Publications by authors named "Nuno A Fonseca"

64 Publications

Modelling the impact of nucleolin expression level on the activity of F3 peptide-targeted pH-sensitive pegylated liposomes containing doxorubicin.

Drug Deliv Transl Res 2021 Apr 15. Epub 2021 Apr 15.

CNC - Center for Neurosciences and Cell Biology, Center for Innovative Biomedicine and Biotechnology (CIBB), Faculty of Medicine (Polo 1), Rua Larga, University of Coimbra, 3004-504, Coimbra, Portugal.

Strategies targeting nucleolin have enabled a significant improvement in intracellular bioavailability of their encapsulated payloads. In this respect, assessment of the impact of target cell heterogeneity and nucleolin homology across species (structurally and functionally) is of major importance. This work also aimed at mathematically modelling the nucleolin expression levels at the cell membrane, binding and internalization of pH-sensitive pegylated liposomes encapsulating doxorubicin and functionalized with the nucleolin-binding F3 peptide (PEGASEMP), and resulting cytotoxicity against cancer cells from mouse, rat, canine, and human origin. Herein, it was shown that nucleolin expression levels were not a limitation on the continuous internalization of F3 peptide-targeted liposomes, despite the saturable nature of the binding mechanism. Modeling enabled the prediction of nucleolin-mediated total doxorubicin exposure provided by the experimental settings of the assessment of PEGASEMP's impact on cell death. The former increased proportionally with nucleolin-binding sites, a measure relevant for patient stratification. This pattern of variation was observed for the resulting cell death in nonsaturating conditions, depending on the cancer cell sensitivity to doxorubicin. This approach differs from standard determination of cytotoxic concentrations, which normally report values of incubation doses rather than the actual intracellular bioactive drug exposure. Importantly, in the context of development of nucleolin-based targeted drug delivery, the structural nucleolin homology (higher than 84%) and functional similarity across species presented herein, emphasized the potential to use toxicological data and other metrics from lower species to infer the dose for a first-in-human trial.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s13346-021-00972-zDOI Listing
April 2021

Comparative Genomics of and pv. Strains Isolated from a Single Walnut Host Tree.

Microorganisms 2021 Mar 17;9(3). Epub 2021 Mar 17.

CIBIO-Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO-Laboratório Associado, Universidade do Porto, Rua Padre Armando Quintas 7, 4485-661 Vairão, Portugal.

The recent report of distinct lineages of pv. and within the same walnut tree revealed that this consortium of walnut-associated includes both pathogenic and nonpathogenic strains. As the implications of this co-colonization are still poorly understood, in order to unveil niche-specific adaptations, the genomes of three strains (CPBF 367, CPBF 424, and CPBF 426) and of an pv. strain (CPBF 427) isolated from a single walnut tree in Loures (Portugal) were sequenced with two different technologies, Illumina and Nanopore, to provide consistent single scaffold chromosomal sequences. General genomic features showed that CPBF 427 has a genome similar to other pv. strains, regarding its size, number, and content of CDSs, while strains show a reduction regarding these features comparatively to pv. strains. Whole genome comparisons revealed remarkable genomic differences between pv. and strains, which translates into different pathogenicity and virulence features, namely regarding type 3 secretion system and its effectors and other secretory systems, chemotaxis-related proteins, and extracellular enzymes. Altogether, the distinct genomic repertoire of may be particularly useful to address pathogenicity emergence and evolution in walnut-associated .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/microorganisms9030624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003016PMC
March 2021

Complete Genome Sequence Obtained by Nanopore and Illumina Hybrid Assembly of Xanthomonas arboricola pv. juglandis CPBF 427, Isolated from Buds of a Walnut Tree.

Microbiol Resour Announc 2021 Mar 11;10(10). Epub 2021 Mar 11.

Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO), InBIO-Laboratório Associado, Universidade do Porto, Vairão, Portugal.

