The growing accessibility of sequencing experiments has significantly accelerated the development of personalized immunotherapies based on the identification of cancer neoantigens. However, predicting neoantigens involves lengthy and inefficient protocols, which require simultaneous analysis of sequencing data from paired tumor/normal exomes and tumor transcriptome, often resulting in a low success rate. To date, the feasibility of adopting a more efficient strategy has not been fully evaluated. To this end, we developed ENEO, a computational approach to detect cancer neoantigens using solely the tumor RNA-seq data while addressing the lack of matched control through a Bayesian probabilistic model. ENEO was assessed on the TESLA benchmark dataset, reporting efficient identification of DNA-alterations derived neoantigens and compelling results against state-of-art exome-based methods. We further validated the method on two independent cohorts, encompassing different tumor types and experimental procedures. Our work demonstrates that a tumor-only RNA-based approach, such as the one implemented in ENEO, maintains accuracy in identifying mutated peptides resulting from expressed genomic alterations while also broadening the pool of potential neoantigens with RNA-specific mutations in a faster and cost-effective way. ENEO is freely available at the URL: https://github.com/ctglab/ENEO

The BRAFV600E mutant kinase is widely studied as a cancer driver and therapeutic target. Here, we investigated how the annotation of the BRAF-reference (ref) and BRAF-X1 variants has evolved in public databases and addressed challenges posed by their discrimination and quantification from short-read sequencing. We built IsoWorm, a bioinformatic pipeline tailored to discriminate and quantify BRAF variants, and employed it to analyze > 600 cancer cell lines and > 1000 cancer tissue samples. Using FLIBase, we reanalyzed TCGA data from > 9000 cancer tissue samples. We consistently found that BRAF-X1 (now BRAF-204) is very abundant in human cancer and its expression is 1.5–75 times greater than that of BRAF-ref (now BRAF-220). Crucially, we identified KIRP-kidney renal papillary cell carcinoma as a cancer subtype in which a high BRAF-204/BRAF-220 ratio is an independent prognostic factor of poor outcome. Our in silico analyses establish BRAF as a mix of two protein-coding transcript variants, with BRAF-204 being more highly expressed than BRAF-220. These findings prompt us to undertake the systematic benchmarking of BRAF-204 against BRAF-220 in terms of molecular mechanisms, biological activities, druggability, and clinical relevance.

Triple-negative breast cancer (TNBC) is a very aggressive and heterogeneous group of tumors. In order to develop effective therapeutic strategies, it is therefore essential to identify the subtype-specific molecular mechanisms underlying disease progression and resistance to chemotherapy. TNBC cells are highly dependent on exogenous cystine, provided by overexpression of the cystine/glutamate antiporter SLC7A11/xCT, to fuel glutathione synthesis and promote an oxidative stress response consistent with their high metabolic demands. Here we show that TNBC cells of the mesenchymal stem-like subtype (MSL) utilize forced cystine uptake to induce activation of the transcription factor NRF2 and promote a glutathione-independent mechanism to defend against oxidative stress. Mechanistically, we demonstrate that NRF2 activation is mediated by direct cysteinylation of the inhibitor KEAP1. Furthermore, we show that cystine-mediated NRF2 activation induces the expression of important genes involved in oxidative stress response, but also in epithelial-to-mesenchymal transition and stem-like phenotype. Remarkably, in survival analysis, four upregulated genes (OSGIN1, RGS17, SRXN1, AKR1B10) are negative prognostic markers for TNBC. Finally, expression of exogenous OSGIN1, similarly to expression of exogenous NRF2, can prevent cystine depletion-dependent death of MSL TNBC cells. The results suggest that the cystine/NRF2/OSGIN1 axis is a potential target for effective treatment of MSL TNBCs.

