytokine Signaling in Immune System" pathway, involving LAMA5 and SMAD7, regulated by Hsa-miR-21-5p, Hsa-miR-103a-3p, and Hsa-miR-195-5p, emerged as pivotal. In coronary atherosclerosis, the pathway associated with "binding of TCF/LEF:CTNNB1 to target gene promoters" displayed noteworthy implications, with the MYC factor controlled by Hsa-miR-16-5p as a potential regulatory factor. Squamous cell lung carcinoma analysis revealed significant pathways such as "PTK6 promotes HIF1A stabilization," regulated by Hsa-let-7b-5p. In psoriasis, the "Endosomal/Vacuolar pathway," involving HLA-C and Hsa-miR-148a-3p and Hsa-miR-148b-3p, was identified as crucial. Type 2 Diabetes implicated the "Regulation of TP53 Expression" pathway, controlled by Hsa-miR-106a-5p and Hsa-miR-106b-5p. In conclusion, our study elucidates the genetic framework and molecular mechanisms underlying NCDs, offering crucial insights into potential genetic/epigenetic biomarkers for diagnosis and prognosis. The specificity of pathways and related miRNAs in different pathologies highlights promising candidates for further clinical validation, with the potential to advance personalized treatments and alleviate the global burden of NCDs.

The biological interplay between air pollutants and miRNAs regulation in cancer.

Air pollution, especially fine particulate matter (PM2.5, with an aerodynamic diameter of less than 2.5 µm), represents a risk factor for human health. Many studies, regarding cancer onset and progression, correlated with the short and/or long exposition to PM2.5. This is mainly mediated by the ability of PM2.5 to reach the pulmonary alveoli by penetrating into the blood circulation. This review recapitulates the methodologies used to study PM2.5 in cellular models and the downstream effects on the main molecular pathways implicated in cancer. We report a set of data from the literature, that describe the involvement of miRNAs or long noncoding RNAs on the main biological processes involved in oxidative stress, inflammation, autophagy (PI3K), cell proliferation (NFkB, STAT3), and EMT (Notch, AKT, Wnt/ß-catenin) pathways. microRNAs, as well as gene expression profile, responds to air pollution environment modulating some key genes involved in epigenetic modification or in key mediators of the biological processes described below. In this review, we provide some scientific evidences about the thigh correlation between miRNAs dysregulation, PM2.5 exposition, and gene pathways involved in cancer progression.

Radiogenomics, Breast Cancer Diagnosis and Characterization: Current Status and Future Directions.

Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with -omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).

Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction.

Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (miR-25-3p, miR-93-3p, miR-122-5p, miR-183-5p, miR-615-3p, miR-7-5p, miR-375, and miR-92a-3p) were differentially expressed in all GS and proposed as biomarkers for PC onset. In addition, "Extracellular-receptor interaction", "Focal adhesion", and "microRNAs in cancer" were significantly enriched by the differentially expressed target genes of the identified miRNAs. miR-10a-5p was found to be differentially expressed in GS 6, 7, and 8 in PC samples. 3 miRNAs were identified as PC GS-specific differentially expressed miRNAs: miR-155-5p was identified in PC samples with GS 6, and miR-142-3p and miR-296-3p in PC samples with GS 9. The efficacy of 20 miRNAs as potential biomarkers was revealed with a Random Forest classification using an independent dataset. The results demonstrated our 20 miRNAs achieved a better performance (AUC: 0.73) than miRNAs selected with Boruta algorithm (AUC: 0.55), a method for the automated feature extraction. Studying miRNA-mRNA associations, key miRNAs were identified with a computational approach for PC onset and progression. Further experimental validations are needed for future translational development.

Myosins and MyomiR Network in Patients with Obstructive Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiomyopathy. The molecular mechanisms determining HCM phenotypes are incompletely understood. Myocardial biopsies were obtained from a group of patients with obstructive HCM (n = 23) selected for surgical myectomy and from 9 unused donor hearts (controls). A subset of tissue-abundant myectomy samples from HCM (n = 10) and controls (n = 6) was submitted to laser-capture microdissection to isolate cardiomyocytes. We investigated the relationship among clinical phenotype, cardiac myosin proteins (MyHC6, MyHC7, and MyHC7b) measured by optimized label-free mass spectrometry, the relative genes (MYH7, MYH7B and MYLC2), and the MyomiR network (myosin-encoded microRNA (miRs) and long-noncoding RNAs (Mhrt)) measured using RNA sequencing and RT-qPCR. MyHC6 was lower in HCM vs. controls, whilst MyHC7, MyHC7b, and MyLC2 were comparable. MYH7, MYH7B, and MYLC2 were higher in HCM whilst MYH6, miR-208a, miR-208b, miR-499 were comparable in HCM and controls. These results are compatible with defective transcription by active genes in HCM. Mhrt and two miR-499-target genes, SOX6 and PTBP3, were upregulated in HCM. The presence of HCM-associated mutations correlated with PTBP3 in myectomies and with SOX6 in cardiomyocytes. Additionally, iPSC-derived cardiomyocytes, transiently transfected with either miR-208a or miR-499, demonstrated a time-dependent relationship between MyomiRs and myosin genes. The transfection end-stage pattern was at least in part similar to findings in HCM myectomies. These data support uncoupling between myosin protein/genes and a modulatory role for the myosin/MyomiR network in the HCM myocardium, possibly contributing to phenotypic diversity and providing putative therapeutic targets.