MiR-449a antagonizes EMT through IL-6-mediated trans-signaling in laryngeal squamous cancer.

MicroRNAs (miRNAs) are involved in post-transcriptional gene expression regulation and in mechanisms of cancer growth and metastases. In this light, miRNAs could be promising therapeutic targets and biomarkers in clinical practice. Therefore, we investigated if specific miRNAs and their target genes contribute to laryngeal squamous cell carcinoma (LSCC) development. We found a significant decrease of miR-449a in LSCC patients with nodal metastases (63.3%) compared with patients without nodal involvement (44%). The AmpliSeq Transcriptome of HNO-210 miR-449a-transfected cell lines allowed the identification of IL6-R as a potential target. Moreover, the downregulation of IL6-R and the phosphorylation reduction of the downstream signaling effectors, suggested the inhibition of the IL-6 trans-signaling pathway. These biochemical effects were paralleled by a significant inhibition of invasion and migration in vitro and in vivo, supporting an involvement of epithelial-mesenchymal transition. These findings indicate that miR-449a contributes to suppress the metastasization of LSCC by the IL-6 trans-signaling block and affects sensitivity to external stimuli that mimic pro-inflammatory conditions.

Epigenetic remodeling to improve the efficacy of immunotherapy in human glioblastoma: pre-clinical evidence for development of new immunotherapy approaches.

BACKGROUND: Glioblastoma multiforme (GBM) is a highly aggressive primary brain tumor, that is refractory to standard treatment and to immunotherapy with immune-checkpoint inhibitors (ICI). Noteworthy, melanoma brain metastases (MM-BM), that share the same niche as GBM, frequently respond to current ICI therapies. Epigenetic modifications regulate GBM cellular proliferation, invasion, and prognosis and may negatively regulate the cross-talk between malignant cells and immune cells in the tumor milieu, likely contributing to limit the efficacy of ICI therapy of GBM. Thus, manipulating the tumor epigenome can be considered a therapeutic opportunity in GBM. METHODS: Microarray transcriptional and methylation profiles, followed by gene set enrichment and IPA analyses, were performed to study the differences in the constitutive expression profiles of GBM vs MM-BM cells, compared to the extracranial MM cells and to investigate the modulatory effects of the DNA hypomethylating agent (DHA) guadecitabine among the different tumor cells. The prognostic relevance of DHA-modulated genes was tested by Cox analysis in a TCGA GBM patients' cohort. RESULTS: The most striking differences between GBM and MM-BM cells were found to be the enrichment of biological processes associated with tumor growth, invasion, and extravasation with the inhibition of MHC class II antigen processing/presentation in GBM cells. Treatment with guadecitabine reduced these biological differences, shaping GBM cells towards a more immunogenic phenotype. Indeed, in GBM cells, promoter hypomethylation by guadecitabine led to the up-regulation of genes mainly associated with activation, proliferation, and migration of T and B cells and with MHC class II antigen processing/presentation. Among DHA-modulated genes in GBM, 7.6% showed a significant prognostic relevance. Moreover, a large set of immune-related upstream-regulators (URs) were commonly modulated by DHA in GBM, MM-BM, and MM cells: DHA-activated URs enriched for biological processes mainly involved in the regulation of cytokines and chemokines production, inflammatory response, and in Type I/II/III IFN-mediated signaling; conversely, DHA-inhibited URs were involved in metabolic and proliferative pathways. CONCLUSIONS: Epigenetic remodeling by guadecitabine represents a promising strategy to increase the efficacy of cancer immunotherapy of GBM, supporting the rationale to develop new epigenetic-based immunotherapeutic approaches for the treatment of this still highly deadly disease.

Guadecitabine plus ipilimumab in unresectable melanoma: five-year follow-up and integrated multi-omic analysis in the phase 1b NIBIT-M4 trial.