Alport syndrome is a rare genetic kidney disease caused by variants in the COL4A3/A4/A5 genes. It’s characterised by progressive kidney failure, though therapies targeting Renin-Angiotensin System can delay its progression. Additionally, extrarenal manifestations may sometimes coexist. Recent advances in genetic analysis and the necessity to better clarify genotype-phenotype correlations in affected patients raises the importance of detecting even cryptic splicing variants, lying in both canonical and non-canonical splice sites variants such as last exonic nucleotide variants. These variants, often, do not cause an amino acid change but alter the snRNP proteins binding. We studied a big Italian family with Alport syndrome showing a clear dominant pattern of transmission with younger family members having only haematuria and older individuals presenting with End-Stage Kidney Failure (ESKF). Kidney biopsy showed the typical disease hallmarks. We deeply mined the data for SNV and CNV through exome sequencing on DNA from both peripheral blood samples and patients’ podocytes-lineage cells. We identified an already reported synonymous variant, c.765G>A (p.(Thr255Thr)), in the last exonic nucleotide of exon 13 of the COL4A3 gene. Employing the patient’s podocytes we demonstrated that this variant results in exon skipping leading to an in-frame deletion of 28 amino acids without leaky effect. According to the pattern of transmission, to the kidney biopsy and to the exome data analysis we provided further evidence that autosomal dominant Alport syndrome is a well-defined clinical entity. We also confirmed the pathogenicity of the synonymous COL4A3 variant for the first time demonstrating its role in a dominant pattern of transmission.

In epigenetic analysis, identifying differentially methylated regions (DMRs) typically involves detecting groups of consecutive CpGs that show significant changes in their average methylation levels. However, the methylation state of a genomic region can also be characterized by a mixture of patterns (epialleles) with variable frequencies, and the relative proportions of such patterns can provide insights into its mechanisms of formation.Traditional methods based on bisulfite conversion and NGS, due to the read size (150 bp), allow epiallele frequency analysis only in high-CpG-density regions, limiting differential methylation studies to just 50% of the human methylome. Nanopore sequencing, with its long reads, enables the analysis of epiallele frequency across both high- and low-CpG-density regions.We introduce a novel computational approach, PoreMeth2, an R library that integrates epiallelic diversity and methylation frequency changes from Nanopore data to identify DMRs, assess their formation mechanisms, and annotate them to genic and regulatory elements. We applied PoreMeth2 to cancer and glial cell datasets, demonstrating its ability to distinguish epigenomic changes with a strong effect on gene expression from those with a weaker impact on transcriptional activity.PoreMeth2 is publicly available athttps://github.com/Lab-CoMBINE/PoreMeth2.

Quantum Machine Learning (QML) is considered one of the most promising applications of Quantum Computing in the Noisy Intermediate Scale Quantum (NISQ) era for the impact it is thought to have in the near future. Although promising theoretical assumptions, the exploration of how QML could foster new discoveries in Medicine and Biology fields is still in its infancy with few examples. In this study, we aimed to assess whether Quantum Kernels (QK) could effectively classify subtypes of Breast Cancer (BC) patients on the basis of molecular characteristics. We performed an heuristic exploration of encoding configurations with different entanglement levels to determine a trade-off between kernel expressivity and performances. Our results show that QKs yield comparable clustering results with classical methods while using fewer data points, and are able to fit the data with a higher number of clusters. Additionally, we conducted the experiments on the Quantum Processing Unit (QPU) to evaluate the effect of noise on the outcome. We found that less expressive encodings showed a higher resilience to noise, indicating that the computational pipeline can be reliably implemented on the NISQ devices. Our findings suggest that QK methods show promises for application in Precision Oncology, especially in scenarios where the dataset is limited in size and a granular non-trivial stratification of complex molecular data cannot be achieved classically.

