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1.
Int J Mol Sci ; 21(11)2020 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-32517089

RESUMO

Long non-coding RNAs (lncRNAs) are increasingly being identified as crucial regulators in pathologies like cancer. High-grade serous ovarian carcinoma (HGSC) is the most common subtype of ovarian cancer (OC), one of the most lethal gynecological malignancies. LncRNAs, especially in cancers such as HGSC, could play a valuable role in diagnosis and even therapy. From RNA-sequencing analysis performed between an OC cell line, SKOV3, and a Fallopian Tube (FT) cell line, FT194, an important long non-coding RNA, HAND2 Anti sense RNA 1 (HAND2-AS1), was observed to be significantly downregulated in OCs when compared to FT. Its downregulation in HGSC was validated in different datasets and in a panel of HGSC cell lines. Furthermore, this study shows that the downregulation of HAND2-AS1 is caused by promoter hypermethylation in HGSC and behaves as a tumor suppressor in HGSC cell lines. Since therapeutic relevance is of key importance in HGSC research, for the first time, HAND2-AS1 upregulation was demonstrated to be one of the mechanisms through which HDAC inhibitor Panobinostat could be used in a strategy to increase HGSC cells' sensitivity to chemotherapeutic agents currently used in clinical trials. To unravel the mechanism by which HAND2-AS1 exerts its role, an in silico mRNA network was constructed using mRNAs whose expressions were positively and negatively correlated with this lncRNA in HGSC. Finally, a putative ceRNA network with possible miRNA targets of HAND2-AS1 and their mRNA targets was constructed, and the enriched Gene Ontology (GO) biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified.


Assuntos
Cistadenocarcinoma Seroso/genética , Regulação Neoplásica da Expressão Gênica , Genes Supressores de Tumor , Neoplasias Ovarianas/genética , Interferência de RNA , RNA Longo não Codificante/genética , Linhagem Celular Tumoral , Movimento Celular/genética , Proliferação de Células , Sobrevivência Celular/genética , Cistadenocarcinoma Seroso/patologia , Metilação de DNA , Feminino , Inibidores de Histona Desacetilases/farmacologia , Humanos , MicroRNAs/genética , Gradação de Tumores , Estadiamento de Neoplasias , Neoplasias Ovarianas/patologia , Regiões Promotoras Genéticas
2.
BMC Bioinformatics ; 20(Suppl 4): 168, 2019 Apr 18.
Artigo em Inglês | MEDLINE | ID: mdl-30999839

RESUMO

BACKGROUND: Next Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This 'misalignment' can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Investigating the source of the unmapped reads is definitely important to better assess the quality of the whole experiment and to check for possible downstream or upstream 'contamination' from exogenous nucleic acids. RESULTS: Here we propose DecontaMiner, a tool to unravel the presence of contaminating sequences among the unmapped reads. It uses a subtraction approach to identify bacteria, fungi and viruses genome contamination. DecontaMiner generates several output files to track all the processed reads, and to provide a complete report of their characteristics. The good quality matches on microorganism genomes are counted and compared among samples. DecontaMiner builds an offline HTML page containing summary statistics and plots. The latter are obtained using the state-of-the-art D3 javascript libraries. DecontaMiner has been mainly used to detect contamination in human RNA-Seq data. The software is freely available at http://www-labgtp.na.icar.cnr.it/decontaminer . CONCLUSIONS: DecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline.


Assuntos
Contaminação por DNA , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Bactérias/genética , Fungos/genética , Humanos , Software , Vírus/genética
3.
BMC Bioinformatics ; 20(Suppl 4): 162, 2019 Apr 18.
Artigo em Inglês | MEDLINE | ID: mdl-30999849