We report the genome sequence of pv. juglandis strain CPBF 427, which was isolated from early-season buds of a diseased walnut tree, suggesting overwinter potential. This study provides a consistent genomic reference for this pathovar and may contribute to addressing the overwinter survival of these walnut pathogens.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1128/MRA.00085-21DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953287PMC
March 2021

Tumour gene expression signature in primary melanoma predicts long-term outcomes.

Nat Commun 2021 02 18;12(1):1137. Epub 2021 Feb 18.

Cambridge Cancer Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.

Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10) and overall survival (HR = 1.61, p = 1.67 × 10), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (p = 7.03 × 10), or published prognostic signatures (p < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-021-21207-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7893180PMC
February 2021

In Vitro and In Vivo Tumor Models for the Evaluation of Anticancer Nanoparticles.

Adv Exp Med Biol 2021 ;1295:271-299

CNC - Center for Neurosciences and Cell Biology, Center for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Faculty of Medicine (Polo 1), Rua Larga, Coimbra, Portugal.

Multiple studies about tumor biology have revealed the determinant role of the tumor microenvironment in cancer progression, resulting from the dynamic interactions between tumor cells and surrounding stromal cells within the extracellular matrix. This malignant microenvironment highly impacts the efficacy of anticancer nanoparticles by displaying drug resistance mechanisms, as well as intrinsic physical and biochemical barriers, which hamper their intratumoral accumulation and biological activity.Currently, two-dimensional cell cultures are used as the initial screening method in vitro for testing cytotoxic nanocarriers. However, this fails to mimic the tumor heterogeneity, as well as the three-dimensional tumor architecture and pathophysiological barriers, leading to an inaccurate pharmacological evaluation.Biomimetic 3D in vitro tumor models, on the other hand, are emerging as promising tools for more accurately assessing nanoparticle activity, owing to their ability to recapitulate certain features of the tumor microenvironment and thus provide mechanistic insights into nanocarrier intratumoral penetration and diffusion rates.Notwithstanding, in vivo validation of nanomedicines remains irreplaceable at the preclinical stage, and a vast variety of more advanced in vivo tumor models is currently available. Such complex animal models (e.g., genetically engineered mice and patient-derived xenografts) are capable of better predicting nanocarrier clinical efficiency, as they closely resemble the heterogeneity of the human tumor microenvironment.Herein, the development of physiologically more relevant in vitro and in vivo tumor models for the preclinical evaluation of anticancer nanoparticles will be discussed, as well as the current limitations and future challenges in clinical translation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/978-3-030-58174-9_12DOI Listing
February 2021

Shedding Light on the African Enigma: In Vitro Testing of Coevolution.

Microorganisms 2021 Jan 25;9(2). Epub 2021 Jan 25.

i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.

The continuous characterization of genome-wide diversity in population and case-cohort samples, allied to the development of new algorithms, are shedding light on host ancestry impact and selection events on various infectious diseases. Especially interesting are the long-standing associations between humans and certain bacteria, such as the case of , which could have been strong drivers of adaptation leading to coevolution. Some evidence on admixed gastric cancer cohorts have been suggested as supporting - coevolution, but reliable experimental data that control both the bacterium and the host ancestries are lacking. Here, we conducted the first in vitro coinfection assays with dual human- and bacterium-matched and -mismatched ancestries, in African and European backgrounds, to evaluate the genome wide gene expression host response to . Our results showed that: (1) the host response to infection was greatly shaped by the human ancestry, with variability on innate immune system and metabolism; (2) African human ancestry showed signs of coevolution with while European ancestry appeared to be maladapted; and (3) mismatched ancestry did not seem to be an important differentiator of gene expression at the initial stages of infection as assayed here.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/microorganisms9020240DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912213PMC
January 2021

Complete Genome Sequences of Walnut-Associated Strains CPBF 367 and CPBF 426 Obtained by Illumina/Nanopore Hybrid Assembly.

Microbiol Resour Announc 2020 Nov 5;9(45). Epub 2020 Nov 5.

CIBIO-Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO-Laboratório Associado, Universidade do Porto, Vairão, Portugal.