Patient management with lower-grade glioma (LGG) requires tumour sampling to identify IDH mutation and 1p19q codeletion status, which are pivotal for subtype classification and subsequent therapy. The use of MRI has been investigated so far by radiomics which focuses on features extracted from 2D images of the tumour region only. Deep Learning (DL) algorithms, and in particular Neural Networks (NN), proved to be effective in improving the detection of cancers from diverse imaging data, often through tumour segmentation masking. We aimed to develop a DL-based framework to streamline the LGG molecular-based subtypes classification from the whole-brain 3D MRI scans and, subsequently, to extract a fine map of the brain regions which resulted relevant for the classification. Pre-operative MRI scans (T2-FLAIR, T1gad) and molecular information (IDH mutation, 1p19q codeletion status) of 82 LGG patients were collected from the TCIA and TCGA datasets. 56 “IDH-mutant astrocytomas” and 26 “IDH-mutant 1p19q codeleted oligodendrogliomas” were split into class-balanced training (65) and test (17) sets. A computational framework was developed to preprocess the MRIs, train and optimize different DL models through hyperparameters fine-tuning and to automatically detect the best-performing one. We explored a total of 162 configurations, using single and multiple MRI modalities within two residual NN and calculated the attention maps using guided back-propagation. In the test set we obtained a balanced accuracy of 92/% and a F1-weighted score of 89/% in differentiating IDH-mutant astrocytomas (sensitivity=0.83) from IDH-mutant 1p19q codeleted oligodendrogliomas (sensitivity=1). The generated attention maps confirmed that features extracted from the perilesional regions positively influenced the classification of the tumour subtypes, especially of astrocytomas (100/% of cases); on the contrary, the widely used tumoral region was scarcely considered in the classification of this subtype (10/%), having an impact only in oligodendrogliomas (60/%). Interestingly, contralateral and other distant-from-the-tumour areas were relevant in the classification of both subtypes (40/%), with a focus on distant-from-the-tumour areas in oligodendrogliomas (60/%). 3D whole-brain scans coupled with optimized DL-based approach showed to be a non-invasive and promising alternative in classifying LGG molecular-based subtypes, providing a more exploratory insight in the subject-level discrimination of brain regions differently associated with IDH mutation and 1p19q codeletion status. Further validations are needed to prove the efficacy of the proposed method in supporting the clinical decision-making.

Docetaxel (DCT) resistance is one of the main factors responsible for treatment failure in metastatic prostate cancer (PCa). Although several mechanisms of DCT resistance have been elucidated, the issue is still far from comprehensive. In this work we show that miR-96-5p, miR-183-5p and miR-210-3p (referred to as sDCTR-miRNAs) are specifically released by DCT resistant (DCTR) PCa clones and decrease the efficacy of DCT in PCa cells when overexpressed. Through bioinformatic analysis, we identified several potential targets of sDCTR-miRNAs’ activity including FOXO1, IGFBP3, and PDCD4 known to exert a role in DCT resistance. Additionally, we found that PPP2CB and INSIG1 mediated the ability of sDCTR-miRNAs to reduce the efficacy of DCT. We explored whether secreted sDCTR-miRNAs could affect the phenotype of PCa cells. We found that exposure to exosomes derived from DCTR PCa clones (in which the content of sDCTR-miRNAs was higher than in exosomes from parental cells), as well as exposure to exosome loaded with sDCTR-miRNAs, reduced the cytotoxicity of DCT in PCa cells sensitive to the drug. Finally, we validated circulating miR-183-5p and miR-21-5p as potential predictive biomarkers of DCT resistance in PCa patients. Our study suggests a horizontal transfer mechanism mediated by exosomal miRNAs that contributes to reduce docetaxel sensitivity and highlights the relevance of cell-to-cell communication in drug resistance.

