Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction.

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases.

Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here, we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and OVOL2, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy and discovered a role for IL2 STAT5 signaling in heart failure. Our findings underscore the importance of TF activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

Large-scale DNA sequencing identifies rare variants associated with Systemic Lupus Erythematosus susceptibility in known risk genes.

The identification of rare genetic variants associated to Systemic Lupus Erythematosus (SLE) could also help to understand the pathogenic mechanisms at the basis of the disease. In this study we have analyzed a cohort of 200 Italian SLE patients in order to explore the rare protein-coding variants in five genes (TNFAIP3, STAT4, IL10, TRAF3IP2, and HCP5) already investigated for commons variants found associated in our previous studies. Genomic DNA of 200 SLE patients was sequenced by whole exome sequencing. The identified variants were filtered by frequency and evaluated by in silico predictions. Allelic association analysis was performed with standard Fisher's exact test. Introducing a cutoff at MAF < 0.01, a total of 19 rare variants were identified. Seven of these variants were ultra-rare (MAF < 0.001) and six were absent in the GnomAD database. For TNFAIP3 gene, the variant c.A1939C was observed in 4 SLE patients and it is located in a region enriched in phosphorylation sites and affects the predict affinity of specific kinases. In TRAF3IP2 gene, we observed 5 different rare variants, including the novel variant c.G410A, located in the region that mediates interaction with TRAF6, and therefore a possible risk factor for SLE development. In STAT4 gene, we identified 6 different rare variants. Among these, three missense variants decrease the stability of this protein. Moreover, 3 novel rare variants were detected in 3 SLE patients. In particular, c.A767T variant was predicted as damaging by six prediction tools. Concluding, we have observed that even in genes whose common variability is associated with SLE susceptibility, it is possible to identify rare variants that could have a strong effect in the disease development and could therefore allow a better understanding of the functional domain involved.

Clinical and functional characterization of COL2A1 p.Gly444Ser variant: From a fetal phenotype to a previously undisclosed postnatal phenotype.

COL2A1 gene encodes the alpha-1 chain of type-II procollagen. Heterozygous pathogenic variants are associated with the broad clinical spectrum of genetic diseases known as type-II collagenopathies. We aimed to characterize the NM_001844.5:c.1330G>A;p.Gly444Ser variant detected in the COL2A1 gene through trio-based prenatal exome sequencing in a fetus presenting a severe skeletal phenotype at 31 Gestational Weeks and in his previously undisclosed mild-affected father. Functional studies on father's cutaneous fibroblasts, along with in silico protein modeling and in vitro chondrocytes differentiation, showed intracellular accumulation of collagen-II, its localization in external Golgi vesicles and nuclear morphological alterations. Extracellular matrix showed a disorganized fibronectin network. These results showed that p.Gly444Ser variant alters procollagen molecules processing and the assembly of mature type-II collagen fibrils, according to COL2A1-chain disorganization, displayed by protein modeling. Clinical assessment at 38 y.o., through a reverse-phenotyping approach, revealed limp gait, short and stocky appearance. X-Ray and MRI showed pelvis asymmetry with severe morpho-structural alterations of the femoral heads bilaterally, consistent with a mild form of type-II collagenopathy. This study shows how the fusion of genomics and clinical expertise can drive a diagnosis supported by cellular and bioinformatics studies to effectively establish variants pathogenicity.

Inhibition of exosome biogenesis affects cell motility in heterogeneous sub-populations of paediatric-type diffuse high-grade gliomas.