We present the complete genome sequences of two strains isolated from buds of a walnut tree. The whole-genome sequences of strains CPBF 367 and CPBF 426 consist of two circular chromosomes of 4,923,218 bp and 4,883,254 bp and two putative plasmids of 45,241 bp and 17,394 bp, respectively. These data may contribute to the understanding of species-specific adaptations to walnut.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1128/MRA.00902-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7645659PMC
November 2020

The InBIO Barcoding Initiative Database: contribution to the knowledge on DNA barcodes of Iberian Plecoptera.

Biodivers Data J 2020 7;8:e55137. Epub 2020 Jul 7.

CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto Vairão Portugal.

Background: The use of DNA barcoding allows unprecedented advances in biodiversity assessments and monitoring schemes of freshwater ecosystems; nevertheless, it requires the construction of comprehensive reference collections of DNA sequences that represent the existing biodiversity. Plecoptera are considered particularly good ecological indicators and one of the most endangered groups of insects, but very limited information on their DNA barcodes is available in public databases. Currently, less than 50% of the Iberian species are represented in BOLD.

New Information: The InBIO Barcoding Initiative Database: contribution to the knowledge on DNA barcodes of Iberian Plecoptera dataset contains records of 71 specimens of Plecoptera. All specimens have been morphologically identified to species level and belong to 29 species in total. This dataset contributes to the knowledge on the DNA barcodes and distribution of Plecoptera from the Iberian Peninsula and it is one of the IBI database public releases that makes available genetic and distribution data for a series of taxa.The species represented in this dataset correspond to an addition to public databases of 17 species and 21 BINs. Fifty-eight specimens were collected in Portugal and 18 in Spain during the period of 2004 to 2018. All specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources and their DNA barcodes are publicly available in the Barcode of Life Data System (BOLD) online database. The distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3897/BDJ.8.e55137DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7403161PMC
July 2020

Gastric Microbiome Diversities in Gastric Cancer Patients from Europe and Asia Mimic the Human Population Structure and Are Partly Driven by Microbiome Quantitative Trait Loci.

Microorganisms 2020 Aug 6;8(8). Epub 2020 Aug 6.

i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.

The human gastrointestinal tract harbors approximately 100 trillion microorganisms with different microbial compositions across geographic locations. In this work, we used RNASeq data from stomach samples of non-disease (164 individuals from European ancestry) and gastric cancer patients (137 from Europe and Asia) from public databases. Although these data were intended to characterize the human expression profiles, they allowed for a reliable inference of the microbiome composition, as confirmed from measures such as the genus coverage, richness and evenness. The microbiome diversity (weighted UniFrac distances) in gastric cancer mimics host diversity across the world, with European gastric microbiome profiles clustering together, distinct from Asian ones. Despite the confirmed loss of microbiome diversity from a healthy status to a cancer status, the structured profile was still recognized in the disease condition. In concordance with the parallel host-bacteria population structure, we found 16 human loci (non-synonymous variants) in the European-descendent cohorts that were significantly associated with specific genera abundance. These microbiome quantitative trait loci display heterogeneity between population groups, being mainly linked to the immune system or cellular features that may play a role in enabling microbe colonization and inflammation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/microorganisms8081196DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7463948PMC
August 2020

An RNA-seq Based Machine Learning Approach Identifies Latent Tuberculosis Patients With an Active Tuberculosis Profile.

Front Immunol 2020 14;11:1470. Epub 2020 Jul 14.

CINBIO, Universidade de Vigo, Immunology Group, Campus Universitario Lagoas-Marcosende, Vigo, Spain.

