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  1. Article ; Online: TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype and is associated with increased survival in cancer patients with high tumor macrophage content.

    Gunalp, Sinem / Helvaci, Derya Goksu / Oner, Aysenur / Bursalı, Ahmet / Conforte, Alessandra / Güner, Hüseyin / Karakülah, Gökhan / Szegezdi, Eva / Sag, Duygu

    Frontiers in immunology

    2023  Volume 14, Page(s) 1209249

    Abstract: Background: TNF-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily that can either induce cell death or activate survival pathways after binding to death receptors (DRs) DR4 or DR5. TRAIL is investigated as a therapeutic agent ... ...

    Abstract Background: TNF-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily that can either induce cell death or activate survival pathways after binding to death receptors (DRs) DR4 or DR5. TRAIL is investigated as a therapeutic agent in clinical trials due to its selective toxicity to transformed cells. Macrophages can be polarized into pro-inflammatory/tumor-fighting M1 macrophages or anti-inflammatory/tumor-supportive M2 macrophages and an imbalance between M1 and M2 macrophages can promote diseases. Therefore, identifying modulators that regulate macrophage polarization is important to design effective macrophage-targeted immunotherapies. The impact of TRAIL on macrophage polarization is not known.
    Methods: Primary human monocyte-derived macrophages were pre-treated with either TRAIL or with DR4 or DR5-specific ligands and then polarized into M1, M2a, or M2c phenotypes
    Results: TRAIL increased the expression of M1 markers at both mRNA and protein levels while decreasing the expression of M2 markers at the mRNA level in human macrophages. TRAIL also shifted M2 macrophages towards an M1 phenotype. Our data showed that both DR4 and DR5 death receptors play a role in macrophage polarization. Furthermore, TRAIL enhanced the cytotoxicity of macrophages against the AML cancer cells
    Conclusions: TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype via both DR4 and DR5. Our study defines TRAIL as a new regulator of macrophage polarization and suggests that targeting DRs can enhance the anti-tumorigenic response of macrophages in the tumor microenvironment by increasing M1 polarization.
    MeSH term(s) Humans ; TNF-Related Apoptosis-Inducing Ligand/metabolism ; Macrophages/metabolism ; Phenotype ; RNA, Messenger/metabolism ; Receptors, Death Domain/metabolism ; Leukemia, Myeloid, Acute/metabolism ; Tumor Microenvironment
    Chemical Substances TNF-Related Apoptosis-Inducing Ligand ; RNA, Messenger ; Receptors, Death Domain
    Language English
    Publishing date 2023-09-21
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2606827-8
    ISSN 1664-3224 ; 1664-3224
    ISSN (online) 1664-3224
    ISSN 1664-3224
    DOI 10.3389/fimmu.2023.1209249
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Modeling Basins of Attraction for Breast Cancer Using Hopfield Networks.

    Conforte, Alessandra Jordano / Alves, Leon / Coelho, Flávio Codeço / Carels, Nicolas / da Silva, Fabrício Alves Barbosa

    Frontiers in genetics

    2020  Volume 11, Page(s) 314

    Abstract: Cancer is a genetic disease for which traditional treatments cause harmful side effects. After two decades of genomics technological breakthroughs, personalized medicine is being used to improve treatment outcomes and mitigate side effects. In ... ...

    Abstract Cancer is a genetic disease for which traditional treatments cause harmful side effects. After two decades of genomics technological breakthroughs, personalized medicine is being used to improve treatment outcomes and mitigate side effects. In mathematical modeling, it has been proposed that cancer matches an attractor in Waddington's epigenetic landscape. The use of Hopfield networks is an attractive modeling approach because it requires neither previous biological knowledge about protein-protein interactions nor kinetic parameters. In this report, Hopfield network modeling was used to analyze bulk RNA-Seq data of paired breast tumor and control samples from 70 patients. We characterized the control and tumor attractors with respect to their size and potential energy and correlated the Euclidean distances between the tumor samples and the control attractor with their corresponding clinical data. In addition, we developed a protocol that outlines the key genes involved in tumor state stability. We found that the tumor basin of attraction is larger than that of the control and that tumor samples are associated with a more substantial negative energy than control samples, which is in agreement with previous reports. Moreover, we found a negative correlation between the Euclidean distances from tumor samples to the control attractor and patient overall survival. The ascending order of each node's density in the weight matrix and the descending order of the number of patients that have the target active only in the tumor sample were the parameters that withdrew more tumor samples from the tumor basin of attraction with fewer gene inhibitions. The combinations of therapeutic targets were specific to each patient. We performed an initial validation through simulation of trastuzumab treatment effects in HER2+ breast cancer samples. For that, we built an energy landscape composed of single-cell and bulk RNA-Seq data from trastuzumab-treated and non-treated HER2+ samples. The trajectory from the non-treated bulk sample toward the treated bulk sample was inferred through the perturbation of differentially expressed genes between these samples. Among them, we characterized key genes involved in the trastuzumab response according to the literature.
    Language English
    Publishing date 2020-04-07
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2020.00314
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Cell-cell interactome of the hematopoietic niche and its changes in acute myeloid leukemia.

