Hooked Up from a Distance: Charting Genome-Wide Long-Range Interaction Maps in Neural Cells Chromatin to Identify Novel Candidate Genes for Neurodevelopmental Disorders.

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.

Bridging between Mouse and Human Enhancer-Promoter Long-Range Interactions in Neural Stem Cells, to Understand Enhancer Function in Neurodevelopmental Disease.

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.

miR-182-5p is an evolutionarily conserved Tbx5 effector that impacts cardiac development and electrical activity in zebrafish.

To dissect the TBX5 regulatory circuit, we focused on microRNAs (miRNAs) that collectively contribute to make TBX5 a pivotal cardiac regulator. We profiled miRNAs in hearts isolated from wild-type, CRE, Tbx5lox/+and Tbx5del/+ mice using a Next Generation Sequencing (NGS) approach. TBX5 deficiency in cardiomyocytes increased the expression of the miR-183 cluster family that is controlled by Kruppel-like factor 4, a transcription factor repressed by TBX5. MiR-182-5p, the most highly expressed miRNA of this family, was functionally analyzed in zebrafish. Transient overexpression of miR-182-5p affected heart morphology, calcium handling and the onset of arrhythmias as detected by ECG tracings. Accordingly, several calcium channel proteins identified as putative miR-182-5p targets were downregulated in miR-182-5p overexpressing hearts. In stable zebrafish transgenic lines, we demonstrated that selective miRNA-182-5p upregulation contributes to arrhythmias. Moreover, cardiac-specific down-regulation of miR-182-5p rescued cardiac defects in a zebrafish model of Holt-Oram syndrome. In conclusion, miR-182-5p exerts an evolutionarily conserved role as a TBX5 effector in the onset of cardiac propensity for arrhythmia, and constitutes a relevant target for mediating the relationship between TBX5, arrhythmia and heart development.

Nanopore sequencing data analysis: state of the art, applications and challenges.

The nanopore sequencing process is based on the transit of a DNA molecule through a nanoscopic pore, and since the 90s is considered as one of the most promising approaches to detect polymeric molecules. In 2014, Oxford Nanopore Technologies (ONT) launched a beta-testing program that supplied the scientific community with the first prototype of a nanopore sequencer: the MinION. Thanks to this program, several research groups had the opportunity to evaluate the performance of this novel instrument and develop novel computational approaches for analyzing this new generation of data. Despite the short period of time from the release of the MinION, a large number of algorithms and tools have been developed for base calling, data handling, read mapping, de novo assembly and variant discovery. Here, we face the main computational challenges related to the analysis of nanopore data, and we carry out a comprehensive and up-to-date survey of the algorithmic solutions adopted by the bioinformatic community comparing performance and reporting limits and advantages of using this new generation of sequences for genomic analyses. Our analyses demonstrate that the use of nanopore data dramatically improves the de novo assembly of genomes and allows for the exploration of structural variants with an unprecedented accuracy and resolution. However, despite the impressive improvements reached by ONT in the past 2 years, the use of these data for small-variant calling is still challenging, and at present, it needs to be coupled with complementary short sequences for mitigating the intrinsic biases of nanopore sequencing technology.

The creation and selection of mutations resistant to a gene drive over multiple generations in the malaria mosquito.

Gene drives have enormous potential for the control of insect populations of medical and agricultural relevance. By preferentially biasing their own inheritance, gene drives can rapidly introduce genetic traits even if these confer a negative fitness effect on the population. We have recently developed gene drives based on CRISPR nuclease constructs that are designed to disrupt key genes essential for female fertility in the malaria mosquito. The construct copies itself and the associated genetic disruption from one homologous chromosome to another during gamete formation, a process called homing that ensures the majority of offspring inherit the drive. Such drives have the potential to cause long-lasting, sustainable population suppression, though they are also expected to impose a large selection pressure for resistance in the mosquito. One of these population suppression gene drives showed rapid invasion of a caged population over 4 generations, establishing proof of principle for this technology. In order to assess the potential for the emergence of resistance to the gene drive in this population we allowed it to run for 25 generations and monitored the frequency of the gene drive over time. Following the initial increase of the gene drive we observed a gradual decrease in its frequency that was accompanied by the spread of small, nuclease-induced mutations at the target gene that are resistant to further cleavage and restore its functionality. Such mutations showed rates of increase consistent with positive selection in the face of the gene drive. Our findings represent the first documented example of selection for resistance to a synthetic gene drive and lead to important design recommendations and considerations in order to mitigate for resistance in future gene drive applications.

MicroRNA Expression in the Aqueous Humor of Patients with Diabetic Macular Edema.

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.

RNA sequencing reveals PNN and KCNQ1OT1 as predictive biomarkers of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy.

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.

Early modifications of circulating microRNAs levels in metastatic colorectal cancer patients treated with regorafenib.