BACKGROUND: Paediatric-type diffuse High-Grade Gliomas (PDHGG) are highly heterogeneous tumours which include distinct cell sub-populations co-existing within the same tumour mass. We have previously shown that primary patient-derived and optical barcoded single-cell-derived clones function as interconnected networks. Here, we investigated the role of exosomes as a route for inter-clonal communication mediating PDHGG migration and invasion. RESULTS: A comprehensive characterisation of seven optical barcoded single-cell-derived clones obtained from two patient-derived cell lines was performed. These analyses highlighted extensive intra-tumour heterogeneity in terms of genetic and transcriptional profiles between clones as well as marked phenotypic differences including distinctive motility patterns. Live single-cell tracking analysis of 3D migration and invasion assays showed that the single-cell-derived clones display a higher speed and longer travelled distance when in co-culture compared to mono-culture conditions. To determine the role of exosomes in PDHGG inter-clonal cross-talks, we isolated exosomes released by different clones and characterised them in terms of marker expression, size and concentration. We demonstrated that exosomes are actively internalized by the cells and that the inhibition of their biogenesis, using the phospholipase inhibitor GW4689, significantly reduced the cell motility in mono-culture and more prominently when the cells from the clones were in co-culture. Analysis of the exosomal miRNAs, performed with a miRNome PCR panel, identified clone-specific miRNAs and a set of miRNA target genes involved in the regulation of cell motility/invasion/migration. These genes were found differentially expressed in co-culture versus mono-culture conditions and their expression levels were significantly modulated upon inhibition of exosome biogenesis. CONCLUSIONS: In conclusion, our study highlights for the first time a key role for exosomes in the inter-clonal communication in PDHGG and suggests that interfering with the exosome biogenesis pathway may be a valuable strategy to inhibit cell motility and dissemination for these specific diseases.

Exploring the landscape of tools and resources for the analysis of long non-coding RNAs.

In recent years, research on long non-coding RNAs (lncRNAs) has gained considerable attention due to the increasing number of newly identified transcripts. Several characteristics make their functional evaluation challenging, which called for the urgent need to combine molecular biology with other disciplines, including bioinformatics. Indeed, the recent development of computational pipelines and resources has greatly facilitated both the discovery and the mechanisms of action of lncRNAs. In this review, we present a curated collection of the most recent computational resources, which have been categorized into distinct groups: databases and annotation, identification and classification, interaction prediction, and structure prediction. As the repertoire of lncRNAs and their analysis tools continues to expand over the years, standardizing the computational pipelines and improving the existing annotation of lncRNAs will be crucial to facilitate functional genomics studies.

Looking for Plant microRNAs in Human Blood Samples: Bioinformatics Evidence and Perspectives.

Literature has proposed the existence of a cross kingdom regulation (CRK) between human and plants. In this context, microRNAs present in edible plants would be acquired through diet by the consumer's organism and transported via bloodstream to tissues, where they would modulate gene expression. However, the validity of this phenomenon is strongly debated; indeed, some scholars have discussed both the methodologies and the results obtained in previous works. To date, only one study has performed a bioinformatics analysis on small RNA-sequencing data for checking the presence of plant miRNAs (pmiRNAs) in human plasma. For that investigation, the lack of reliable controls, which led to the misidentification of human RNAs as pmiRNAs, has been deeply criticized. Thus, in the present contribution, we aim to demonstrate the existence of pmiRNAs in human blood, adopting a bioinformatics approach characterized by more stringent conditions and filtering. The information obtained from 380 experiments produced in 5 different next generation sequencing (NGS) projects was examined, revealing the presence of 350 circulating pmiRNAs across the analysed data set. Although one of the NGS projects shows results likely to be attributed to sample contamination, the others appear to provide reliable support for the acquisition of pmiRNAs through diet. To infer the potential biological activity of the identified pmiRNAs, we predicted their putative human mRNA targets, finding with great surprise that they appear to be mainly involved in neurogenesis and nervous system development. Unfortunately, no consensus was identified within the sequences of detected pmiRNAs, in order to justify their stability or capability to be preserved in human plasma. We believe that the issue regarding CKR still needs further clarifications, even if the present findings would offer a solid support that this hypothesis is not impossible.

Type I IFNs promote cancer cell stemness by triggering the epigenetic regulator KDM1B.

Cancer stem cells (CSCs) are a subpopulation of cancer cells endowed with high tumorigenic, chemoresistant and metastatic potential. Nongenetic mechanisms of acquired resistance are increasingly being discovered, but molecular insights into the evolutionary process of CSCs are limited. Here, we show that type I interferons (IFNs-I) function as molecular hubs of resistance during immunogenic chemotherapy, triggering the epigenetic regulator demethylase 1B (KDM1B) to promote an adaptive, yet reversible, transcriptional rewiring of cancer cells towards stemness and immune escape. Accordingly, KDM1B inhibition prevents the appearance of IFN-I-induced CSCs, both in vitro and in vivo. Notably, IFN-I-induced CSCs are heterogeneous in terms of multidrug resistance, plasticity, invasiveness and immunogenicity. Moreover, in breast cancer (BC) patients receiving anthracycline-based chemotherapy, KDM1B positively correlated with CSC signatures. Our study identifies an IFN-I → KDM1B axis as a potent engine of cancer cell reprogramming, supporting KDM1B targeting as an attractive adjunctive to immunogenic drugs to prevent CSC expansion and increase the long-term benefit of therapy.