Association with hypomethylating agents is a promising strategy to improve the efficacy of immune checkpoint inhibitors-based therapy. The NIBIT-M4 was a phase Ib, dose-escalation trial in patients with advanced melanoma of the hypomethylating agent guadecitabine combined with the anti-CTLA-4 antibody ipilimumab that followed a traditional 3 + 3 design (NCT02608437). Patients received guadecitabine 30, 45 or 60 mg/m2/day subcutaneously on days 1 to 5 every 3 weeks starting on week 0 for a total of four cycles, and ipilimumab 3 mg/kg intravenously starting on day 1 of week 1 every 3 weeks for a total of four cycles. Primary outcomes of safety, tolerability, and maximum tolerated dose of treatment were previously reported. Here we report the 5-year clinical outcome for the secondary endpoints of overall survival, progression free survival, and duration of response, and an exploratory integrated multi-omics analysis on pre- and on-treatment tumor biopsies. With a minimum follow-up of 45 months, the 5-year overall survival rate was 28.9% and the median duration of response was 20.6 months. Re-expression of immuno-modulatory endogenous retroviruses and of other repetitive elements, and a mechanistic signature of guadecitabine are associated with response. Integration of a genetic immunoediting index with an adaptive immunity signature stratifies patients/lesions into four distinct subsets and discriminates 5-year overall survival and progression free survival. These results suggest that coupling genetic immunoediting with activation of adaptive immunity is a relevant requisite for achieving long term clinical benefit by epigenetic immunomodulation in advanced melanoma patients.

Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures.

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Landscape of immune-related signatures induced by targeting of different epigenetic regulators in melanoma: implications for immunotherapy.

BACKGROUND: Improvement of efficacy of immune checkpoint blockade (ICB) remains a major clinical goal. Association of ICB with immunomodulatory epigenetic drugs is an option. However, epigenetic inhibitors show a heterogeneous landscape of activities. Analysis of transcriptional programs induced in neoplastic cells by distinct classes of epigenetic drugs may foster identification of the most promising agents. METHODS: Melanoma cell lines, characterized for mutational and differentiation profile, were treated with inhibitors of DNA methyltransferases (guadecitabine), histone deacetylases (givinostat), BET proteins (JQ1 and OTX-015), and enhancer of zeste homolog 2 (GSK126). Modulatory effects of epigenetic drugs were evaluated at the gene and protein levels. Master molecules explaining changes in gene expression were identified by Upstream Regulator (UR) analysis. Gene set enrichment and IPA were used respectively to test modulation of guadecitabine-specific gene and UR signatures in baseline and on-treatment tumor biopsies from melanoma patients in the Phase Ib NIBIT-M4 Guadecitabine + Ipilimumab Trial. Prognostic significance of drug-specific immune-related genes was tested with Timer 2.0 in TCGA tumor datasets. RESULTS: Epigenetic drugs induced different profiles of gene expression in melanoma cell lines. Immune-related genes were frequently upregulated by guadecitabine, irrespective of the mutational and differentiation profiles of the melanoma cell lines, to a lesser extent by givinostat, but mostly downregulated by JQ1 and OTX-015. GSK126 was the least active drug. Quantitative western blot analysis confirmed drug-specific modulatory profiles. Most of the guadecitabine-specific signature genes were upregulated in on-treatment NIBIT-M4 tumor biopsies, but not in on-treatment lesions of patients treated only with ipilimumab. A guadecitabine-specific UR signature, containing activated molecules of the TLR, NF-kB, and IFN innate immunity pathways, was induced in drug-treated melanoma, mesothelioma and hepatocarcinoma cell lines and in a human melanoma xenograft model. Activation of guadecitabine-specific UR signature molecules in on-treatment tumor biopsies discriminated responding from non-responding NIBIT-M4 patients. Sixty-five % of the immune-related genes upregulated by guadecitabine were prognostically significant and conferred a reduced risk in the TCGA cutaneous melanoma dataset. CONCLUSIONS: The DNMT inhibitor guadecitabine emerged as the most promising immunomodulatory agent among those tested, supporting the rationale for usage of this class of epigenetic drugs in combinatorial immunotherapy approaches.

A novel microRNA signature for the detection of melanoma by liquid biopsy.