A better understanding of the response against Tuberculosis (TB) infection is required to accurately identify the individuals with an active or a latent TB infection (LTBI) and also those LTBI patients at higher risk of developing active TB. In this work, we have used the information obtained from studying the gene expression profile of active TB patients and their infected -LTBI- or uninfected -NoTBI- contacts, recruited in Spain and Mozambique, to build a class-prediction model that identifies individuals with a TB infection profile. Following this approach, we have identified several genes and metabolic pathways that provide important information of the immune mechanisms triggered against TB infection. As a novelty of our work, a combination of this class-prediction model and the direct measurement of different immunological parameters, was used to identify a subset of LTBI contacts (called whose transcriptional and immunological profiles are suggestive of infection with a higher probability of developing active TB. Validation of this novel approach to identifying LTBI individuals with the highest risk of active TB disease merits further longitudinal studies on larger cohorts in TB endemic areas.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fimmu.2020.01470DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372107PMC
April 2021

Tumors induce de novo steroid biosynthesis in T cells to evade immunity.

Nat Commun 2020 07 17;11(1):3588. Epub 2020 Jul 17.

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.

Tumors subvert immune cell function to evade immune responses, yet the complex mechanisms driving immune evasion remain poorly understood. Here we show that tumors induce de novo steroidogenesis in T lymphocytes to evade anti-tumor immunity. Using a transgenic steroidogenesis-reporter mouse line we identify and characterize de novo steroidogenic immune cells, defining the global gene expression identity of these steroid-producing immune cells and gene regulatory networks by using single-cell transcriptomics. Genetic ablation of T cell steroidogenesis restricts primary tumor growth and metastatic dissemination in mouse models. Steroidogenic T cells dysregulate anti-tumor immunity, and inhibition of the steroidogenesis pathway is sufficient to restore anti-tumor immunity. This study demonstrates T cell de novo steroidogenesis as a mechanism of anti-tumor immunosuppression and a potential druggable target.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-17339-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7368057PMC
July 2020

A user guide for the online exploration and visualization of PCAWG data.

Nat Commun 2020 07 7;11(1):3400. Epub 2020 Jul 7.

European Molecular Biology Laboratory, 69117, Heidelberg, Germany.

The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-16785-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340791PMC
July 2020

The InBIO Barcoding Initiative Database: DNA barcodes of Portuguese Diptera 01.

Biodivers Data J 2020 20;8:e49985. Epub 2020 Mar 20.

CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4485-661 Vairão, Vila do Conde, Portugal CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4485-661 Vairão Vila do Conde Portugal.

Background: The InBIO Barcoding Initiative (IBI) Diptera 01 dataset contains records of 203 specimens of Diptera. All specimens have been morphologically identified to species level, and belong to 154 species in total. The species represented in this dataset correspond to about 10% of continental Portugal dipteran species diversity. All specimens were collected north of the Tagus river in Portugal. Sampling took place from 2014 to 2018, and specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources.

New Information: This dataset contributes to the knowledge on the DNA barcodes and distribution of 154 species of Diptera from Portugal and is the first of the planned IBI database public releases, which will make available genetic and distribution data for a series of taxa. All specimens have their DNA barcodes made publicly available in the Barcode of Life Data System (BOLD) online database and the distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3897/BDJ.8.e49985DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101446PMC
March 2020

Genomic basis for RNA alterations in cancer.

Nature 2020 02 5;578(7793):129-136. Epub 2020 Feb 5.

BGI-Shenzhen, Shenzhen, China.

Transcript alterations often result from somatic changes in cancer genomes. Various forms of RNA alterations have been described in cancer, including overexpression, altered splicing and gene fusions; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-020-1970-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054216PMC
February 2020

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

Nature 2020 02 5;578(7793):102-111. Epub 2020 Feb 5.

Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.

The discovery of drivers of cancer has traditionally focused on protein-coding genes. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-020-1965-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054214PMC
February 2020

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations.

Nat Commun 2020 02 5;11(1):736. Epub 2020 Feb 5.

Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA.

The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-019-13885-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7002524PMC
February 2020

Current challenges and emerging opportunities of CAR-T cell therapies.

J Control Release 2020 03 30;319:246-261. Epub 2019 Dec 30.