RESUMO

BACKGROUND: Obesity is a complex disorder associated with an increased risk of developing several comorbid chronic diseases, including postmenopausal breast cancer. Although many studies have investigated this issue, the link between body weight and either risk or poor outcome of breast cancer is still to characterize. Systems biology approaches, based on the integration of multiscale models and data from a wide variety of sources, are particularly suitable for investigating the underlying molecular mechanisms of complex diseases. In this scenario, GEnome-scale metabolic Models (GEMs) are a valuable tool, since they represent the metabolic structure of cells and provide a functional scaffold for simulating and quantifying metabolic fluxes in living organisms through constraint-based mathematical methods. The integration of omics data into the structural information described by GEMs allows to build more accurate descriptions of metabolic states. RESULTS: In this work, we exploited gene expression data of postmenopausal breast cancer obese and lean patients to simulate a curated GEM of the human adipocyte, available in the Human Metabolic Atlas database. To this aim, we used a published algorithm which exploits a data-driven approach to overcome the limitation of defining a single objective function to simulate the model. The flux solutions were used to build condition-specific graphs to visualise and investigate the reaction networks and their properties. In particular, we performed a network topology differential analysis to search for pattern differences and identify the principal reactions associated with significant changes across the two conditions under study. CONCLUSIONS: Metabolic network models represent an important source to study the metabolic phenotype of an organism in different conditions. Here we demonstrate the importance of exploiting Next Generation Sequencing data to perform condition-specific GEM analyses. In particular, we show that the qualitative and quantitative assessment of metabolic fluxes modulated by gene expression data provides a valuable method for investigating the mechanisms associated with the phenotype under study, and can foster our interpretation of biological phenomena.


Assuntos
Neoplasias da Mama/genética , Genoma Humano , Modelos Genéticos , Obesidade/genética , Transcriptoma/genética , Proteína de Transporte de Acila/metabolismo , Ácidos Graxos/metabolismo , Feminino , Perfilação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Gotículas Lipídicas/metabolismo , Redes e Vias Metabólicas/genética , Reprodutibilidade dos Testes , Magreza/genética
4.
Int J Mol Sci ; 20(23)2019 Dec 03.
Artigo em Inglês | MEDLINE | ID: mdl-31816915

RESUMO

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the "RankerGUI pipeline", a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms' data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.


Assuntos
Algoritmos , Biologia Computacional/métodos , Perfilação da Expressão Gênica , Interface Usuário-Computador , Regulação da Expressão Gênica , Ontologia Genética , Humanos , Neoplasias/genética , Transdução de Sinais/genética
5.
BMC Bioinformatics ; 19(Suppl 2): 48, 2018 03 08.
Artigo em Inglês | MEDLINE | ID: mdl-29536823

RESUMO

BACKGROUND: System toxicology aims at understanding the mechanisms used by biological systems to respond to toxicants. Such understanding can be leveraged to assess the risk of chemicals, drugs, and consumer products in living organisms. In system toxicology, machine learning techniques and methodologies are applied to develop prediction models for classification of toxicant exposure of biological systems. Gene expression data (RNA/DNA microarray) are often used to develop such prediction models. RESULTS: The outcome of the present work is an experimental methodology to develop prediction models, based on robust gene signatures, for the classification of cigarette smoke exposure and cessation in humans. It is a result of the participation in the recent sbv IMPROVER SysTox Computational Challenge. By merging different gene selection techniques, we obtain robust gene signatures and we investigate prediction capabilities of different off-the-shelf machine learning techniques, such as artificial neural networks, linear models and support vector machines. We also predict six novel genes in our signature, and firmly believe these genes have to be further investigated as biomarkers for tobacco smoking exposure. CONCLUSIONS: The proposed methodology provides gene signatures with top-ranked performances in the prediction of the investigated classification methods, as well as new discoveries in genetic signatures for bio-markers of the smoke exposure of humans.


Assuntos
Algoritmos , Perfilação da Expressão Gênica , Fumar/efeitos adversos , Fumar/genética , Doença/genética , Ontologia Genética , Humanos , Modelos Genéticos , Redes Neurais de Computação , Máquina de Vetores de Suporte
6.
BMC Bioinformatics ; 19(Suppl 2): 58, 2018 03 08.
Artigo em Inglês | MEDLINE | ID: mdl-29536825

RESUMO

BACKGROUND: The endomembrane system, known as secretory pathway, is responsible for the synthesis and transport of protein molecules in cells. Therefore, genes involved in the secretory pathway are essential for the cellular development and function. Recent scientific investigations show that ER and Golgi apparatus may provide a convenient drug target for cancer therapy. On the other hand, it is known that abundantly expressed genes in different cellular organelles share interconnected pathways and co-regulate each other activities. The cross-talks among these genes play an important role in signaling pathways, associated to the regulation of intracellular protein transport. RESULTS: In the present study, we device an integrated approach to understand these complex interactions. We analyze gene perturbation expression profiles, reconstruct a directed gene interaction network and decipher the regulatory interactions among genes involved in protein transport signaling. In particular, we focus on expression signatures of genes involved in the secretory pathway of MCF7 breast cancer cell line. Furthermore, network biology analysis delineates these gene-centric cross-talks at the level of specific modules/sub-networks, corresponding to different signaling pathways. CONCLUSIONS: We elucidate the regulatory connections between genes constituting signaling pathways such as PI3K-Akt, Ras, Rap1, calcium, JAK-STAT, EFGR and FGFR signaling. Interestingly, we determine some key regulatory cross-talks between signaling pathways (PI3K-Akt signaling and Ras signaling pathway) and intracellular protein transport.