BACKGROUND: Melanoma is the deadliest form of skin cancer and metastatic disease is associated with a significant survival rate drop. There is an urgent need for consistent tumor biomarkers to scale precision medicine and reduce cancer mortality. Here, we aimed to identify a melanoma-specific circulating microRNA signature and assess its value as a diagnostic tool. METHODS: The study consisted of a discovery phase and two validation phases. Circulating plasma extracellular vesicles (pEV) associated microRNA profiles were obtained from a discovery cohort of metastatic melanoma patients and normal subjects as controls. A pEV-microRNA signature was obtained using a LASSO penalized logistic regression model. The pEV-microRNA signature was subsequently validated both in a publicly available dataset and in an independent internal cohort. RESULTS: We identified and validated in three independent cohorts a panel of melanoma-specific circulating microRNAs that showed high accuracy in differentiating melanoma patients from healthy subjects with an area under the curve (AUC) of 1.00, 0.94 and 0.75 respectively. Investigation of the function of the pEV-microRNA signature evidenced their possible immune suppressive role in melanoma patients. CONCLUSIONS: We demonstrate that a blood test based on circulating microRNAs can non-invasively detect melanoma, offering a novel diagnostic tool for improving standard care. Moreover, we revealed an immune suppressive role for melanoma pEV-microRNAs.

Loss of circadian rhythmicity in bdnf knockout zebrafish larvae.

Brain-derived neurotrophic factor (BDNF) plays a pivotal role in neuronal growth and differentiation, neuronal plasticity, learning, and memory. Using CRISPR/Cas9 technology, we generated a vital Bdnf null mutant line in zebrafish and carried out its molecular and behavioral characterization. Although no defects are evident on a morphological inspection, 66% of coding genes and 37% of microRNAs turned out to be differentially expressed in bdnf -/- compared with wild type sibling embryos. We deeply investigated the circadian clock pathway and confirmed changes in the rhythmic expression of clock (arntl1a, clock1a and clock2) and clock-controlled (aanat2) genes. The modulatory role of Bdnf on the zebrafish circadian clock was then validated by behavioral tests highlighting the absence of circadian activity rhythms in bdnf -/- larvae. The circadian behavior was partially rescued by pharmacological treatment. The bdnf -/- zebrafish line presented here is the first valuable and stable vertebrate model for the study of BDNF-related neurodevelopmental diseases.

Prediction and pan-cancer analysis of mammalian transcripts involved in target directed miRNA degradation.

It is currently unknown how many RNA transcripts are able to induce degradation of microRNAs (miRNA) via the mechanism known as target-directed miRNA degradation (TDMD). We developed TDMDfinder, a computational pipeline that identifies 'high confidence' TDMD interactions in the Human and Mouse transcriptomes by combining sequence alignment and feature selection approaches. Our predictions suggested that TDMD is widespread, with potentially every miRNA controlled by endogenous targets. We experimentally tested 37 TDMDfinder predictions, of which 17 showed TDMD effects as measured by RT-qPCR and small RNA sequencing, linking the miR-17, miR-19, miR-30, miR-221, miR-26 and miR-23 families to novel endogenous TDMDs. In some cases, TDMD was found to affect different members of the same miRNA family selectively. Features like complementarity to the miRNA 3' region, bulge size and hybridization energy appeared to be the main factors determining sensitivity. Computational analyses performed using the multiomic TCGA platform substantiated the involvement of many TDMD transcripts in human cancer and highlighted 36 highly significant interactions, suggesting TDMD as a new potential oncogenic mechanism. In conclusion, TDMDfinder provides the first inventory of bona fide human and mouse TDMDs. Available as a free webtool, TDMDfinder allows users to search for any TDMD interaction of interest by customizing its selection criteria.

Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach.