CNC - Center for Neurosciences and Cell Biology, University of Coimbra, Faculty of Medicine (Polo 1), Rua Larga, 3004-504 Coimbra, Portugal; FFUC - Faculty of Pharmacy, University of Coimbra, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal. Electronic address:

Infusion of chimeric antigen receptor (CAR)-genetically modified T cells (CAR-T cells) have led to remarkable clinical responses and cancer remission in patients suffering from relapsed or refractory B-cell malignancies. This is a new form of adoptive T cell therapy (ACT), whereby the artificial CAR enables the redirection of T cells endogenous antitumor activity towards a predefined tumor-associated antigen, leading to the elimination of a specific tumor. The early success in blood cancers has prompted the US Food and Drug Administration (FDA) to approve the first CAR-T cell therapies for the treatment of CD19-positive leukemias and lymphomas in 2017. Despite the emergence of CAR-T cells as one of the latest breakthroughs of cancer immunotherapies, their wider application has been hampered by specific life-threatening toxicities, and a substantial lack of efficacy in the treatment of solid tumors, owing to the strong immunosuppressive tumor microenvironment and the paucity of reliable tumor-specific targets. Herein, besides providing an overview of the emerging CAR-technologies and current clinical applications, the major hurdles of CAR-T cell therapies will be discussed, namely treatment-related life-threatening toxicities and the obstacles posed by the immunosupressive tumor-microenvironment of solid tumors, as well as the next-generation strategies currently designed to simultaneously improve safety and efficacy of CAR-T cell therapies in vivo.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jconrel.2019.12.047DOI Listing
March 2020

Expression Atlas update: from tissues to single cells.

Nucleic Acids Res 2020 01;48(D1):D77-D83

European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK.

Expression Atlas is EMBL-EBI's resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of single cell RNA-Seq datasets in the public archives, we have now extended Expression Atlas with a new added-value service to display gene expression in single cells. Single Cell Expression Atlas was launched in 2018 and currently includes 123 single cell RNA-Seq studies from 12 species. The website can be searched by genes within or across species to reveal experiments, tissues and cell types where this gene is expressed or under which conditions it is a marker gene. Within each study, cells can be visualized using a pre-calculated t-SNE plot and can be coloured by different features or by cell clusters based on gene expression. Within each experiment, there are links to downloadable files, such as RNA quantification matrices, clustering results, reports on protocols and associated metadata, such as assigned cell types.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gkz947DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145605PMC
January 2020

A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters.

Cell 2019 09;178(6):1465-1477.e17

Computational and Systems Biology, Genome Institute of Singapore, Singapore 138672, Singapore; Cellular and Molecular Research, National Cancer Centre, Singapore 169610, Singapore. Electronic address:

Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. However, while a global change in transcription is recognized as a defining feature of cancer, the contribution of alternative promoters still remains largely unexplored. Here, we infer active promoters using RNA-seq data from 18,468 cancer and normal samples, demonstrating that alternative promoters are a major contributor to context-specific regulation of transcription. We find that promoters are deregulated across tissues, cancer types, and patients, affecting known cancer genes and novel candidates. For genes with independently regulated promoters, we demonstrate that promoter activity provides a more accurate predictor of patient survival than gene expression. Our study suggests that a dynamic landscape of active promoters shapes the cancer transcriptome, opening new diagnostic avenues and opportunities to further explore the interplay of regulatory mechanisms with transcriptional aberrations in cancer.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cell.2019.08.018DOI Listing
September 2019

ArrayExpress update - from bulk to single-cell expression data.