Dissecting the Genome for Drug Response Prediction.

The prediction of the cancer cell lines sensitivity to a specific treatment is one of the current challenges in precision medicine. With omics and pharmacogenomics data being available for over 1000 cancer cell lines, several machine learning and deep learning algorithms have been proposed for drug sensitivity prediction. However, deciding which omics data to use and which computational methods can efficiently incorporate data from different sources is the challenge which several research groups are working on. In this review, we summarize recent advances in the representative computational methods that have been developed in the last 2 years on three public datasets: COSMIC, CCLE, NCI-60. These methods aim to improve the prediction of the cancer cell lines sensitivity to a given treatment by incorporating drug's chemical information in the input or using a priori feature selection. Finally, we discuss the latest published method which aims to improve the prediction of clinical drug response of real patients starting from cancer cell line molecular profiles.

Variation in the co-expression profile highlights a loss of miRNA-mRNA regulation in multiple cancer types.

Recent research provides insight into the ability of miRNA to regulate various pathways in several cancer types. Despite their involvement in the regulation of the mRNA via targeting the 3'UTR, there are relatively few studies examining the changes in these regulatory mechanisms specific to single cancer types or shared between different cancer types. We analyzed samples where both miRNA and mRNA expression had been measured and performed a thorough correlation analysis on 7494 experimentally validated human miRNA-mRNA target-gene pairs in both healthy and tumoral samples. We show how more than 90% of these miRNA-mRNA interactions show a loss of regulation in the tumoral samples compared with their healthy counterparts. As expected, we found shared miRNA-mRNA dysregulated pairs among different tumors of the same tissue. However, anatomically different cancers also share multiple dysregulated interactions, suggesting that some cancer-related mechanisms are not tumor-specific. 2865 unique miRNA-mRNA pairs were identified across 13 cancer types, ≈ 40% of these pairs showed a loss of correlation in the tumoral samples in at least 2 out of the 13 analyzed cancers. Specifically, miR-200 family, miR-155 and miR-1 were identified, based on the computational analysis described below, as the miRNAs that potentially lose the highest number of interactions across different samples (only literature-based interactions were used for this analysis). Moreover, the miR-34a/ALDH2 and miR-9/MTHFD2 pairs show a switch in their correlation between healthy and tumor kidney samples suggesting a possible change in the regulation exerted by the miRNAs. Interestingly, the expression of these mRNAs is also associated with the overall survival. The disruption of miRNA regulation on its target, therefore, suggests the possible involvement of these pairs in cell malignant functions. The analysis reported here shows how the regulation of miRNA-mRNA interactions strongly differs between healthy and tumoral cells, based on the strong correlation variation between miRNA and its target that we obtained by analyzing the expression data of healthy and tumor tissue in highly reliable miRNA-target pairs. Finally, a go term enrichment analysis shows that the critical pairs identified are involved in cellular adhesion, proliferation, and migration.

Conserved exchange of paralog proteins during neuronal differentiation.

Gene duplication enables the emergence of new functions by lowering the evolutionary pressure that is posed on the ancestral genes. Previous studies have highlighted the role of specific paralog genes during cell differentiation, for example, in chromatin remodeling complexes. It remains unexplored whether similar mechanisms extend to other biological functions and whether the regulation of paralog genes is conserved across species. Here, we analyze the expression of paralogs across human tissues, during development and neuronal differentiation in fish, rodents and humans. Whereas ∼80% of paralog genes are co-regulated, a subset of paralogs shows divergent expression profiles, contributing to variability of protein complexes. We identify 78 substitutions of paralog pairs that occur during neuronal differentiation and are conserved across species. Among these, we highlight a substitution between the paralogs SEC23A and SEC23B members of the COPII complex. Altering the ratio between these two genes via RNAi-mediated knockdown is sufficient to influence neuron differentiation. We propose that remodeling of the vesicular transport system via paralog substitutions is an evolutionary conserved mechanism enabling neuronal differentiation.

Early life adversity affecting the attachment bond alters ventral tegmental area transcriptomic patterning and behavior almost exclusively in female mice.