Assuntos
Espaço Intracelular/metabolismo , Transdução de Sinais , Análise por Conglomerados , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Células MCF-7 , Fosfatidilinositol 3-Quinases/metabolismo , Transporte Proteico , Proteínas Proto-Oncogênicas c-akt/metabolismo , Transcriptoma , Proteínas ras/metabolismo
7.
Cell Commun Signal ; 15(1): 51, 2017 12 08.
Artigo em Inglês | MEDLINE | ID: mdl-29216878

RESUMO

BACKGROUND: Prostate cancer (PCa), the second most common cancer affecting men worldwide, shows a broad spectrum of biological and clinical behaviour representing the epiphenomenon of an extreme heterogeneity. Androgen deprivation therapy is the mainstay of treatment for advanced forms but after few years the majority of patients progress to castration-resistant prostate cancer (CRPC), a lethal form that poses considerable therapeutic challenges. METHODS: Western blotting, immunocytochemistry, invasion and reporter assays, and in vivo studies were performed to characterize androgen resistant sublines phenotype in comparison to the parental cell line LNCaP. RNA microarray, mass spectrometry, integrative transcriptomic and proteomic differential analysis coupled with GeneOntology and multivariate analyses were applied to identify deregulated genes and proteins involved in CRPC evolution. RESULTS: Treating the androgen-responsive LNCaP cell line for over a year with 10 µM bicalutamide both in the presence and absence of 0.1 nM 5-α-dihydrotestosterone (DHT) we obtained two cell sublines, designated PDB and MDB respectively, presenting several analogies with CRPC. Molecular and functional analyses of PDB and MDB, compared to the parental cell line, showed that both resistant cell lines were PSA low/negative with comparable levels of nuclear androgen receptor devoid of activity due to altered phosphorylation; cell growth and survival were dependent on AKT and p38MAPK activation and PARP-1 overexpression; their malignant phenotype increased both in vitro and in vivo. Performing bioinformatic analyses we highlighted biological processes related to environmental and stress adaptation supporting cell survival and growth. We identified 15 proteins that could direct androgen-resistance acquisition. Eleven out of these 15 proteins were closely related to biological processes involved in PCa progression. CONCLUSIONS: Our models suggest that environmental factors and epigenetic modulation can activate processes of phenotypic adaptation driving drug-resistance. The identified key proteins of these adaptive phenotypes could be eligible targets for innovative therapies as well as molecules of prognostic and predictive value.


Assuntos
Adaptação Fisiológica/efeitos dos fármacos , Androgênios/metabolismo , Resistencia a Medicamentos Antineoplásicos , Neoplasias de Próstata Resistentes à Castração/tratamento farmacológico , Neoplasias de Próstata Resistentes à Castração/fisiopatologia , Linhagem Celular Tumoral , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Humanos , Masculino , Fosforilação/efeitos dos fármacos , Neoplasias de Próstata Resistentes à Castração/metabolismo , Neoplasias de Próstata Resistentes à Castração/patologia , Receptores Androgênicos/metabolismo , Transdução de Sinais/efeitos dos fármacos , Resultado do Tratamento
8.
BMC Bioinformatics ; 17(Suppl 11): 360, 2016 Sep 22.
Artigo em Inglês | MEDLINE | ID: mdl-28185543

RESUMO

BACKGROUND: RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological information is still a key issue, reason for which the creation of web-resources useful for their analysis is highly desiderable. RESULTS: Starting from a previous work, Transcriptator, we present the Atlas of Hydra's vulgaris, an extensible web tool in which its complete transcriptome is annotated. In order to provide to the users an advantageous resource that include the whole functional annotated transcriptome of Hydra vulgaris water polyp, we implemented the Atlas web-tool contains 31.988 accesible and downloadable transcripts of this non-reference model organism. CONCLUSION: Atlas, as a freely available resource, can be considered a valuable tool to rapidly retrieve functional annotation for transcripts differentially expressed in Hydra vulgaris exposed to the distinct experimental treatments. WEB RESOURCE URL: http://www-labgtp.na.icar.cnr.it/Atlas .


