Human Amniotic MSC Response in LPS-Stimulated Ascites from Patients with Cirrhosis: FOXO1 Gene and Th17 Activation in Enhanced Antibacterial Activation.

Spontaneous bacterial peritonitis (SBP) is a severe complication in patients with decompensated liver cirrhosis and is commonly treated with broad spectrum antibiotics. However, the rise of antibiotic resistance requires alternative therapeutic strategies. As recently shown, human amnion-derived mesenchymal stem cells (hA-MSCs) are able, in vitro, to promote bacterial clearance and modulate the immune and inflammatory response in SBP. Our results highlight the upregulation of FOXO1, CXCL5, CXCL6, CCL20, and MAPK13 in hA-MSCs as well as the promotion of bacterial clearance, prompting a shift in the immune response toward a Th17 lymphocyte phenotype after 72 h treatment. In this study, we used an in vitro SBP model and employed omics techniques (next-generation sequencing) to investigate the mechanisms by which hA-MSCs modify the crosstalk between immune cells in LPS-stimulated ascitic fluid. We also validated the data obtained via qRT-PCR, cytofluorimetric analysis, and Luminex assay. These findings provide further support to the hope of using hA-MSCs for the prevention and treatment of infective diseases, such as SBP, offering a viable alternative to antibiotic therapy.

An extended catalogue of ncRNAs in Streptomyces coelicolor reporting abundant tmRNA, RNase-P RNA and RNA fragments derived from pre-ribosomal RNA leader sequences.

Streptomyces coelicolor is a model organism for studying streptomycetes. This genus possesses relevant medical and economical roles, because it produces many biologically active metabolites of pharmaceutical interest, including the majority of commercialized antibiotics. In this bioinformatic study, the transcriptome of S. coelicolor has been analyzed to identify novel RNA species and quantify the expression of both annotated and novel transcripts in solid and liquid growth medium cultures at different times. The major characteristics disclosed in this study are: (i) the diffuse antisense transcription; (ii) the great abundance of transfer-messenger RNAs (tmRNA); (iii) the abundance of rnpB transcripts, paramount for the RNase-P complex; and (iv) the presence of abundant fragments derived from pre-ribosomal RNA leader sequences of unknown biological function. Overall, this study extends the catalogue of ncRNAs in S. coelicolor and suggests an important role of non-coding transcription in the regulation of biologically active molecule production.

miRNA expression analysis in the human heart: Undifferentiated progenitors vs. bioptic tissues-Implications for proliferation and ageing.

In developed countries, cardiovascular diseases are currently the first cause of death. Cardiospheres (CSs) and cardiosphere-derived cells (CDCs) have been found to have the ability to regenerate the myocardium after myocardial infarction (MI). In recent years, much effort has been made to gain insight into the human heart repair mechanisms, in which miRNAs have been shown to play an important role. In this regard, to elucidate the involvement of miRNAs, we evaluated the miRNA expression profile across human heart biopsy, CSs and CDCs using microarray and next-generation sequencing (NGS) technologies. We identified several miRNAs more represented in the progenitors, where some of them can be responsible for the proliferation or the maintenance of an undifferentiated state, while others have been found to be downregulated in the undifferentiated progenitors compared with the biopsies. Moreover, we also found a correlation between downregulated miRNAs in CSs/CDCs and patient age (eg miR-490) and an inverse correlation among miRNAs upregulated in CSs/CDCs (eg miR-31).

Aneuploid IMR90 cells induced by depletion of pRB, DNMT1 and MAD2 show a common gene expression signature.

Chromosome segregation defects lead to aneuploidy which is a major feature of solid tumors. How diploid cells face chromosome mis-segregation and how aneuploidy is tolerated in tumor cells are not completely defined yet. Thus, an important goal of cancer genetics is to identify gene networks that underlie aneuploidy and are involved in its tolerance. To this aim, we induced aneuploidy in IMR90 human primary cells by depleting pRB, DNMT1 and MAD2 and analyzed their gene expression profiles by microarray analysis. Bioinformatic analysis revealed a common gene expression profile of IMR90 cells that became aneuploid. Gene Set Enrichment Analysis (GSEA) also revealed gene-sets/pathways that are shared by aneuploid IMR90 cells that may be exploited for novel therapeutic approaches in cancer. Furthermore, Protein-Protein Interaction (PPI) network analysis identified TOP2A and KIF4A as hub genes that may be important for aneuploidy establishment.

Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a great effort on studying the infection molecular mechanisms. Several vaccine formulations are nowadays available and helping to reach immunity. Nevertheless, there is a growing interest towards the development of novel anti-covid drugs. In this scenario, the main protease (Mpro) represents an appealing target, being the enzyme responsible for the cleavage of polypeptides during the viral genome transcription. With the aim of sharing new insights for the design of novel Mpro inhibitors, our research group developed a machine learning approach using the support vector machine (SVM) classification. Starting from a dataset of two million commercially available compounds, the model was able to classify two hundred novel chemo-types as potentially active against the viral protease. The compounds labelled as actives by SVM were next evaluated through consensus docking studies on two PDB structures and their binding mode was compared to well-known protease inhibitors. The best five compounds selected by consensus docking were then submitted to molecular dynamics to deepen binding interactions stability. Of note, the compounds selected via SVM retrieved all the most important interactions known in the literature.

An improvement of ComiR algorithm for microRNA target prediction by exploiting coding region sequences of mRNAs.

MicroRNA are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR is a web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR was trained with the information regarding binding sites in the 3'utr region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein--a component of the microRNA induced silencing complex.In this work, we tested whether including coding region binding sites in ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3'utr information. On the other hand, we show that 3'utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3'utr and coding regions, should be considered in comprehensive analysis.Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3'utr based one.

RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. METHODS: We performed three RIP-Chip experiments using either anti-AGO2 or anti-GW182 antibodies and compiled a data set made up of the miRNA and mRNA expression profiles of three samples for each experiment. Specifically, we analyzed the input sample, the immunoprecipitated fraction and the unbound sample resulting from the RIP experiment. We used the expression profile of the input sample to compute several variables, using formulae capable of integrating the information on miRNA binding sites, both in the 3'UTR and coding regions, with miRNA and mRNA expression level profiles. We compared immunoprecipitated vs unbound samples to determine the enriched or underrepresented genes in the immunoprecipitated fractions, independently for AGO2 and GW182 related samples. RESULTS: For each of the two proteins, we trained and tested several support vector machine algorithms capable of distinguishing the enriched from the underrepresented genes that were experimentally detected. The most efficient algorithm for distinguishing the enriched genes in AGO2 immunoprecipitated samples was trained by using variables involving the number of binding sites in both the 3'UTR and coding region, integrated with the miRNA expression profile, as expected for miRNA targets. On the other hand, we found that the best variable for distinguishing the enriched genes in the GW182 immunoprecipitated samples was the length of the coding region. CONCLUSIONS: Due to the major role of GW182 in GW/P-bodies, our data suggests that the AGO2-GW182 RISC recruits genes based on miRNA binding sites in the 3'UTR and coding region, but only the longer mRNAs probably remain sequestered in GW/P-bodies, functioning as a repository for translationally silenced RNAs.

ComiR: Combinatorial microRNA target prediction tool.

ComiR is a web tool for combinatorial microRNA (miRNA) target prediction. Given an messenger RNA (mRNA) in human, mouse, fly or worm genomes, ComiR computes the potential of being targeted by a set of miRNAs, each of which can have zero, one or more targets on its 3'untranslated region. In determining the regulatory potential of an mRNA from a set of miRNAs, ComiR uses user-provided miRNA expression levels in a combination of appropriate thermodynamic modeling and machine learning techniques to make more accurate predictions. For each gene, ComiR returns the probability of being a functional target of a set of miRNAs, which depends on the relative miRNA expression levels. The tool provides a user-friendly interface to input a miRNA expression table containing many sample information and filter out the most relevant miRNAs. ComiR results can be downloaded or visualized on a table, which can then be used to select the most relevant targets and to compare the results obtained with different miRNA expression input. ComiR is freely available for academic use at http://www.benoslab.pitt.edu/comir/.

Estrogen represses gene expression through reconfiguring chromatin structures.