Leucine-zipper transcription regulator 1 (LZTR1) is a highly mutated tumor suppressor gene, involved in the pathogenesis of several cancer types and developmental disorders. In proteasomal degradation, it acts as an adaptor protein responsible for the recognition and recruitment of substrates to be ubiquitinated in Cullin3-RING ligase E3 (CRL3) machinery. LZTR1 belongs to the BTB-Kelch family, a multi-domain protein where the Kelch propeller plays as the substrate recognition region and for which no experimental structure has been solved. Recently, large effort mutational analyses pointed to the role of disease-associated LZTR1 mutations in the RAS/MAPK signaling pathway and RIT1, a small Ras-related GTPase protein, has been identified by mass spectroscopy to interact with LZTR1. Hence, a better understanding of native structure, molecular mechanism, and substrate specificity would help clarifying the role of LZTR1 in pathological diseases, thus promoting advancement in the development of novel therapeutic strategies. Here, we address the interaction model between adaptor LZTR1 and substrate RIT1 by applying an integrated computational approach, including molecular modeling and docking techniques. We observe that the interaction model LZTR1-RIT1 is stabilized by an electrostatic bond network established between the two protein surfaces, which is reminiscent of homologous ubiquitin ligases complexes. Then, running MD simulations, we characterize differential conformational dynamics of the multi-domain LZTR1, offering interesting implications on the mechanistic role of specific point mutations. We identify G248R and R283Q as damaging mutations involved in the recognition process of the substrate RIT1 and R412C as a possible allosteric mutation from the Kelch to the C-term BTB-domain. Our findings provide important structural insights on targeting CRL3s for drug discovery.

Deep learning predicts short non-coding RNA functions from only raw sequence data.

Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has demanded new computational approaches to annotate their roles. It is widely known that secondary structure is determinant to know RNA function and machine learning based approaches have been successfully proven to predict RNA function from secondary structure information. Here we show that RNA function can be predicted with good accuracy from a lightweight representation of sequence information without the necessity of computing secondary structure features which is computationally expensive. This finding appears to go against the dogma of secondary structure being a key determinant of function in RNA. Compared to recent secondary structure based methods, the proposed solution is more robust to sequence boundary noise and reduces drastically the computational cost allowing for large data volume annotations. Scripts and datasets to reproduce the results of experiments proposed in this study are available at: https://github.com/bioinformatics-sannio/ncrna-deep.

Retinoic Acid Induces Embryonic Stem Cells (ESCs) Transition to 2 Cell-Like State Through a Coordinated Expression of Dux and Duxbl1.

Embryonic stem cells (ESCs) are derived from inner cell mass (ICM) of the blastocyst. In serum/LIF culture condition, they show variable expression of pluripotency genes that mark cell fluctuation between pluripotency and differentiation metastate. The ESCs subpopulation marked by zygotic genome activation gene (ZGA) signature, including Zscan4, retains a wider differentiation potency than epiblast-derived ESCs. We have recently shown that retinoic acid (RA) significantly enhances Zscan4 cell population. However, it remains unexplored how RA initiates the ESCs to 2-cell like reprogramming. Here we found that RA is decisive for ESCs to 2C-like cell transition, and reconstructed the gene network surrounding Zscan4. We revealed that RA regulates 2C-like population co-activating Dux and Duxbl1. We provided novel evidence that RA dependent ESCs to 2C-like cell transition is regulated by Dux, and antagonized by Duxbl1. Our suggested mechanism could shed light on the role of RA on ESC reprogramming.

Detection of long non-coding RNA homology, a comparative study on alignment and alignment-free metrics.

BACKGROUND: Long non-coding RNAs (lncRNAs) represent a novel class of non-coding RNAs having a crucial role in many biological processes. The identification of long non-coding homologs among different species is essential to investigate such roles in model organisms as homologous genes tend to retain similar molecular and biological functions. Alignment-based metrics are able to effectively capture the conservation of transcribed coding sequences and then the homology of protein coding genes. However, unlike protein coding genes the poor sequence conservation of long non-coding genes makes the identification of their homologs a challenging task. RESULTS: In this study we compare alignment-based and alignment-free string similarity metrics and look at promoter regions as a possible source of conserved information. We show that promoter regions encode relevant information for the conservation of long non-coding genes across species and that such information is better captured by alignment-free metrics. We perform a genome wide test of this hypothesis in human, mouse, and zebrafish. CONCLUSIONS: The obtained results persuaded us to postulate the new hypothesis that, unlike protein coding genes, long non-coding genes tend to preserve their regulatory machinery rather than their transcribed sequence. All datasets, scripts, and the prediction tools adopted in this study are available at https://github.com/bioinformatics-sannio/lncrna-homologs .

Identification of long non-coding transcripts with feature selection: a comparative study.