Nucleic Acids Res 2019 01;47(D1):D711-D715

European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

ArrayExpress (https://www.ebi.ac.uk/arrayexpress) is an archive of functional genomics data from a variety of technologies assaying functional modalities of a genome, such as gene expression or promoter occupancy. The number of experiments based on sequencing technologies, in particular RNA-seq experiments, has been increasing over the last few years and submissions of sequencing data have overtaken microarray experiments in the last 12 months. Additionally, there is a significant increase in experiments investigating single cells, rather than bulk samples, known as single-cell RNA-seq. To accommodate these trends, we have substantially changed our submission tool Annotare which, along with raw and processed data, collects all metadata necessary to interpret these experiments. Selected datasets are re-processed and loaded into our sister resource, the value-added Expression Atlas (and its component Single Cell Expression Atlas), which not only enables users to interpret the data easily but also serves as a test for data quality. With an increasing number of studies that combine different assay modalities (multi-omics experiments), a new more general archival resource the BioStudies Database has been developed, which will eventually supersede ArrayExpress. Data submissions will continue unchanged; all existing ArrayExpress data will be incorporated into BioStudies and the existing accession numbers and application programming interfaces will be maintained.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gky964DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323929PMC
January 2019

Inferences on specificity recognition at the Malus×domestica gametophytic self-incompatibility system.

Sci Rep 2018 01 29;8(1):1717. Epub 2018 Jan 29.

Instituto de Biologia Molecular e Celular (IBMC), Universidade do Porto, Rua Alfredo Allen 208, 4200-135, Porto, Portugal.

In Malus × domestica (Rosaceae) the product of each SFBB gene (the pollen component of the gametophytic self-incompatibility (GSI) system) of a S-haplotype (the combination of pistil and pollen genes that are linked) interacts with a sub-set of non-self S-RNases (the pistil component), but not with the self S-RNase. To understand how the Malus GSI system works, we identified 24 SFBB genes expressed in anthers, and determined their gene sequence in nine M. domestica cultivars. Expression of these SFBBs was not detected in the petal, sepal, filament, receptacle, style, stigma, ovary or young leaf. For all SFBBs (except SFBB15), identical sequences were obtained only in cultivars having the same S-RNase. Linkage with a particular S-RNase was further established using the progeny of three crosses. Such data is needed to understand how other genes not involved in GSI are affected by the S-locus region. To classify SFBBs specificity, the amino acids under positive selection obtained when performing intra-haplotypic analyses were used. Using this information and the previously identified S-RNase positively selected amino acid sites, inferences are made on the S-RNase amino acid properties (hydrophobicity, aromatic, aliphatic, polarity, and size), at these positions, that are critical features for GSI specificity determination.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-018-19820-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5788982PMC
January 2018

Expression Atlas: gene and protein expression across multiple studies and organisms.

Nucleic Acids Res 2018 01;46(D1):D246-D251

European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK.

Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gkx1158DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753389PMC
January 2018

Two independent modes of chromatin organization revealed by cohesin removal.

Nature 2017 11 27;551(7678):51-56. Epub 2017 Sep 27.

Developmental Biology Unit. European Molecular Biology Laboratory. 69117 Heidelberg, Germany.

Imaging and chromosome conformation capture studies have revealed several layers of chromosome organization, including segregation into megabase-sized active and inactive compartments, and partitioning into sub-megabase domains (TADs). It remains unclear, however, how these layers of organization form, interact with one another and influence genome function. Here we show that deletion of the cohesin-loading factor Nipbl in mouse liver leads to a marked reorganization of chromosomal folding. TADs and associated Hi-C peaks vanish globally, even in the absence of transcriptional changes. By contrast, compartmental segregation is preserved and even reinforced. Strikingly, the disappearance of TADs unmasks a finer compartment structure that accurately reflects the underlying epigenetic landscape. These observations demonstrate that the three-dimensional organization of the genome results from the interplay of two independent mechanisms: cohesin-independent segregation of the genome into fine-scale compartments, defined by chromatin state; and cohesin-dependent formation of TADs, possibly by loop extrusion, which helps to guide distant enhancers to their target genes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nature24281DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5687303PMC
November 2017

The cancer stem cell phenotype as a determinant factor of the heterotypic nature of breast tumors.

Crit Rev Oncol Hematol 2017 May 16;113:111-121. Epub 2017 Mar 16.