Estrogen regulates over a thousand genes, with an equal number of them being induced or repressed. The distinct mechanisms underlying these dual transcriptional effects remain largely unknown. We derived comprehensive views of the transcription machineries assembled at estrogen-responsive genes through integrating multiple types of genomic data. In the absence of estrogen, the majority of genes formed higher-order chromatin structures, including DNA loops tethered to protein complexes involving RNA polymerase II (Pol II), estrogen receptor alpha (ERα) and ERα-pioneer factors. Genes to be 'repressed' by estrogen showed active transcription at promoters and throughout the gene bodies; genes to be 'induced' exhibited active transcription initiation at promoters, but with transcription paused in gene bodies. In the presence of estrogen, the majority of estrogen-induced genes retained the original higher-order chromatin structures, whereas most estrogen-repressed genes underwent a chromatin reconfiguration. For estrogen-induced genes, estrogen enhances transcription elongation, potentially through recruitment of co-activators or release of co-repressors with unique roles in elongation. For estrogen-repressed genes, estrogen treatment leads to chromatin structure reconfiguration, thereby disrupting the originally transcription-efficient chromatin structures. Our in silico studies have shown that estrogen regulates gene expression, at least in part, through modifying previously assembled higher-order complexes, rather than by facilitating de novo assembly of machineries.

Aldosterone regulates microRNAs in the cortical collecting duct to alter sodium transport.

A role for microRNAs (miRs) in the physiologic regulation of sodium transport in the kidney has not been established. In this study, we investigated the potential of aldosterone to alter miR expression in mouse cortical collecting duct (mCCD) epithelial cells. Microarray studies demonstrated the regulation of miR expression by aldosterone in both cultured mCCD and isolated primary distal nephron principal cells. Aldosterone regulation of the most significantly downregulated miRs, mmu-miR-335-3p, mmu-miR-290-5p, and mmu-miR-1983 was confirmed by quantitative RT-PCR. Reducing the expression of these miRs separately or in combination increased epithelial sodium channel (ENaC)-mediated sodium transport in mCCD cells, without mineralocorticoid supplementation. Artificially increasing the expression of these miRs by transfection with plasmid precursors or miR mimic constructs blunted aldosterone stimulation of ENaC transport. Using a newly developed computational approach, termed ComiR, we predicted potential gene targets for the aldosterone-regulated miRs and confirmed ankyrin 3 (Ank3) as a novel aldosterone and miR-regulated protein. A dual-luciferase assay demonstrated direct binding of the miRs with the Ank3-3' untranslated region. Overexpression of Ank3 increased and depletion of Ank3 decreased ENaC-mediated sodium transport in mCCD cells. These findings implicate miRs as intermediaries in aldosterone signaling in principal cells of the distal kidney nephron.

Regulatory role of lncH19 in RAC1 alternative splicing: implication for RAC1B expression in colorectal cancer.

Aberrant alternative splicing events play a critical role in cancer biology, contributing to tumor invasion, metastasis, epithelial-mesenchymal transition, and drug resistance. Recent studies have shown that alternative splicing is a key feature for transcriptomic variations in colorectal cancer, which ranks third among malignant tumors worldwide in both incidence and mortality. Long non-coding RNAs can modulate this process by acting as trans-regulatory agents, recruiting splicing factors, or driving them to specific targeted genes. LncH19 is a lncRNA dis-regulated in several tumor types and, in colorectal cancer, it plays a critical role in tumor onset, progression, and metastasis. In this paper, we found, that in colorectal cancer cells, the long non-coding RNA H19 can bind immature RNAs and splicing factors as hnRNPM and RBFOX2. Through bioinformatic analysis, we identified 57 transcripts associated with lncH19 and containing binding sites for both splicing factors, hnRNPM, and RBFOX2. Among these transcripts, we identified the mRNA of the GTPase-RAC1, whose alternatively spliced isoform, RAC1B, has been ascribed several roles in the malignant transformation. We confirmed, in vitro, the binding of the splicing factors to both the transcripts RAC1 and lncH19. Loss and gain of expression experiments in two colorectal cancer cell lines (SW620 and HCT116) demonstrated that lncH19 is required for RAC1B expression and, through RAC1B, it induces c-Myc and Cyclin-D increase. In vivo, investigation from biopsies of colorectal cancer patients showed higher levels of all the explored genes (lncH19, RAC1B, c-Myc and Cyclin-D) concerning the healthy counterpart, thus supporting our in vitro model. In addition, we identified a positive correlation between lncH19 and RAC1B in colorectal cancer patients. Finally, we demonstrated that lncH19, as a shuttle, drives the splicing factors RBFOX2 and hnRNPM to RAC1 allowing exon retention and RAC1B expression. The data shown in this paper represent the first evidence of a new mechanism of action by which lncH19 carries out its functions as an oncogene by prompting colorectal cancer through the modulation of alternative splicing.