Early life experiences that affect the attachment bond formation can alter developmental trajectories and result in pathological outcomes in a sex-related manner. However, the molecular basis of sex differences is quite unknown. The dopaminergic system originating from the ventral tegmental area has been proposed to be a key mediator of this process. Here we exploited a murine model of early adversity (Repeated Cross Fostering, RCF) to test how interfering with the attachment bond formation affects the VTA-related functions in a sex-specific manner. Through a comprehensive behavioral screening, within the NiH RDoC framework, and by next-generation RNA-Seq experiments, we analyzed the long-lasting effect of RCF on behavioral and transcriptional profiles related to the VTA, across two different inbred strains of mouse in both sexes. We found that RCF impacted to an extremely greater extent VTA-related behaviors in females than in males and this result mirrored the transcriptional alterations in the VTA that were almost exclusively observed in females. The sexual dimorphism was conserved across two different inbred strains in spite of their divergent long lasting consequences of RCF exposure. Our data suggest that to be female primes a sub-set of genes to respond to early environmental perturbations. This is, to the best of our knowledge, the first evidence of an almost exclusive effect of early life experiences on females, thus mirroring the extremely stronger impact of precocious aversive events reported in clinical studies in women.

COTAN: scRNA-seq data analysis based on gene co-expression.

Estimating the co-expression of cell identity factors in single-cell is crucial. Due to the low efficiency of scRNA-seq methodologies, sensitive computational approaches are critical to accurately infer transcription profiles in a cell population. We introduce COTAN, a statistical and computational method, to analyze the co-expression of gene pairs at single cell level, providing the foundation for single-cell gene interactome analysis. The basic idea is studying the zero UMI counts' distribution instead of focusing on positive counts; this is done with a generalized contingency tables framework. COTAN can assess the correlated or anti-correlated expression of gene pairs, providing a new correlation index with an approximate p-value for the associated test of independence. COTAN can evaluate whether single genes are differentially expressed, scoring them with a newly defined global differentiation index. Similarly to correlation network analysis, it provides ways to plot and cluster genes according to their co-expression pattern with other genes, effectively helping the study of gene interactions, becoming a new tool to identify cell-identity markers. We assayed COTAN on two neural development datasets with very promising results. COTAN is an R package that complements the traditional single cell RNA-seq analysis and it is available at https://github.com/seriph78/COTAN.

Variants in MHY7 Gene Cause Arrhythmogenic Cardiomyopathy.

BACKGROUND: Arrhythmogenic Cardiomyopathy (ACM) is a disease of the cardiac muscle, characterized by frequent ventricular arrhythmias and functional/ structural abnormalities, mainly of the right ventricle. To date, 20 different genes have been associated with ACM and the majority of them encode for desmosomal proteins. In this study, we describe the characterization of two novel variants in MHY7 gene, segregating in two ACM families. MYH7 encodes for myosin heavy chain ß (MHC-ß) isoform, involved in cardiac muscle contractility. METHOD AND RESULTS: In family A, the autopsy revealed ACM with biventricular involvement in both the proband and his father. In family B, the proband had been diagnosed as affected by ACM and implanted with implantable cardioverter defibrillator (ICD), due to ECG evidence of monomorphic ventricular tachycardia after syncope. After clinical evaluation, a molecular diagnosis was performed using a NGS custom panel. The two novel variants identified predicted damaging, located in a highly conserved domain: c. 2630T>C is not described while c.2609G>A has a frequency of 0.00000398. In silico analyses evaluated the docking characteristics between proteins using the Haddock2.2 webserver. CONCLUSIONS: Our results reveal two variants in sarcomeric genes to be the molecular cause of ACM, further increasing the genetic heterogeneity of the disease; in fact, sarcomeric variants are usually associated with HCM phenotype. Studies on the role of sarcomere genes in the pathogenesis of ACM are surely recommended in those ACM patients negative for desmosomal mutation screening.

BRIO: a web server for RNA sequence and structure motif scan.