    Ennis, Sarah / Conforte, Alessandra / O'Reilly, Eimear / Takanlu, Javid Sabour / Cichocka, Tatiana / Dhami, Sukhraj Pal / Nicholson, Pamela / Krebs, Philippe / Ó Broin, Pilib / Szegezdi, Eva

    iScience

    2023  Volume 26, Issue 6, Page(s) 106943

    Abstract: The bone marrow (BM) is a complex microenvironment, coordinating the production of billions of blood cells every day. Despite its essential role and its relevance to hematopoietic diseases, this environment remains poorly characterized. Here we present a ...

    Abstract The bone marrow (BM) is a complex microenvironment, coordinating the production of billions of blood cells every day. Despite its essential role and its relevance to hematopoietic diseases, this environment remains poorly characterized. Here we present a high-resolution characterization of the niche in health and acute myeloid leukemia (AML) by establishing a single-cell gene expression database of 339,381 BM cells. We found significant changes in cell type proportions and gene expression in AML, indicating that the entire niche is disrupted. We then predicted interactions between hematopoietic stem and progenitor cells (HSPCs) and other BM cell types, revealing a remarkable expansion of predicted interactions in AML that promote HSPC-cell adhesion, immunosuppression, and cytokine signaling. In particular, predicted interactions involving transforming growth factor β1 (TGFB1) become widespread, and we show that this can drive AML cell quiescence
    Language English
    Publishing date 2023-05-23
    Publishing country United States
    Document type Journal Article
    ISSN 2589-0042
    ISSN (online) 2589-0042
    DOI 10.1016/j.isci.2023.106943
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Data-Driven Modeling of Breast Cancer Tumors Using Boolean Networks.

    Sgariglia, Domenico / Conforte, Alessandra Jordano / Pedreira, Carlos Eduardo / Vidal de Carvalho, Luis Alfredo / Carneiro, Flavia Raquel Gonçalves / Carels, Nicolas / Silva, Fabricio Alves Barbosa da

    Frontiers in big data

    2021  Volume 4, Page(s) 656395

    Abstract: Cancer is a genomic disease involving various intertwined pathways with complex cross-communication links. Conceptually, this complex interconnected system forms a network, which allows one to model the dynamic behavior of the elements that characterize ... ...

    Abstract Cancer is a genomic disease involving various intertwined pathways with complex cross-communication links. Conceptually, this complex interconnected system forms a network, which allows one to model the dynamic behavior of the elements that characterize it to describe the entire system's development in its various evolutionary stages of carcinogenesis. Knowing the activation or inhibition status of the genes that make up the network during its temporal evolution is necessary for the rational intervention on the critical factors for controlling the system's dynamic evolution. In this report, we proposed a methodology for building data-driven boolean networks that model breast cancer tumors. We defined the network components and topology based on gene expression data from RNA-seq of breast cancer cell lines. We used a Boolean logic formalism to describe the network dynamics. The combination of single-cell RNA-seq and interactome data enabled us to study the dynamics of malignant subnetworks of up-regulated genes. First, we used the same Boolean function construction scheme for each network node, based on canalyzing functions. Using single-cell breast cancer datasets from The Cancer Genome Atlas, we applied a binarization algorithm. The binarized version of scRNA-seq data allowed identifying attractors specific to patients and critical genes related to each breast cancer subtype. The model proposed in this report may serve as a basis for a methodology to detect critical genes involved in malignant attractor stability, whose inhibition could have potential applications in cancer theranostics.
    Language English
    Publishing date 2021-10-20
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2624-909X
    ISSN (online) 2624-909X
    DOI 10.3389/fdata.2021.656395
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Galaxy and MEAN Stack to Create a User-Friendly Workflow for the Rational Optimization of Cancer Chemotherapy.

    Pires, Jorge Guerra / da Silva, Gilberto Ferreira / Weyssow, Thomas / Conforte, Alessandra Jordano / Pagnoncelli, Dante / da Silva, Fabricio Alves Barbosa / Carels, Nicolas

    Frontiers in genetics

    2021  Volume 12, Page(s) 624259

    Abstract: One aspect of personalized medicine is aiming at identifying specific targets for therapy considering the gene expression profile of each patient individually. The real-world implementation of this approach is better achieved by user-friendly ... ...

    Abstract One aspect of personalized medicine is aiming at identifying specific targets for therapy considering the gene expression profile of each patient individually. The real-world implementation of this approach is better achieved by user-friendly bioinformatics systems for healthcare professionals. In this report, we present an online platform that endows users with an interface designed using MEAN stack supported by a Galaxy pipeline. This pipeline targets connection
    Language English
    Publishing date 2021-02-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2021.624259
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Signaling Complexity Measured by Shannon Entropy and Its Application in Personalized Medicine.