DNA sequence variants (single nucleotide polymorphisms or variants, SNPs/SNVs; copy number variants, CNVs) associated to neurodevelopmental disorders (NDD) and traits often map on putative transcriptional regulatory elements, including, in particular, enhancers. However, the genes controlled by these enhancers remain poorly defined. Traditionally, the activity of a given enhancer, and the effect of its possible alteration associated to the sequence variants, has been thought to influence the nearest gene promoter. However, the obtainment of genome-wide long-range interaction maps in neural cells chromatin challenged this view, showing that a given enhancer is very frequently not connected to the nearest promoter, but to a more distant one, skipping genes in between. In this Perspective, we review some recent papers, who generated long-range interaction maps (by HiC, RNApolII ChIA-PET, Capture-HiC, or PLACseq), and overlapped the identified long-range interacting DNA segments with DNA sequence variants associated to NDD (such as schizophrenia, bipolar disorder and autism) and traits (intelligence). This strategy allowed to attribute the function of enhancers, hosting the NDD-related sequence variants, to a connected gene promoter lying far away on the linear chromosome map. Some of these enhancer-connected genes had indeed been already identified as contributive to the diseases, by the identification of mutations within the gene’s protein-coding regions (exons), validating the approach. Significantly, however, the connected genes also include many genes that were not previously found mutated in their exons, pointing to novel candidate contributors to NDD and traits. Thus, long-range interaction maps, in combination with DNA variants detected in association with NDD, can be used as “pointers” to identify novel candidate disease-relevant genes. Functional manipulation of the long-range interaction network involving enhancers and promoters by CRISPR-Cas9-based approaches is beginning to probe for the functional significance of the identified interactions, and the enhancers and the genes involved, improving our understanding of neural development and its pathology.

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80–0.95 and 0.83, 95% C.I. 0.74–0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.

Non-coding variation in complex human disease has been well established by genome-wide association studies, and is thought to involve regulatory elements, such as enhancers, whose variation affects the expression of the gene responsible for the disease. The regulatory elements often lie far from the gene they regulate, or within introns of genes differing from the regulated gene, making it difficult to identify the gene whose function is affected by a given enhancer variation. Enhancers are connected to their target gene promoters via long-range physical interactions (loops). In our study, we re-mapped, onto the human genome, more than 10,000 enhancers connected to promoters via long-range interactions, that we had previously identified in mouse brain-derived neural stem cells by RNApolII-ChIA-PET analysis, coupled to ChIP-seq mapping of DNA/chromatin regions carrying epigenetic enhancer marks. These interactions are thought to be functionally relevant. We discovered, in the human genome, thousands of DNA regions syntenic with the interacting mouse DNA regions (enhancers and connected promoters). We further annotated these human regions regarding their overlap with sequence variants (single nucleotide polymorphisms, SNPs; copy number variants, CNVs), that were previously associated with neurodevelopmental disease in humans. We document various cases in which the genetic variant, associated in humans to neurodevelopmental disease, affects an enhancer involved in long-range interactions: SNPs, previously identified by genome-wide association studies to be associated with schizophrenia, bipolar disorder, and intelligence, are located within our human syntenic enhancers, and alter transcription factor recognition sites. Similarly, CNVs associated to autism spectrum disease and other neurodevelopmental disorders overlap with our human syntenic enhancers. Some of these enhancers are connected (in mice) to homologs of genes already associated to the human disease, strengthening the hypothesis that the gene is indeed involved in the disease. Other enhancers are connected to genes not previously associated with the disease, pointing to their possible pathogenetic involvement. Our observations provide a resource for further exploration of neural disease, in parallel with the now widespread genome-wide identification of DNA variants in patients with neural disease.

Inhibition of DDX3X expression or activity reduces proliferation in cells from various tumor tissues, in particular in breast cancer, and its expression often correlates to tumor aggressiveness. This makes DDX3X a prominent candidate for the design of drugs for novel personalized therapeutic strategies. Starting from an in silico drug discovery approach, a group of molecules has been selected by molecular docking at the RNA binding site of DDX3X. Here, the most promising among them, FHP01, was evaluated in breast cancer preclinical models. Specifically, FHP01 exhibited very effective antiproliferative and killing activity against different breast cancer cell types, among which those from triple-negative breast cancer (TNBC). Interestingly, FHP01 also inhibited WNT signaling, a key tumorigenic pathway already correlated to DDX3X functions in breast cancer model cell lines. Ultimately, FHP01 also caused a significant reduction, in vivo, in the growth of MDA MB 231-derived TNBC xenograft models. Importantly, FHP01 showed good bioavailability and no toxicity on normal peripheral blood mononuclear cells in vitro and on several mouse tissues in vivo. Overall, our data suggest that the use of FHP01 and its related compounds may represent a novel therapeutic approach with high potential against breast cancer, including the triple-negative subtype usually correlated to the most unfavorable outcomes because of the lack of available targeted therapies.