Overexpression of microRNA-1 promotes cardiomyocyte commitment from human cardiovascular progenitors via suppressing WNT and FGF signaling pathways.

Early heart development takes place through a complex series of steps, including the induction of cardiac mesoderm, formation of the cardiovascular progenitor cells and the commitment of cardiovascular lineage cells, such as cardiomyocytes (CMs), smooth muscle cells (SMCs) and endothelial cells (ECs). Recently, microRNAs, a family of endogenous, small non-coding RNAs, have been identified as critical regulators in cardiogenesis and cardiovascular disease. Previous studies demonstrated that microRNA-1 (miR-1) could promote cardiac differentiation from mouse and human embryonic stem (ES) cells. However, the underlying mechanism remained largely unclear. We performed microRNA deep sequencing among human ES cells, ES cell derived-multipotent cardiovascular progenitors (MCPs), and MCP-specified CMs, ECs, and SMCs. A specific enrichment of miR-1 was found in CMs, not in SMCs or ECs, implying a key role of miR-1 in determining cardiovascular commitment from MCPs. When overexpressed in human induced pluripotent stem cells, miR-1 enhanced the expression of key cardiac transcriptional factors and sarcomeric genes. Importantly, we found miR-1 promoted CM differentiation and suppressed EC commitment from MCPs by modulating the activities of WNT and FGF signaling pathways. FZD7 and FRS2 were confirmed as miR-1 targets using luciferase reporter assay and western blot. Overall, this study reveals a fate-switching role of miR-1 at early human cardiovascular commitment stage via suppressing both WNT and FGF signaling pathways.

Novel modeling of combinatorial miRNA targeting identifies SNP with potential role in bone density.

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies.

MBS: a genome browser annotation track for high-confident microRNA binding sites in whole human transcriptome.

MicroRNAs (miRNAs) are small non-coding ribonucleic acids (RNAs) that play a role in many regulatory pathways in eukaryotes. They usually exert their functions by binding mature messenger RNAs. The prediction of the binding targets of the endogenous miRNAs is crucial to unravel the processes they are involved in. In this work, we performed an extensive miRNA binding sites (MBS) prediction over all the annotated transcript sequences and made them available through an UCSC track. MBS annotation track allows to study and visualize the human miRNA binding sites transcriptome-wide in a genome browser, together with any other available information the user is interested in. In the creation of the database that underlies the MBS track, three consolidated algorithms of miRNA binding prediction have been used: PITA, miRanda and TargetScan, and information about the binding sites predicted by all of them has been collected. MBS track displays high-confident miRNA binding sites for the whole length of each human transcript, both coding and non-coding ones. Each annotation can redirect to a web page with the details of the miRNA binding and the involved transcripts. MBS can be easily applied to retrieve specific information such as the effects of alternative splicing on miRNA binding or when a specific miRNA binds an exon-exon junction in the mature RNA. Overall, MBS will be of great help for studying and visualizing, in a user-friendly mode, the predicted miRNA binding sites on all the transcripts arising from a gene or a region of interest. Database URL https://datasharingada.fondazionerimed.com:8080/MBS.

An Overview of In Vitro Assays of 64Cu-, 68Ga-, 125I-, and 99mTc-Labelled Radiopharmaceuticals Using Radiometric Counters in the Era of Radiotheranostics.