    Conforte, Alessandra J / Tuszynski, Jack Adam / da Silva, Fabricio Alves Barbosa / Carels, Nicolas

    Frontiers in genetics

    2019  Volume 10, Page(s) 930

    Abstract: Traditional approaches to cancer therapy seek common molecular targets in tumors from different patients. However, molecular profiles differ between patients, and most tumors exhibit inherent heterogeneity. Hence, imprecise targeting commonly results in ... ...

    Abstract Traditional approaches to cancer therapy seek common molecular targets in tumors from different patients. However, molecular profiles differ between patients, and most tumors exhibit inherent heterogeneity. Hence, imprecise targeting commonly results in side effects, reduced efficacy, and drug resistance. By contrast, personalized medicine aims to establish a molecular diagnosis specific to each patient, which is currently feasible due to the progress achieved with high-throughput technologies. In this report, we explored data from human RNA-seq and protein-protein interaction (PPI) networks using bioinformatics to investigate the relationship between tumor entropy and aggressiveness. To compare PPI subnetworks of different sizes, we calculated the Shannon entropy associated with vertex connections of differentially expressed genes comparing tumor samples with their paired control tissues. We found that the inhibition of up-regulated connectivity hubs led to a higher reduction of subnetwork entropy compared to that obtained with the inhibition of targets selected at random. Furthermore, these hubs were described to be participating in tumor processes. We also found a significant negative correlation between subnetwork entropies of tumors and the respective 5-year survival rates of the corresponding cancer types. This correlation was also observed considering patients with lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) based on the clinical data from The Cancer Genome Atlas database (TCGA). Thus, network entropy increases in parallel with tumor aggressiveness but does not correlate with PPI subnetwork size. This correlation is consistent with previous reports and allowed us to assess the number of hubs to be inhibited for therapy to be effective, in the context of precision medicine, by reference to the 100% patient survival rate 5 years after diagnosis. Large standard deviations of subnetwork entropies and variations in target numbers per patient among tumor types characterize tumor heterogeneity.
    Language English
    Publishing date 2019-10-21
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2019.00930
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Isolation and characterization of a promoter responsive to salt, osmotic and dehydration stresses in soybean.

    Conforte, Alessandra Jordano / Guimarães-Dias, Fábia / Neves-Borges, Anna Cristina / Bencke-Malato, Marta / Felix-Whipps, Durvalina / Alves-Ferreira, Márcio

    Genetics and molecular biology

    2017  Volume 40, Issue 1 suppl 1, Page(s) 226–237

    Abstract: Drought stress is the main limiting factor of soybean yield. Currently, genetic engineering has been one important tool in the development of drought-tolerant cultivars. A widely used strategy is the fusion of genes that confer tolerance under the ... ...

    Abstract Drought stress is the main limiting factor of soybean yield. Currently, genetic engineering has been one important tool in the development of drought-tolerant cultivars. A widely used strategy is the fusion of genes that confer tolerance under the control of the CaMV35S constitutive promoter; however, stress-responsive promoters would constitute the best alternative to the generation of drought-tolerant crops. We characterized the promoter of α-galactosidase soybean (GlymaGAL) gene that was previously identified as highly up-regulated by drought stress. The β-glucuronidase (GUS) activity of Arabidopsis transgenic plants bearing 1000- and 2000-bp fragments of the GlymaGAL promoter fused to the uidA gene was evaluated under air-dried, polyethylene glycol (PEG) and salt stress treatments. After 24 h of air-dried and PEG treatments, the pGAL-2kb led to an increase in GUS expression in leaf and root samples when compared to the control samples. These results were corroborated by qPCR expression analysis of the uidA gene. The pGAL-1kb showed no difference in GUS activity between control and treated samples. The pGAL-2kb promoter was evaluated in transgenic soybean roots, leading to an increase in EGFP expression under air-dried treatment. Our data indicates that pGAL-2kb could be a useful tool in developing drought-tolerant cultivars by driving gene expression.
    Language English
    Publishing date 2017-03-27
    Publishing country Brazil
    Document type Journal Article
    ZDB-ID 1445712-x
    ISSN 1678-4685 ; 1415-4757
    ISSN (online) 1678-4685
    ISSN 1415-4757
    DOI 10.1590/1678-4685-GMB-2016-0052
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Conference proceedings ; Online: FORMAS DE APRENDIZAGEM E PRODUÇÃO DO CONHECIMENTO EM UM ARRANJO PRODUTIVO LOCAL DA SOJA NO CERRADO

    Conforte, Alessandra Cristina / Le Boourlegat, Cleonice Alexandre

    2006  

    Keywords Crop Production/Industries ; Production Economics
    Language English
    Publishing country us
    Document type Conference proceedings ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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