miR-28-5p is downregulated in some tumor tissues in which it has been demonstrated to have tumor suppressor (TS) activity. Here, we demonstrate that miR-28-5p acts as a TS in prostate cancer (PCa) cells affecting cell proliferation/survival, as well as migration and invasion. Using the miRNA pull out assay and next generation sequencing, we collected the complete repertoire of miR-28-5p targets, obtaining a data set (miR-28-5p targetome) of 191 mRNAs. Filtering the targetome with TargetScan 7, PITA and RNA22, we found that 61% of the transcripts had miR-28-5p binding sites. To assign a functional value to the captured transcripts, we grouped the miR-28-5p targets into gene families with annotated function and showed that six transcripts belong to the transcription factor category. Among them we selected SREBF2, a gene with an important role in PCa. We validated miR-28-5p/SREBF2 interaction, demonstrating that SREBF2 inhibition affects almost all the tumor processes altered by miR-28-5p re-expression, suggesting that SREBF2 is an important mediator of miR-28-5p TS activity. Our findings support the identification of the targetome of cancer-related miRNAs as a tool to discover genes and pathways fundamental for tumor development, and potential new targets for anti-tumor therapy.

We identified and compared secreted microRNA (miRNA) expression in aqueous humor (AH) and plasma samples among patients with: type 2 diabetes mellitus (T2D) complicated by non-proliferative diabetic retinopathy (DR) associated with diabetic macular edema (DME) (DME group: 12 patients); T2D patients without DR (D group: 8 patients); and non-diabetic patients (CTR group: 10 patients). Individual patient AH samples from five subjects in each group were profiled on TaqMan Low Density MicroRNA Array Cards. Differentially expressed miRNAs identified from profiling were then validated in single assay for all subjects. The miRNAs validated in AH were then evaluated in single assay in plasma. Gene Ontology (GO) analysis was conducted. From AH profiling, 119 mature miRNAs were detected: 86 in the DME group, 113 in the D group and 107 in the CTR group. miRNA underexpression in the DME group was confirmed in single assay for let-7c-5p, miR-200b-3p, miR-199a-3p and miR-365-3p. Of these four, miR-199a-3p and miR-365-3p were downregulated also in the plasma of the DME group. GO highlighted 54 validated target genes of miR-199a-3p, miR-200b-3p and miR-365-3p potentially implied in DME pathogenesis. Although more studies are needed, miR-200b-3p, let-7c-5p, miR-365-3p and miR-199a-3p represent interesting molecules in the study of DME pathogenesis.

The LncRNA my-heart (Mhrt) and the chromatin remodeler Brg1 inhibit each other to respectively prevent or favor the maladaptive α-myosin-heavy-chain (Myh6) to β-myosin-heavy-chain (Myh7) switch, so their balance crucially guides the outcome of cardiac remodeling under stress conditions. Even though triiodothyronine (T3) has long been recognized as a critical regulator of the cardiac Myh isoform composition, its role as a modulator of the Mhrt/Brg1 axis is still unexplored. Here the effect of T3 on the Mhrt/Brg1 regulatory circuit has been analyzed in relation with chromatin remodeling and previously identified T3-dependent miRNAs. The expression levels of Mhrt, Brg1 and Myh6/Myh7 have been assessed in rat models of hyperthyroidism or acute myocardial ischemia/reperfusion (IR) treated with T3 replacement therapy. To gain mechanistic insights, in silico analyses and site-directed mutagenesis have been adopted in combination with gene reporter assays and loss or gain of function strategies in cultured cardiomyocytes. Our results indicate a pivotal role of Mhrt over-expression in the T3-dependent regulation of Myh switch. Mechanistically, T3 activates the Mhrt promoter at two putative thyroid hormone responsive elements (TRE) located in a crucial region that is necessary for both Mhrt activation and Brg1-dependent Mhrt repression. This newly identified T3 mode of action requires DNA chromatinization and is critically involved in mitigating the repressive function of the Brg1 protein on Mhrt promoter. In addition, T3 is also able to prevent the Brg1 over-expression observed in the post-IR setting through a pathway that might entail the T3-mediated up-regulation of miR-208a. Taken together, our data evidence a novel T3-responsive network of cross-talking epigenetic factors that dictates the cardiac Myh composition and could be of great translational relevance.