Radionuclides are unstable isotopes that mainly emit alpha (α), beta (ß) or gamma (γ) radiation through radiation decay. Therefore, they are used in the biomedical field to label biomolecules or drugs for diagnostic imaging applications, such as positron emission tomography (PET) and/or single-photon emission computed tomography (SPECT). A growing field of research is the development of new radiopharmaceuticals for use in cancer treatments. Preclinical studies are the gold standard for translational research. Specifically, in vitro radiopharmaceutical studies are based on the use of radiopharmaceuticals directly on cells. To date, radiometric ß- and γ-counters are the only tools able to assess a preclinical in vitro assay with the aim of estimating uptake, retention, and release parameters, including time- and dose-dependent cytotoxicity and kinetic parameters. This review has been designed for researchers, such as biologists and biotechnologists, who would like to approach the radiobiology field and conduct in vitro assays for cellular radioactivity evaluations using radiometric counters. To demonstrate the importance of in vitro radiopharmaceutical assays using radiometric counters with a view to radiogenomics, many studies based on 64Cu-, 68Ga-, 125I-, and 99mTc-labeled radiopharmaceuticals have been revised and summarized in this manuscript.

In-silico guided chemical exploration of KDM4A fragments hits.

BACKGROUND: Lysine demethylase enzymes (KDMs) are an emerging class of therapeutic targets, that catalyse the removal of methyl marks from histone lysine residues regulating chromatin structure and gene expression. KDM4A isoform plays an important role in the epigenetic dysregulation in various cancers and is linked to aggressive disease and poor clinical outcomes. Despite several efforts, the KDM4 family lacks successful specific molecular inhibitors. RESULTS: Herein, starting from a structure-based fragments virtual screening campaign we developed a synergic framework as a guide to rationally design efficient KDM4A inhibitors. Commercial libraries were used to create a fragments collection and perform a virtual screening campaign combining docking and pharmacophore approaches. The most promising compounds were tested in-vitro by a Homogeneous Time-Resolved Fluorescence-based assay developed for identifying selective substrate-competitive inhibitors by means of inhibition of H3K9me3 peptide demethylation. 2-(methylcarbamoyl)isonicotinic acid was identified as a preliminary active fragment, displaying inhibition of KDM4A enzymatic activity. Its chemical exploration was deeply investigated by computational and experimental approaches which allowed a rational fragment growing process. The in-silico studies guided the development of derivatives designed as expansion of the primary fragment hit and provided further knowledge on the structure-activity relationship. CONCLUSIONS: Our study describes useful insights into key ligand-KDM4A protein interaction and provides structural features for the development of successful selective KDM4A inhibitors.

Caspase-8 activation by cigarette smoke induces pro-inflammatory cell death of human macrophages exposed to lipopolysaccharide.

Cigarette smoking impairs the lung innate immune response making smokers more susceptible to infections and severe symptoms. Dysregulation of cell death is emerging as a key player in chronic inflammatory conditions. We have recently reported that short exposure of human monocyte-derived macrophages (hMDMs) to cigarette smoke extract (CSE) altered the TLR4-dependent response to lipopolysaccharide (LPS). CSE caused inhibition of the MyD88-dependent inflammatory response and activation of TRIF/caspase-8/caspase-1 pathway leading to Gasdermin D (GSDMD) cleavage and increased cell permeability. Herein, we tested the hypothesis that activation of caspase-8 by CSE increased pro-inflammatory cell death of LPS-stimulated macrophages. To this purpose, we measured apoptotic and pyroptotic markers as well as the expression/release of pro-inflammatory mediators in hMDMs exposed to LPS and CSE, alone or in combination, for 6 and 24 h. We show that LPS/CSE-treated hMDMs, but not cells treated with CSE or LPS alone, underwent lytic cell death (LDH release) and displayed apoptotic features (activation of caspase-8 and -3/7, nuclear condensation, and mitochondrial membrane depolarization). Moreover, the negative regulator of caspase-8, coded by CFLAR gene, was downregulated by CSE. Activation of caspase-3 led to Gasdermin E (GSDME) cleavage. Notably, lytic cell death caused the release of the damage-associated molecular patterns (DAMPs) heat shock protein-60 (HSP60) and S100A8/A9. This was accompanied by an impaired inflammatory response resulting in inhibited and delayed release of IL6 and TNF. Of note, increased cleaved caspase-3, higher levels of GSDME and altered expression of cell death-associated genes were found in alveolar macrophages of smoker subjects compared to non-smoking controls. Overall, our findings show that CSE sensitizes human macrophages to cell death by promoting pyroptotic and apoptotic pathways upon encountering LPS. We propose that while the delayed inflammatory response may result in ineffective defenses against infections, the observed cell death associated with DAMP release may contribute to establish chronic inflammation. CS exposure sensitizes human macrophages to pro-inflammatory cell death. Upon exposure to LPS, CS inhibits the TLR4/MyD88 inflammatory response, downregulating the pro-inflammatory genes TNF and IL6 and the anti-apoptotic gene CFLAR, known to counteract caspase-8 activity. CS enhances caspase-8 activation through TLR4/TRIF, with a partial involvement of RIPK1, resulting on the activation of caspase-1/GSDMD axis leading to increased cell permeability and DAMP release through gasdermin pores [19]. At later timepoints caspase-3 becomes strongly activated by caspase-8 triggering apoptotic events which are associated with mitochondrial membrane depolarization, gasdermin E cleavage and secondary necrosis with consequent massive DAMP release.