The interaction between RNA and RNA-binding proteins (RBPs) has a key role in the regulation of gene expression, in RNA stability, and in many other biological processes. RBPs accomplish these functions by binding target RNA molecules through specific sequence and structure motifs. The identification of these binding motifs is therefore fundamental to improve our knowledge of the cellular processes and how they are regulated. Here, we present BRIO (BEAM RNA Interaction mOtifs), a new web server designed for the identification of sequence and structure RNA-binding motifs in one or more RNA molecules of interest. BRIO enables the user to scan over 2508 sequence motifs and 2296 secondary structure motifs identified in Homo sapiens and Mus musculus, in three different types of experiments (PAR-CLIP, eCLIP, HITS). The motifs are associated with the binding of 186 RBPs and 69 protein domains. The web server is freely available at http://brio.bio.uniroma2.it.

A eutherian-specific microRNA controls the translation of Satb2 in a model of cortical differentiation.

Cerebral cortical development is controlled by key transcription factors that specify the neuronal identities in the different layers. The mechanisms controlling their expression in distinct cells are only partially known. We investigated the expression and stability of Tbr1, Bcl11b, Fezf2, Satb2, and Cux1 mRNAs in single developing mouse cortical cells. We observe that Satb2 mRNA appears much earlier than its protein and in a set of cells broader than expected, suggesting an initial inhibition of its translation, subsequently released during development. Mechanistically, Satb2 3'UTR modulates protein translation of GFP reporters during mouse corticogenesis. We select miR-541, a eutherian-specific miRNA, and miR-92a/b as the best candidates responsible for SATB2 inhibition, being strongly expressed in early and reduced in late progenitor cells. Their inactivation triggers robust and premature SATB2 translation in both mouse and human cortical cells. Our findings indicate RNA interference as a major mechanism in timing cortical cell identities.

Motif Discovery from CLIP Experiments.

RNA primary and secondary motif discovery is an important step in the annotation and characterization of unknown interaction dynamics between RNAs and RNA-Binding Proteins, and several methods have been developed to meet the need of fast and efficient discovery of interaction motifs. Recent advances have increased the amount of data produced by experimental assays and there is no available method suitable for the analysis of all type of results. Here we present a simple workflow to help choosing the more appropriate method, depending on the starting situation, among the three algorithms that best cover the landscape of approaches. A detailed analysis is presented to highlight the need for different algorithms in different working settings. In conclusion, the proposed workflow depends on the nature of the starting data and on the availability of RNA annotations.

Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments.

Structural characterization of RNAs is a dynamic field, offering many modelling possibilities. RNA secondary structure models are usually characterized by an encoding that depicts structural information of the molecule through string representations or graphs. In this work, we provide a generalization of the BEAR encoding (a context-aware structural encoding we previously developed) by expanding the set of alignments used for the construction of substitution matrices and then applying it to secondary structure encodings ranging from fine-grained to more coarse-grained representations. We also introduce a re-interpretation of the Shannon Information applied on RNA alignments, proposing a new scoring metric, the Relative Information Gain (RIG). The RIG score is available for any position in an alignment, showing how different levels of detail encoded in the RNA representation can contribute differently to convey structural information. The approaches presented in this study can be used alongside state-of-the-art tools to synergistically gain insights into the structural elements that RNAs and RNA families are composed of. This additional information could potentially contribute to their improvement or increase the degree of confidence in the secondary structure of families and any set of aligned RNAs.

COVID-19 and Genetic Variants of Protein Involved in the SARS-CoV-2 Entry into the Host Cells.

The recent global COVID-19 public health emergency is caused by SARS-CoV-2 infections and can manifest extremely variable clinical symptoms. Host human genetic variability could influence susceptibility and response to infection. It is known that ACE2 acts as a receptor for this pathogen, but the viral entry into the target cell also depends on other proteins. The aim of this study was to investigate the variability of genes coding for these proteins involved in the SARS-CoV-2 entry into the cells. We analyzed 131 COVID-19 patients by exome sequencing and examined the genetic variants of TMPRSS2, PCSK3, DPP4, and BSG genes. In total we identified seventeen variants. In PCSK3 gene, we observed a missense variant (c.893G>A) statistically more frequent compared to the EUR GnomAD reference population and a missense mutation (c.1906A>G) not found in the GnomAD database. In TMPRSS2 gene, we observed a significant difference in the frequency of c.331G>A, c.23G>T, and c.589G>A variant alleles in COVID-19 patients, compared to the corresponding allelic frequency in GnomAD. Genetic variants in these genes could influence the entry of the SARS-CoV-2. These data also support the hypothesis that host genetic variability may contribute to the variability in infection susceptibility and severity.