Biomarkers able to improve the cost/benefit ratio are urgently needed for metastatic colorectal cancer patients that are eligible to receive regorafenib. Here, we measured plasma levels of ten circulating microRNAs (c-miRNAs) and we investigated their early changes during treatment, as well as possible correlation with clinical outcome. Ten literature-selected c-miRNAs were quantified by qRT-PCR on plasma samples collected at baseline (d1) and after 15 days of treatment (d15). C-miRNAs showing significant changes were further analyzed to establish correlations with outcome. A decision tree-based approach was employed to define a c-miRNA signature able to predict the outcome. Results achieved in an exploratory cohort were tested in a validation group. In the exploratory cohort (n = 34), the levels of c-miR-21 (p = 0.06), c-miR-141 (p = 0.04), and c-miR-601 (p = 0.01) increased at d15 compared with d1. A c-miRNA signature involving c-miR-21, c-miR-221, and c-miR-760 predicted response to treatment (p < 0.0001) and was significantly associated to PFS (HR = 10.68; 95% CI 3.2-35.65; p < 0.0001). In the validation cohort (n = 36), the increase in c-miR-21 (p = 0.02) and c-miR-601 (p = 0.02) levels at d15 was confirmed, but the associations with outcome were not. Our data indicate that early changes of c-miRNA levels might be influenced by regorafenib treatment. However, further studies are needed to establish the predictive power of such modifications.

Systematic evaluation of the microRNAome through miR-CATCHv2.0 identifies positive and negative regulators of BRAF-X1 mRNA.

Here we present miR-CATCHv2.0, an implemented experimental method that allows the identification of the microRNA species directly bound to an RNA of interest. After cross-linking of microRNA::RNA::Ago2 complexes using formaldehyde, the RNA is fragmented using sonication and then subjected to affinity purification using two sets of biotinylated tiling probes (ODD and EVEN). Finally, enriched microRNA species are retrieved by means of small RNA sequencing coupled with an ad hoc analytical workflow. In BRAFV600E mutant A375 melanoma cells, miR-CATCHv2.0 allowed us to identify 20 microRNAs that target X1, the most abundant isoform of BRAF mRNA. These microRNAs fall into different functional classes, according to the effect that they exert (decrease/increase in BRAFV600E mRNA and protein levels) and to the mechanism they use to achieve it (destabilization/stabilization of X1 mRNA or decrease/increase in its translation). microRNA-induced variations in BRAFV600E protein levels are most of the times coupled to consistent variations in pMEK levels, in melanoma cell proliferation in vitro and in sensitivity to the BRAF inhibitor vemurafenib in a xenograft model in zebrafish. However, microRNAs exist that uncouple the degree of activation of the ERK pathway from the levels of BRAFV600E protein. Our study proposes miR-CATCHv2.0 as an effective tool for the identification of direct microRNA-target interactions and, by using such a tool, unveils the complexity of the post-transcriptional regulation to which BRAFV600E and the ERK pathway are subjected in melanoma cells.

Altered Metabolic Profile and Adipocyte Insulin Resistance Mark Severe Liver Fibrosis in Patients with Chronic Liver Disease.

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.

Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2.

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the performance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 outperforms other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprecedented resolution. EXCAVATOR2 is freely available at http://sourceforge.net/projects/excavator2tool/.

The Prostate Cancer Cells Resistant to Docetaxel as in vitro Model for Discovering MicroRNAs Predictive of the Onset of Docetaxel Resistance.

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.

In-silico prediction and deep-DNA sequencing validation indicate phase variation in 115 Neisseria meningitidis genes.

BACKGROUND: The Neisseria meningitidis (Nm) chromosome shows a high abundance of simple sequence DNA repeats (SSRs) that undergo stochastic, reversible mutations at high frequency. This mechanism is reflected in an extensive phenotypic diversity that facilitates Nm adaptation to dynamic environmental changes. To date, phase-variable phenotypes mediated by SSRs variation have been experimentally confirmed for 26 Nm genes. RESULTS: Here we present a population-scale comparative genomic analysis that identified 277 genes and classified them into 52 strong, 60 moderate and 165 weak candidates for phase variation. Deep-coverage DNA sequencing of single colonies grown overnight under non-selective conditions confirmed the presence of high-frequency, stochastic variation in 115 of them, providing circumstantial evidence for their phase variability. We confirmed previous observations of a predominance of variable SSRs within genes for components located on the cell surface or DNA metabolism. However, in addition we identified an unexpectedly broad spectrum of other metabolic functions, and most of the variable SSRs were predicted to induce phenotypic changes by modulating gene expression at a transcriptional level or by producing different protein isoforms rather than mediating on/off translational switching through frameshifts. Investigation of the evolutionary history of SSR contingency loci revealed that these loci were inherited from a Nm ancestor, evolved independently within Nm, or were acquired by Nm through lateral DNA exchange. CONCLUSIONS: Overall, our results have identified a broader and qualitatively different phenotypic diversification of SSRs-mediated stochastic variation than previously documented, including its impact on central Nm metabolism.