Repetitive Sequence Transcription in Breast Cancer.

Repetitive sequences represent about half of the human genome. They are actively transcribed and play a role during development and in epigenetic regulation. The altered activity of repetitive sequences can lead to genomic instability and they can contribute to the establishment or the progression of degenerative diseases and cancer transformation. In this work, we analyzed the expression profiles of DNA repetitive sequences in the breast cancer specimens of the HMUCC cohort. Satellite expression is generally upregulated in breast cancers, with specific families upregulated per histotype: in HER2-enriched cancers, they are the human satellite II (HSATII), in luminal A and B, they are part of the ALR family and in triple-negative, they are part of SAR and GSAT families, together with a perturbation in the transcription from endogenous retroviruses and their LTR sequences. We report that the background expression of repetitive sequences in healthy tissues of cancer patients differs from the tissues of non-cancerous controls. To conclude, peculiar patterns of expression of repetitive sequences are reported in each specimen, especially in the case of transcripts arising from satellite repeats.

Moving Towards Induced Pluripotent Stem Cell-based Therapies with Artificial Intelligence and Machine Learning.

The advent of induced pluripotent stem cell (iPSC) technology, which allows to transform one cell type into another, holds the promise to produce therapeutic cells and organs on demand. Realization of this objective is contingent on the ability to demonstrate quality and safety of the cellular product for its intended use. Bottlenecks and backlogs to the clinical use of iPSCs have been fully outlined and a need has emerged for safer and standardized protocols to trigger cell reprogramming and functional differentiation. Amidst great challenges, in particular associated with lengthy culture time and laborious cell characterization, a demand for faster and more accurate methods for the validation of cell identity and function at different stages of the iPSC manufacturing process has risen. Artificial intelligence-based methods are proving helpful for these complex tasks and might revolutionize the way iPSCs are managed to create surrogate cells and organs. Here, we briefly review recent progress in artificial intelligence approaches for evaluation of iPSCs and their derivatives in experimental studies.

A multivariate statistical test for differential expression analysis.

Statistical tests of differential expression usually suffer from two problems. Firstly, their statistical power is often limited when applied to small and skewed data sets. Secondly, gene expression data are usually discretized by applying arbitrary criteria to limit the number of false positives. In this work, a new statistical test obtained from a convolution of multivariate hypergeometric distributions, the Hy-test, is proposed to address these issues. Hy-test has been carried out on transcriptomic data from breast and kidney cancer tissues, and it has been compared with other differential expression analysis methods. Hy-test allows implicit discretization of the expression profiles and is more selective in retrieving both differential expressed genes and terms of Gene Ontology. Hy-test can be adopted together with other tests to retrieve information that would remain hidden otherwise, e.g., terms of (1) cell cycle deregulation for breast cancer and (2) "programmed cell death" for kidney cancer.