Assuntos
Bases de Dados Genéticas , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Hydra/genética , Internet , Anotação de Sequência Molecular , Software , Transcriptoma , Animais , Genômica/métodos
9.
BMC Bioinformatics ; 17(Suppl 12): 376, 2016 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-28185576

RESUMO

BACKGROUND: One of the most challenging issue in the variant calling process is handling the resulting data, and filtering the genes retaining only the ones strictly related to the topic of interest. Several tools permit to gather annotations at different levels of complexity for the detected genes and to group them according to the pathways and/or processes they belong to. However, it might be a time consuming and frustrating task. This is partly due to the size of the file, that might contain many thousands of genes, and to the search of associated variants that requires a gene-by-gene investigation and annotation approach. As a consequence, the initial gene list is often reduced exploiting the knowledge of variants effect, novelty and genotype, with the potential risk of losing meaningful pieces of information. RESULTS: Here we present Var2GO, a new web-based tool to support the annotation and filtering of variants and genes coming from variant calling of high-throughput sequencing data. Var2GO permits to upload either the unprocessed Variant Calling Format file or a table containing the annotated variants. The raw data undergo a preliminary step of variants annotation, using the SnpEff tool, and are converted to a table format. The table is then uploaded into an on the fly generated database. Genes associated to the variants are automatically annotated with the corresponding Gene Ontology terms covering the three GO domains. Using the web interface it is then possible to filter and extract, from the whole list, genes having annotations in the domain of interest, by simply specifying filtering parameters and one or more keywords. The relevance of this tool is demonstrated on exome sequencing data. CONCLUSIONS: Var2GO is a novel tool that implements a topic-based approach, expressly designed to help biologists in narrowing the search of relevant genes coming from variant calling analysis. Its main purpose is to support non-bioinformaticians in handling and processing raw variant calling data through an intuitive web interface. Furthermore, Var2GO offers a complete pipeline that, starting from the raw VCF file, allows to annotate both variants and associated genes and supports the extraction of relevant biological knowledge.


Assuntos
Biologia Computacional/métodos , Variação Genética , Proteínas/genética , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Internet , Software
10.
BMC Bioinformatics ; 17 Suppl 2: 14, 2016 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-26821710

RESUMO

BACKGROUND: Mecp2 null mice model Rett syndrome (RTT) a human neurological disorder affecting females after apparent normal pre- and peri-natal developmental periods. Neuroanatomical studies in cerebral cortex of RTT mouse models revealed delayed maturation of neuronal morphology and autonomous as well as non-cell autonomous reduction in dendritic complexity of postnatal cortical neurons. However, both morphometric parameters and high-resolution expression profile of cortical neurons at embryonic developmental stage have not yet been studied. Here we address these topics by using embryonic neuronal primary cultures from Mecp2 loss of function mouse model. RESULTS: We show that embryonic primary cortical neurons of Mecp2 null mice display reduced neurite complexity possibly reflecting transcriptional changes. We used RNA-sequencing coupled with a bioinformatics comparative approach to identify and remove the contribution of variable and hard to quantify non-neuronal brain cells present in our in vitro cell cultures. CONCLUSIONS: Our results support the need to investigate both Mecp2 morphological as well as molecular effect in neurons since prenatal developmental stage, long time before onset of Rett symptoms.


Assuntos
Encéfalo/patologia , Proteína 2 de Ligação a Metil-CpG/genética , Síndrome de Rett/embriologia , Síndrome de Rett/genética , Animais , Astrócitos/metabolismo , Encéfalo/embriologia , Encéfalo/metabolismo , Córtex Cerebral/metabolismo , Biologia Computacional , Dendritos/metabolismo , Modelos Animais de Doenças , Feminino , Perfilação da Expressão Gênica , Camundongos , Neuroglia/metabolismo , Neurônios/citologia , Síndrome de Rett/patologia , Análise de Sequência de RNA
11.
Med Sci Monit ; 19: 95-101, 2013 Feb 07.
Artigo em Inglês | MEDLINE | ID: mdl-23396358