Circulating miRNAs (c-miRNAs) are promising biomarkers for HF diagnosis and prognosis. There are no studies on HF pediatric patients undergoing VAD-implantation. Aims of this study were: to examine the c-miRNAs profile in HF children; to evaluate the effects of VAD on c-miRNAs levels; to in vitro validate putative c-miRNA targets. c-miRNA profile was determined in serum of HF children by NGS before and one month after VAD-implant. The c-miRNA differentially expressed were analyzed by real time-PCR, before and at 4 hrs,1,3,7,14,30 days after VAD-implant. A miRNA mimic transfection study in HepG2 cells was performed to validate putative miRNA targets selected through miRWalk database. Thirteen c-miRNAs were modified at 30 days after VAD-implant compared to pre-VAD at NSG, and, among them, six c-miRNAs were confirmed by Real-TimePCR. Putative targets of the validated c-miRNAs are involved in the hemostatic process. The in vitro study confirmed a down-regulatory effect of hsa-miR-409-3p towards coagulation factor 7 (F7) and F2. Of note, all patients had thrombotic events requiring pump change. In conclusion, in HF children, the level of six c-miRNAs involved in the regulation of hemostatic events changed after 30 days of VAD-treatment. In particular, the lowering of c-miR-409-3p regulating both F7 and F2 could reflect a pro-thrombotic state after VAD-implant.

Five‐year overall survival of stage III colorectal cancer (CRC) patients treated with standard adjuvant chemotherapy (ACHT) is highly variable. Genomic biomarkers and/or transcriptomic profiles identified lack of adequate validation. Aim of our study was to identify and validate molecular biomarkers predictive of ACHT response in stage III CRC patients by a transcriptomic approach. From a series of CRC patients who received ACHT, two stage III extreme cohorts (unfavorable vs. favorable prognosis) were selected. RNA‐sequencing was performed from fresh frozen explants. Tumors were characterized for somatic mutations. Validation was performed in stage III CRC patients extracted from two GEO datasets. According to disease‐free survival (DFS), 108 differentially expressed genes (104/4 up/downregulated in the unfavorable prognosis group) were identified. Among 104 upregulated genes, 42 belonged to olfactory signaling pathways, 62 were classified as pseudogenes (n = 17), uncharacterized noncoding RNA (n = 10), immune response genes (n = 4), microRNA (n = 1), cancer‐related genes (n = 14) and cancer‐unrelated genes (n = 16). Three out of four down‐regulated genes were cancer‐related. Mutational status (i.e., RAS, BRAF, PIK3CA) did not differ among the cohorts. In the validation cohort, multivariate analysis showed high PNN and KCNQ1OT1 expression predictive of shorter DFS in ACHT treated patients (p = 0.018 and p = 0.014, respectively); no difference was observed in untreated patients. This is the first study that identifies by a transcriptomic approach and validates PNN and KCNQ1OT1 as molecular biomarkers predictive of chemotherapy response in stage III CRC patients. After a further validation in an independent cohort, PNN and KCNQ1OT1 evaluation could be proposed to prospectively identify stage III CRC patients benefiting from ACHT.