BACKGROUND: The unveiling of long non-coding RNAs as important gene regulators in many biological contexts has increased the demand for efficient and robust computational methods to identify novel long non-coding RNAs from transcripts assembled with high throughput RNA-seq data. Several classes of sequence-based features have been proposed to distinguish between coding and non-coding transcripts. Among them, open reading frame, conservation scores, nucleotide arrangements, and RNA secondary structure have been used with success in literature to recognize intergenic long non-coding RNAs, a particular subclass of non-coding RNAs. RESULTS: In this paper we perform a systematic assessment of a wide collection of features extracted from sequence data. We use most of the features proposed in the literature, and we include, as a novel set of features, the occurrence of repeats contained in transposable elements. The aim is to detect signatures (groups of features) able to distinguish long non-coding transcripts from other classes, both protein-coding and non-coding. We evaluate different feature selection algorithms, test for signature stability, and evaluate the prediction ability of a signature with a machine learning algorithm. The study reveals different signatures in human, mouse, and zebrafish, highlighting that some features are shared among species, while others tend to be species-specific. Compared to coding potential tools and similar supervised approaches, including novel signatures, such as those identified here, in a machine learning algorithm improves the prediction performance, in terms of area under precision and recall curve, by 1 to 24%, depending on the species and on the signature. CONCLUSIONS: Understanding which features are best suited for the prediction of long non-coding RNAs allows for the development of more effective automatic annotation pipelines especially relevant for poorly annotated genomes, such as zebrafish. We provide a web tool that recognizes novel long non-coding RNAs with the obtained signatures from fasta and gtf formats. The tool is available at the following url: http://www.bioinformatics-sannio.org/software/ .

[Diabetes ketoacidosis associated with Guillan-Barré syndrome]. / Cetoacidose diabética associada com síndrome de Guillain-Barré: relato de caso.

Guillain-Barré syndrome (GBS) is a disorder caused by exaggerated immune response to infectious process. Diabetes Melito (DM) is not recognized as one cause of this inflammatory polyradiculoneuropathy with just a few cases of this association been described in the literature so far. We report here the case of a 44 years-old female patient admitted with a history of polyuria, polydipsia, weight loss, asthenia, hyperglycemia (562 mg/dL) and ketoacidosis without any infectious focus. The patient progressed with poliradiculopathy, respiratory insufficiency and liquoric alteration completing the picture of Guillain-Barré syndrome. The patient fully recovered from the neurologic deficit and then stopped with insulin therapy.

Cetoacidose diabética associada com síndrome de Guillain-Barré: relato de caso / Diabetes ketoacidosis associated with Guillan-Barré syndrome

A síndrome de Guillain-Barré (GBS) é uma desordem causada por exacerbada resposta imune aos processos infecciosos. O diabetes melito (DM) não é reconhecido como uma causa desta polirradiculopatia inflamatória, com poucos casos relatados na literatura sobre tal associação. Apresentamos um caso de uma paciente do sexo feminino, 44 anos, admitida com história recente de poliúria, polidipsia, perda de peso e astenia, glicemia de 562 mg/dL, em cetoacidose, sem foco infeccioso. Posteriormente desenvolveu quadro de polirradiculopatia, insuficiência respiratória e alteração liquórica compondo o quadro de GBS. No presente relato, a paciente recuperou-se plenamente do déficit neurológico, assim como da hiperglicemia, configurando quadro de diabetes tipo 2, com tendência à cetoacidose, evoluindo sem insulino-dependência.

Guillain-Barré syndrome (GBS) is a disorder caused by exaggerated immune response to infectious process. Diabetes Melito (DM) is not recognized as one cause of this inflammatory polyradiculoneuropathy with just a few cases of this association been described in the literature so far. We report here the case of a 44 years-old female patient admitted with a history of polyuria, polydipsia, weight loss, asthenia, hyperglycemia (562 mg/dL) and ketoacidosis without any infectious focus. The patient progressed with poliradiculopathy, respiratory insufficiency and liquoric alteration completing the picture of Guillain-Barré syndrome. The patient fully recovered from the neurologic deficit and then stopped with insulin therapy.