Characterization and identification of hidden rare variants in the human genome.

BACKGROUND: By examining the genotype calls generated by the 1000 Genomes Project we discovered that the human reference genome GRCh37 contains almost 20,000 loci in which the reference allele has never been observed in healthy individuals and around 70,000 loci in which it has been observed only in the heterozygous state. RESULTS: We show that a large fraction of this rare reference allele (RRA) loci belongs to coding, functional and regulatory elements of the genome and could be linked to rare Mendelian disorders as well as cancer. We also demonstrate that classical germline and somatic variant calling tools are not capable to recognize the rare allele when present in these loci. To overcome such limitations, we developed a novel tool, named RAREVATOR, that is able to identify and call the rare allele in these genomic positions. By using a small cancer dataset we compared our tool with two state-of-the-art callers and we found that RAREVATOR identified more than 1,500 germline and 22 somatic RRA variants missed by the two methods and which belong to significantly mutated pathways. CONCLUSIONS: These results show that, to date, the investigation of around 100,000 loci of the human genome has been missed by re-sequencing experiments based on the GRCh37 assembly and that our tool can fill the gap left by other methods. Moreover, the investigation of the latest version of the human reference genome, GRCh38, showed that although the GRC corrected almost all insertions and a small part of SNVs and deletions, a large number of functionally relevant RRAs still remain unchanged. For this reason, also future resequencing experiments, based on GRCh38, will benefit from RAREVATOR analysis results. RAREVATOR is freely available at http://sourceforge.net/projects/rarevator .

NRF2 activation by cysteine as a survival mechanism for triple-negative breast cancer cells.

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.

Secreted miR-210-3p, miR-183-5p and miR-96-5p reduce sensitivity to docetaxel in prostate cancer cells.

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.

Heterozygosity for neuronal ceroid lipofuscinosis predisposes to bipolar disorder.

OBJECTIVE: Bipolar disorder is a heritable chronic mental disorder that causes psychosocial impairment through depressive/manic episodes. Familial transmission of bipolar disorder does not follow simple Mendelian patterns of inheritance. The aim of this study was to describe a large family with 12 members affected by bipolar disorder. Whole-exome sequencing was performed for eight members, three of whom were diagnosed with bipolar disorder, and another reported as "borderline." METHODS: Whole-exome sequencing data allowed us to select variants that the affected members had in common, including and excluding the "borderline" individual with moderate anxiety and obsessive-compulsive traits. RESULTS: The results favored designating certain genes as predispositional to bipolar disorder: a heterozygous missense variant in CLN6 resulted in a "borderline" phenotype that, if combined with a heterozygous missense variant in ZNF92, is responsible for the more severe bipolar disorder phenotype. Both rare missense changes are predicted to disrupt protein function. CONCLUSIONS: Loss of both alleles in CLN6 causes neuronal ceroid lipofuscinosis, a severe progressive childhood neurological disorder. Our results indicate that heterozygous CLN6 carriers, previously reported as healthy, may be susceptible to bipolar disorder later in life if associated with additional variants in ZNF92.

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis.

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.

Surfome analysis as a fast track to vaccine discovery: identification of a novel protective antigen for Group B Streptococcus hypervirulent strain COH1.

Safe recombinant vaccines, based on a small number of antigenic proteins, are emerging as the most attractive, cost-effective solution against infectious diseases. In the present work, we confirmed previous data from our laboratory showing that whole viable bacterial cell treatment with proteases followed by the identification of released peptides by mass spectrometry is the method of choice for the rapid and reliable identification of vaccine candidates in Gram-positive bacteria. When applied to the Group B Streptococcus COH1 strain, 43 surface-associated proteins were identified, including all the protective antigens described in the literature as well as a new protective antigen, the cell wall-anchored protein SAN_1485 belonging to the serine-rich repeat protein family. This strategy overcomes the difficulties so far encountered in the identification of novel vaccine candidates and speeds up the entire vaccine discovery process by reducing the number of recombinant proteins to be tested in the animal model.

High-Throughput Identification of miRNA-Target Interactions in Melanoma Using miR-CATCHv2.0.

MicroRNAs (miRNAs) can regulate the expression of potentially every transcript in the cell, and the definition of miRNA-target interactions is crucial to understand their role in all biological processes. However, the identification of the miRNAs that target a specific mRNA remains a challenge. Here, we describe an innovative method called miR-CATCHv2.0 for the high-throughput identification of the miRNA species bound to an RNA of interest. We also describe how this method can overcome the limitations of the current computational and experimental methods available in this field.