Metabolomics/lipidomics are important tools to identify novel biomarkers associated with liver damage. Patients with chronic liver disease (CLD) and hepatitis C virus (HCV) infection often have alterations in glucose, lipid and protein metabolism. The aim of this study was to evaluate if dysfunctional lipid and amino acid metabolism was associated with fibrosis severity and insulin resistance in CLD/HCV patients. We analyzed the baseline sera of 75 subjects with CLD/HCV infection HCV genotype-1, with proven liver biopsy prior to antiviral treatment. We measured amino acid (AA) and lipid concentration by gas and liquid chromatography-mass spectrometry respectively. Alterations in peripheral glucose metabolism due to insulin resistance (IR) were assesed by HOMA-IR (Glucose x Insulin/22.5), while adipose tissue IR was estimated as (Adipo-IR = Free Fatty Acids x Insulin). Baseline HOMA-IR and Adipo-IR were related to the degree of liver fibrosis. Reduction in ceramides 18:1/22:0, 18:1/24:0, diacylglycerol 42:6 and increased phosphocholine 40:6 were associated with higher fibrosis. Adipo-IR was related to lower levels of lysophosphatidylcholine 14:0 and 18:2 and with higher levels of sphingomyelin 18:2/24:0 and 18:2/24:1. Almost all AA were positively associated with Adipo-IR but not with HOMA-IR. We further confirmed the potential use of metabolomics and lipidomics in CLD/HCV subjects finding novel biomarkers of hepatic fibrosis and show that the adipose tissue IR is associated with more severe liver disease and is an important marker not only of altered lipid but also AA metabolism.

Thyroid hormone (T3) dyshomeostasis in the cardiac ischemia-reperfusion (IR) setting negatively impacts on mitochondria function and extracellular matrix remodeling. The modulation of cardiac miRNAs may represent the underlying molecular mechanisms, but a systems biology perspective investigating this critical issue in depth is still lacking. A rat model of myocardial IR, with or without an early short-term T3-replacement, was used to predict putative T3-dependent miRNA-gene interactions targeted to mitochondria quality control and wound healing repair. As evidenced by mRNA and miRNA expression profiling, the T3 supplementation reverted the expression of 87 genes and 11 miRNAs that were dysregulated in the untreated group. In silico crossing and functional analysis of the T3-associated differentially expressed transcripts, identified a signature of interconnected miRNA-gene regulatory circuits that confer resistance to noxious cascades of acute stress. In this network the T3-down-regulated Tp53, Jun and Sp1 transcription factors emerge as critical nodes linking intrinsic cell death and oxidative stress pathways to adverse remodeling cascades. The data presented here provide a novel insight into the molecular basis of T3 cardioprotection in the early post-IR phase and highlight the contribution of a previously unappreciated complex T3-regulatory network that may be helpful in translating T3 replacement into clinical practice.

Congenital myotonic dystrophy type 1 (CDM1) is characterized by severe symptoms that affect patients from birth, with 40% mortality in the neonatal period and impaired skeletal muscle development. In this paper, we examined the relationship between autophagy and abnormal myogenic differentiation of CDM1 myoblasts. We investigated these pathological features at both ultrastructural and molecular levels, utilizing two CDM1 foetal myoblasts, CDM13 and CDM15, with 1800 and 3200 repeats, respectively. The congenital nature of these CDM1 myoblasts was confirmed by the high methylation level at the DMPK locus. Our results indicated that abnormal autophagy was independent of myogenic differentiation, as CDM13 myoblasts differentiated as well as control myoblasts but underwent autophagy like CDM15, displaying impaired differentiation. miRNA expression profiles revealed that CDM15 myoblasts failed to upregulate the complex network of myo-miRNAs under MYOD and MEF2A control, while this network was upregulated in CDM13 myoblasts. Interestingly, the abnormal differentiation of CDM15 myoblasts was associated with cellular stress accompanied by the induction of the interferon type 1 pathway (innate immune response). Indeed, inhibition of the interferon (IFN) type I pathway restores myogenic differentiation of CDM15 myoblasts, suggesting that the inappropriate activation of the innate immune response might contribute to impaired myogenic differentiation and severe muscle symptoms observed in some CDM1 patients. These findings open up the possibility of new therapeutic approaches to treat CDM1.