CNC - Center for Neurosciences and Cell Biology, University of Coimbra, Faculty of Medicine (Polo 1), Rua Larga, 3004-504 Coimbra, Portugal; FFUC - Faculty of Pharmacy, University of Coimbra, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal. Electronic address:

Gathering evidence supports the existence of a population of cells with stem-like characteristics, named cancer stem cells (CSC), which is involved not only in tumor recurrence but also in tumorigenicity, metastization and drug resistance. Several markers have been used to identify putative CSC sub-populations in different cancers. Notwithstanding, it has been acknowledged that breast CSC may originate from non-stem cancer cells (non-SCC), interconverting through an epithelial-to-mesenchymal transition-mediated process, and presenting several deregulated canonical and developmental signaling pathways. These support the heterogeneity that, directly or indirectly, influences fundamental biological features supporting breast tumor development. Accordingly, CSC have increasingly become highly relevant cellular targets. In this review, we will address the stemness concept in cancer, setting the perspective on CSC and their origin, by exploring their relation and regulation within the tumor microenvironment, in the context of emerging therapeutic targets. Within this framework, we will discuss nucleolin, a protein that has been associated with angiogenesis and, more recently, with the stemness phenotype, becoming a common denominator between CSC and non-SCC for multicellular targeting.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.critrevonc.2017.03.016DOI Listing
May 2017

The RNASeq-er API-a gateway to systematically updated analysis of public RNA-seq data.

Bioinformatics 2017 Jul;33(14):2218-2220

Functional Genomics Group, European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK.

Motivation: The exponential growth of publicly available RNA-sequencing (RNA-Seq) data poses an increasing challenge to researchers wishing to discover, analyse and store such data, particularly those based in institutions with limited computational resources. EMBL-EBI is in an ideal position to address these challenges and to allow the scientific community easy access to not just raw, but also processed RNA-Seq data. We present a Web service to access the results of a systematically and continually updated standardized alignment as well as gene and exon expression quantification of all public bulk (and in the near future also single-cell) RNA-Seq runs in 264 species in European Nucleotide Archive, using Representational State Transfer.

Results: The RNASeq-er API (Application Programming Interface) enables ontology-powered search for and retrieval of CRAM, bigwig and bedGraph files, gene and exon expression quantification matrices (Fragments Per Kilobase Of Exon Per Million Fragments Mapped, Transcripts Per Million, raw counts) as well as sample attributes annotated with ontology terms. To date over 270 00 RNA-Seq runs in nearly 10 000 studies (1PB of raw FASTQ data) in 264 species in ENA have been processed and made available via the API.

Availability And Implementation: The RNASeq-er API can be accessed at http://www.ebi.ac.uk/fg/rnaseq/api . The commands used to analyse the data are available in supplementary materials and at https://github.com/nunofonseca/irap/wiki/iRAP-single-library .

Contact: rnaseq@ebi.ac.uk ; rpetry@ebi.ac.uk.

Supplementary Information: Supplementary data are available at Bioinformatics online.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/bioinformatics/btx143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870697PMC
July 2017

Inoculated Cell Density as a Determinant Factor of the Growth Dynamics and Metastatic Efficiency of a Breast Cancer Murine Model.

PLoS One 2016 7;11(11):e0165817. Epub 2016 Nov 7.

CNC-Center for Neurosciences and Cell Biology, University of Coimbra, Coimbra, Portugal.

4T1 metastatic breast cancer model have been widely used to study stage IV human breast cancer. However, the frequent inoculation of a large number of cells, gives rise to fast growing tumors, as well as to a surprisingly low metastatic take rate. The present work aimed at establishing the conditions enabling high metastatic take rate of the triple-negative murine 4T1 syngeneic breast cancer model. An 87% 4T1 tumor incidence was observed when as few as 500 cancer cells were implanted. 4T1 cancer cells colonized primarily the lungs with 100% efficiency, and distant lesions were also commonly identified in the mesentery and pancreas. The drastic reduction of the number of inoculated cells resulted in increased tumor doubling times and decreased specific growth rates, following a Gompertzian tumor expansion. The established conditions for the 4T1 mouse model were further validated in a therapeutic study with peguilated liposomal doxorubicin, in clinical used in the setting of metastatic breast cancer. Inoculated cell density was proven to be a key methodological aspect towards the reproducible development of macrometastases in the 4T1 mouse model and a more reliable pre-clinical assessment of antimetastatic therapies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165817PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5098815PMC
June 2017

Gramene 2016: comparative plant genomics and pathway resources.