RESUMO

BACKGROUND: Personalized cancer therapy remains a challenge. In this context, we attempted to identify correlations between tumour angiogenesis, tumour metabolism and tumour cell type. To this aim, we used single=phase multidetector computed tomography (MDCT) and hybrid positron emission tomography-computed tomography (PET/CT) to determine whether net enhancement and standardized uptake value (SUVmax) were correlated with tumour size and cytology in patients affected by non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: Our study included 38 patients (30 men, 8 women, mean age 70) with a NSCLC measuring between 3 cm and 7 cm, using a 16-slice multidetector CT (Brilliance Philips) and with PET-CT (Biograph 16 Siemens Medical Solutions). The following lesion parameters were evaluated: maximum diameter, medium density before contrast injection (CTpre), medium density after contrast injection (CTpost average), density in the most enhanced part of the lesion after contrast (CTpost max), net enhancement, SUVmax, age, and cytology. Correlation coefficient and p-value were computed for each pair of variables. In addition, correlations were computed for each pair of variables, and for all combinations of tumour types. We focused on subsets of data with more than 10 observations, and with correlation r>0.500 and p<0.05. RESULTS: A weak correlation (r=0.32; p=0.048) was found between SUVmax and tumour size; the correlation was stronger for masses larger than 31 mm (r=0.4515; p=0.0268). No other correlations were found among the variables examined. CONCLUSIONS: Our data may have prognostic significance, and could lead to more appropriate surgical treatment and better treatment outcome.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Fluordesoxiglucose F18/farmacocinética , Neoplasias Pulmonares/diagnóstico por imagem , Imagem Multimodal , Tomografia por Emissão de Pósitrons , Tomografia Computadorizada por Raios X , Carga Tumoral , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/patologia , Idoso , Carcinoma Pulmonar de Células não Pequenas/patologia , Meios de Contraste , Feminino , Humanos , Neoplasias Pulmonares/patologia , Masculino
12.
iScience ; 26(10): 107668, 2023 Oct 20.
Artigo em Inglês | MEDLINE | ID: mdl-37720092

RESUMO

Gut microbiota plays a key role in modulating responses to cancer immunotherapy in melanoma patients. Oncolytic viruses (OVs) represent emerging tools in cancer therapy, inducing a potent immunogenic cancer cell death (ICD) and recruiting immune cells in tumors, poorly infiltrated by T cells. We investigated whether the antitumoral activity of oncolytic adenovirus Ad5D24-CpG (Ad-CpG) was gut microbiota-mediated in a syngeneic mouse model of melanoma and observed that ICD was weakened by vancomycin-mediated perturbation of gut microbiota. Ad-CpG efficacy was increased by oral supplementation with Bifidobacterium, reducing melanoma progression and tumor-infiltrating regulatory T cells. Fecal microbiota was enriched in bacterial species belonging to the Firmicutes phylum in mice treated with both Bifidobacterium and Ad-CpG; furthermore, our data suggest that molecular mimicry between melanoma and Bifidobacterium-derived epitopes may favor activation of cross-reactive T cells and constitutes one of the mechanisms by which gut microbiota modulates OVs response.

13.
Sci Data ; 9(1): 607, 2022 10 07.
Artigo em Inglês | MEDLINE | ID: mdl-36207341

RESUMO

Studies about the metabolic alterations during tumorigenesis have increased our knowledge of the underlying mechanisms and consequences, which are important for diagnostic and therapeutic investigations. In this scenario and in the era of systems biology, metabolic networks have become a powerful tool to unravel the complexity of the cancer metabolic machinery and the heterogeneity of this disease. Here, we present TumorMet, a repository of tumor metabolic networks extracted from context-specific Genome-Scale Metabolic Models, as a benchmark for graph machine learning algorithms and network analyses. This repository has an extended scope for use in graph classification, clustering, community detection, and graph embedding studies. Along with the data, we developed and provided Met2Graph, an R package for creating three different types of metabolic graphs, depending on the desired nodes and edges: Metabolites-, Enzymes-, and Reactions-based graphs. This package allows the easy generation of datasets for downstream analysis.