On the grounds that miRNAs present in the blood of prostate cancer (PCa) patients are released in the growth medium by PCa cells, it is conceivable that PCa cells resistant to docetaxel (DCT) (DCTR) will release miRNAs that may be found in PCa patients under DCT therapy if resistant PCa cells appear. We isolated DCTR clones respectively from 22Rv1 and DU-145 PCa cell lines and performed through next-generation sequencing (NGS) the miRNAs profiles of the released miRNAs. The analysis of the NGS data identified 105 and 1 miRNAs which were differentially released in the growth medium of the 22Rv1/DCTR and DU-145/DCTR clones, respectively. Using additional filters, we selected 12 and 1 miRNA more released by all 22Rv1/DCTR and DU-145/DCTR clones, respectively. Moreover, we showed that 6 of them were more represented in the growth medium of the DCTR cells than the ones of DCT-treated cells. We speculated that they have the pre-requisite to be tested as predictive biomarkers of the DCT resistance in PCa patients under DCT therapy. We propose the utilization of clones resistant to a given drug as in vitro model to identify the differentially released miRNAs, which in perspective could be tested as predictive biomarkers of drug resistance in tumor patients under therapy.

Mechanical unloading by left ventricular assist devices (LVADs) in advanced heart failure (HF), in addition to improving symptoms and end-organ perfusion, is supposed to stimulate cellular and molecular responses which can reverse maladaptive cardiac remodeling. As microRNAs (miRNAs) are key regulators in remodeling processes, a comparative miRNA profiling in transplanted hearts of HF patients with/without LVAD assistance could aid to comprehend underlying molecular mechanisms. Next generation sequencing (NGS) was used to analyze miRNA differential expression in left ventricles of HF patients who underwent heart transplantation directly (n=9) or following a period of LVAD support (n=8). After data validation by quantitative real-time PCR, association with functional clinical parameters was investigated. Bioinformatics’ tools were then used for prediction of putative targets of modulated miRNAs and relative pathway enrichment. The analysis revealed 13 upregulated and 10 downregulated miRNAs in failing hearts subjected to LVAD assistance. In particular, the expression level of some of them (miR-338-3p, miR-142-5p and -3p, miR-216a-5p, miR-223-3p, miR-27a-5p, and miR-378g) showed correlation with off-pump cardiac index values. Predicted targets of these miRNAs were involved in focal adhesion/integrin pathway and in actin cytoskeleton regulation. The identified miRNAs might contribute to molecular regulation of reverse remodeling and heart recovery mechanisms.

Holt-Oram Syndrome (HOS) is an autosomal dominant heart-hand syndrome caused by mutations in the TBX5 gene, a transcription factor capable of regulating hundreds of cardiac-specific genes through complex transcriptional networks. Here we show that, in zebrafish, modulation of a single miRNA is sufficient to rescue the morphogenetic defects generated by HOS. The analysis of miRNA-seq profiling revealed a decreased expression of miR-19a in Tbx5-depleted zebrafish embryos compared to the wild type. We revealed that the transcription of the miR-17-92 cluster, which harbors miR-19a, is induced by Tbx5 and that a defined dosage of miR-19a is essential for the correct development of the heart. Importantly, we highlighted that miR-19a replacement is able to rescue cardiac and pectoral fin defects and to increase the viability of HOS zebrafish embryos. We further observed that miR-19a replacement shifts the global gene expression profile of HOS-like zebrafish embryos towards the wild type condition, confirming the ability of miR-19a to rescue the Tbx5 phenotype. In conclusion our data demonstrate the importance of Tbx5/miR-19a regulatory circuit in heart development and provide a proof of principle that morphogenetic defects associated with HOS can be rescued by transient miRNA modulation.

Abstract We developed a novel software tool, EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.