Nucleic Acids Res 2016 Jan 8;44(D1):D1133-40. Epub 2015 Nov 8.

EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.

Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to ∼ 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gkv1179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702844PMC
January 2016

Expression Atlas update--an integrated database of gene and protein expression in humans, animals and plants.

Nucleic Acids Res 2016 Jan 19;44(D1):D746-52. Epub 2015 Oct 19.

European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK.

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons-estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: 'enrichment' in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gkv1045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702781PMC
January 2016

Predicting malignancy from mammography findings and image-guided core biopsies.

Int J Data Min Bioinform 2015 ;11(3):257-76

The main goal of this work is to produce machine learning models that predict the outcome of a mammography from a reduced set of annotated mammography findings. In the study we used a dataset consisting of 348 consecutive breast masses that underwent image guided core biopsy performed between October 2005 and December 2007 on 328 female subjects. We applied various algorithms with parameter variation to learn from the data. The tasks were to predict mass density and to predict malignancy. The best classifier that predicts mass density is based on a support vector machine and has accuracy of 81.3%. The expert correctly annotated 70% of the mass densities. The best classifier that predicts malignancy is also based on a support vector machine and has accuracy of 85.6%, with a positive predictive value of 85%. One important contribution of this work is that our model can predict malignancy in the absence of the mass density attribute, since we can fill up this attribute using our mass density predictor.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4764253PMC
http://dx.doi.org/10.1504/ijdmb.2015.067319DOI Listing
November 2015

Nucleolin overexpression in breast cancer cell sub-populations with different stem-like phenotype enables targeted intracellular delivery of synergistic drug combination.

Biomaterials 2015 Nov 6;69:76-88. Epub 2015 Aug 6.

CNC - Center for Neurosciences and Cell Biology, University of Coimbra, Faculty of Medicine (Polo I), Rua Larga, Coimbra 3004-504, Portugal; FFUC - Faculty of Pharmacy, University of Coimbra, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, Coimbra 3000-548, Portugal. Electronic address:

Breast cancer stem cells (CSC) are thought responsible for tumor growth and relapse, metastization and active evasion to standard chemotherapy. The recognition that CSC may originate from non-stem cancer cells (non-SCC) through plastic epithelial-to-mesenchymal transition turned these into relevant cell targets. Of crucial importance for successful therapeutic intervention is the identification of surface receptors overexpressed in both CSC and non-SCC. Cell surface nucleolin has been described as overexpressed in cancer cells as well as a tumor angiogenic marker. Herein we have addressed the questions on whether nucleolin was a common receptor among breast CSC and non-SCC and whether it could be exploited for targeting purposes. Liposomes functionalized with the nucleolin-binding F3 peptide, targeted simultaneously, nucleolin-overexpressing putative breast CSC and non-SCC, which was paralleled by OCT4 and NANOG mRNA levels in cells from triple negative breast cancer (TNBC) origin. In murine embryonic stem cells, both nucleolin mRNA levels and F3 peptide-targeted liposomes cellular association were dependent on the stemness status. An in vivo tumorigenic assay suggested that surface nucleolin overexpression per se, could be associated with the identification of highly tumorigenic TNBC cells. This proposed link between nucleolin expression and the stem-like phenotype in TNBC, enabled 100% cell death mediated by F3 peptide-targeted synergistic drug combination, suggesting the potential to abrogate the plasticity and adaptability associated with CSC and non-SCC. Ultimately, nucleolin-specific therapeutic tools capable of simultaneous debulk multiple cellular compartments of the tumor microenvironment may pave the way towards a specific treatment for TNBC patient care.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.biomaterials.2015.08.007DOI Listing
November 2015