Assuntos
Redes e Vias Metabólicas , Neoplasias , Algoritmos , Análise por Conglomerados , Genoma Humano , Humanos , Neoplasias/genética
14.
Genome Biol Evol ; 12(5): 626-638, 2020 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-32163147

RESUMO

The pervasiveness of sex despite its well-known costs is a long-standing puzzle in evolutionary biology. Current explanations for the success of sex in nature largely rely on the adaptive significance of the new or rare genotypes that sex may generate. Less explored is the possibility that sex-underlying molecular mechanisms can enhance fitness and convey benefits to the individuals that bear the immediate costs of sex. Here, we show that the molecular environment associated with self-fertilization can increase stress resistance in the ciliate Paramecium tetraurelia. This advantage is independent of new genetic variation, coupled with a reduced nutritional input, and offers fresh insights into the mechanistic origin of sex. In addition to providing evidence that the molecular underpinnings of sexual reproduction and the stress response are linked in P. tetraurelia, these findings supply an integrative explanation for the persistence of self-fertilization in this ciliate.


Assuntos
Variação Genética , Paramecium/crescimento & desenvolvimento , Paramecium/genética , Autofertilização , Inanição , Animais
15.
Microorganisms ; 8(11)2020 Nov 17.
Artigo em Inglês | MEDLINE | ID: mdl-33213098

RESUMO

Obesity is a multifactorial disorder, and the gut microbiome has been suggested to contribute to its onset. In order to better clarify the role of the microbiome in obesity, we evaluated the metatranscriptome in duodenal biopsies from a cohort of 23 adult severely obese and lean control subjects using next generation sequencing. Our aim was to provide a general picture of the duodenal metatranscriptome associated with severe obesity. We found altered expressions of human and microbial genes in the obese compared to lean subjects, with most of the gene alterations being present in the carbohydrate, protein, and lipid metabolic pathways. Defects were also present in several human genes involved in epithelial intestinal cells differentiation and function, as well as in the immunity/inflammation pathways. Moreover, the microbial taxa abundance inferred by our transcriptomic data differed in part from the data that we previously evaluated by 16S rRNA in 13/23 individuals of our cohort, particularly concerning the Firmicutes and Proteobacteria phyla abundances. In conclusion, our pilot study provides the first taxonomic and functional characterization of duodenal microbiota in severely obese subjects and lean controls. Our findings suggest that duodenal microbiome and human genes both play a role in deregulating metabolic pathways, likely affecting energy metabolism and thus contributing to the obese phenotype.

16.
Microorganisms ; 8(4)2020 Mar 29.
Artigo em Inglês | MEDLINE | ID: mdl-32235377

RESUMO

The gut microbiota may have an impact on obesity. To date, the majority of studies in obese patients reported microbiota composition in stool samples. The aim of this study was to investigate the duodenal mucosa dysbiosis in adult obese individuals from Campania, a region in Italy with a very high percentage of obese people, to highlight microbial taxa likely associated with obesity. Duodenum biopsies were taken during upper gastrointestinal endoscopy in 19 obese (OB) and 16 lean control subjects (CO) and microbiome studied by 16S rRNA gene sequencing. Duodenal microbiome in our groups consisted of six phyla: Proteobacteria, Firmicutes, Actinobacteria, Fusobacteria, Bacteroidetes and Acidobacteria. Proteobacteria (51.1% vs. 40.1%) and Firmicutes (33.6% vs. 44.9%) were significantly (p < 0.05) more and less abundant in OB compared with CO, respectively. Oribacterium asaccharolyticum, Atopobium parvulum and Fusobacterium nucleatum were reduced (p < 0.01) and Pseudomonadales were increased (p < 0.05) in OB compared with CO. Receiver operating characteristic curve analysis showed Atopobium and Oribacterium genera able to discriminate with accuracy (power = 75% and 78%, respectively) OB from CO. In conclusion, increased Proteobacteria and decreased Firmicutes (Lachnospiraceae) characterized the duodenal microbiome of obese subjects. These data direct to further studies to evaluate the functional role of the dysbiotic-obese-associated signature.

17.
iScience ; 23(4): 100979, 2020 Apr 24.
Artigo em Inglês | MEDLINE | ID: mdl-32222697

RESUMO

Triple-negative breast cancer (TNBC) is a high heterogeneous group of tumors with a distinctly aggressive nature and high rates of relapse. So far, the lack of any known targetable proteins has not allowed a specific anti-tumor treatment. Therefore, the identification of novel agents for specific TNBC targeting and treatment is desperately needed. Here, by integrating cell-SELEX (Systematic Evolution of Ligands by EXponential enrichment) for the specific recognition of TNBC cells with high-throughput sequencing technology, we identified a panel of 2'-fluoropyrimidine-RNA aptamers binding to TNBC cells and their cisplatin- and doxorubicin-resistant derivatives at low nanomolar affinity. These aptamers distinguish TNBC cells from both non-malignant and non-TNBC breast cancer cells and are able to differentiate TNBC histological specimens. Importantly, they inhibit TNBC cell capacity of growing in vitro as mammospheres, indicating they could also act as anti-tumor agents. Therefore, our newly identified aptamers are a valuable tool for selectively dealing with TNBC.

18.
IEEE J Biomed Health Inform ; 23(2): 481-488, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-29994446

RESUMO

Malignant skin lesions are among the most common types of cancer, and automated systems for their early detection are of fundamental importance. We propose SDI+, an unsupervised algorithm for the segmentation of skin lesions in dermoscopic images. It is articulated into three steps, aimed at extracting preliminary information on possible confounding factors, accurately segmenting the lesion, and post-processing the result. The overall method achieves high accuracy on dark skin lesions and can handle several cases where confounding factors could inhibit a clear understanding by a human operator. We present extensive experimental results and comparisons achieved by the SDI+ algorithm on the ISIC 2017 dataset, highlighting the advantages and disadvantages.


Assuntos
Algoritmos , Dermoscopia/métodos , Interpretação de Imagem Assistida por Computador/métodos , Bases de Dados Factuais , Humanos , Pele/diagnóstico por imagem , Neoplasias Cutâneas/diagnóstico por imagem
19.
Int J Biochem Cell Biol ; 108: 51-60, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30633986

RESUMO

Cell heterogeneity studies using single-cell sequencing are gaining great significance in the era of personalized medicine. In particular, characterization of tumor heterogeneity is an emergent issue to improve clinical oncology, since both inter- and intra-tumor level heterogeneity influence the utility and application of molecular classifications through specific biomarkers. Majority of studies have exploited gene expression to discriminate cell types. However, to provide a more nuanced view of the underlying differences, isoform expression and alternative splicing events have to be analyzed in detail. In this study, we utilize publicly available single cell and bulk RNA sequencing datasets of breast cancer cells from primary tumors and immortalized cell lines. Breast cancer is very heterogeneous with well defined molecular subtypes and was therefore chosen for this study. RNA-seq data were explored in terms of genes, isoforms abundance and splicing events. The study was conducted from an average based approach (gene level expression) to detailed and deeper ones (isoforms abundance/splicing events) to perform a comparative analysis, and, thus, highlight the importance of the splicing machinery in defining the tumor heterogeneity. Moreover, here we demonstrate how the investigation of gene isoforms expression can help to identify the appropriate in vitro models. We furthermore extracted marker isoforms, and alternatively spliced genes between and within the different single cell populations to improve the classification of the breast cancer subtypes.


Assuntos
Processamento Alternativo , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Biologia Computacional , Análise de Sequência de RNA , Análise de Célula Única , Linhagem Celular Tumoral , Humanos
20.
Cancers (Basel) ; 11(12)2019 Dec 12.
Artigo em Inglês | MEDLINE | ID: mdl-31842477

RESUMO

High-Grade Serous Ovarian Carcinoma (HGSC) is the most incidental and lethal subtype of epithelial ovarian cancer (EOC) with a high mortality rate of nearly 65%. Recent findings aimed at understanding the pathogenesis of HGSC have attributed its principal source as the Fallopian Tube (FT). To further comprehend the exact mechanism of carcinogenesis, which is still less known, we performed a transcriptome analysis comparing FT and HGSC. Our study aims at exploring new players involved in the development of HGSC from FT, along with their signaling network, and we chose to focus on non-coding RNAs. Non-coding RNAs (ncRNAs) are increasingly observed to be the major regulators of several cellular processes and could have key functions as biological markers, as well as even a therapeutic approach. The most physiologically relevant and significantly dysregulated non-coding RNAs were identified bioinformatically. After analyzing the trend in HGSC and other cancers, MAGI2-AS3 was observed to be an important player in EOC. We assessed its tumor-suppressive role in EOC by means of various assays. Further, we mapped its signaling pathway using its role as a miRNA sponge to predict the miRNAs binding to MAGI2AS3 and showed it experimentally. We conclude that MAGI2-AS3 acts as a tumor suppressor in EOC, specifically in HGSC by sponging miR-15-5p, miR-374a-5p and miR-374b-5p, and altering downstream signaling of certain mRNAs through a ceRNA network.

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