Novel 2-amino-isoflavones exhibit aryl hydrocarbon receptor agonist or antagonist activity in a species/cell-specific context

The aryl hydrocarbon receptor (AhR) mediates the induction of a variety of xenobiotic metabolism genes. Activation of the AhR occurs through binding to a group of structurally diverse compounds, most notably dioxins, which are exogenous ligands. Isoflavones are part of a family which include some well characterised endogenous AhR ligands. This paper analysed a novel family of these compounds, based on the structure of 2-amino-isoflavone. Initially two luciferase-based cell models, mouse H1L6.1c2 and human HG2L6.1c3, were used to identify whether the compounds had AhR agonistic and/or antagonistic properties. This analysis showed that some of the compounds were weak agonists in mouse and antagonists in human. Further analysis of two of the compounds, Chr-13 and Chr-19, was conducted using quantitative real-time PCR in rat H4IIE and human MCF-7 cells. The results indicated that Chr-13 was an agonist in rat but an antagonist in human cells. Chr-19 was shown to be an agonist in rat but more interestingly, a partial agonist in human. Luciferase induction results not only revealed that subtle differences in the structure of the compound could produce species-specific differences in response but also dictated the ability of the compound to be an AhR agonist or antagonist. Substituted 2-amino-isoflavones represent a novel group of AhR ligands that must differentially interact with the AhR ligand binding domain to produce their species-specific agonist or antagonist activity and future ligand binding analysis and docking studies with these compounds may provide insights into the differential mechanisms of action of structurally similar compounds

The Extracellular Matrix: An Accomplice in Gastric Cancer Development and Progression

The extracellular matrix (ECM) is a dynamic and highly organized tissue structure, providing support and maintaining normal epithelial architecture. In the last decade, increasing evidence has emerged demonstrating that alterations in ECM composition and assembly strongly affect cellular function and behavior. Even though the detailed mechanisms underlying cell-ECM crosstalk are yet to unravel, it is well established that ECM deregulation accompanies the development of many pathological conditions, such as gastric cancer. Notably, gastric cancer remains a worldwide concern, representing the third most frequent cause of cancer-associated deaths. Despite increased surveillance protocols, patients are usually diagnosed at advanced disease stages, urging the identification of novel diagnostic biomarkers and efficient therapeutic strategies. In this review, we provide a comprehensive overview regarding expression patterns of ECM components and cognate receptors described in normal gastric epithelium, pre-malignant lesions, and gastric carcinomas. Important insights are also discussed for the use of ECM-associated molecules as predictive biomarkers of the disease or as potential targets in gastric cancer.This work was supported by FEDER funds through the Operational Programme for Competitiveness Factors (COMPETE 2020), Programa Operacional de Competitividade e Internacionalização (POCI), Programa Cells 2020, 9, 394 14 of 23 Operacional Regional do Norte (Norte 2020) and by National Funds through the Portuguese Foundation for Science and Technology (FCT), under the projects PTDC/MED-GEN/30356/2017, PTDC/BIM-ONC/0171/2012, PTDC/BIM-ONC/0281/2014, NORTE-01–0145-FEDER-000029, and doctoral grants SFRH/BD/114687/2016-AMM, SFRH/BD/143533/2019-JP, and SFRH/BD/108009/2015-SM. We acknowledge the American Association of Patients with Hereditary Gastric Cancer “No Stomach for Cancer” for funding Seruca and Figueiredo’s research

A machine learning approach for single cell interphase cell cycle staging

The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in nuclear morphology are also hallmarks of many diseases including cancer. Regrettably, automated reliable tools for cell cycle staging at single cell level using in situ images are still limited. It is therefore urgent to establish accurate strategies combining bioimaging with high-content image analysis for a bona fide classification. In this study we developed a supervised machine learning method for interphase cell cycle staging of individual adherent cells using in situ fluorescence images of nuclei stained with DAPI. A Support Vector Machine (SVM) classifier operated over normalized nuclear features using more than 3500 DAPI stained nuclei. Molecular ground truth labels were obtained by automatic image processing using fluorescent ubiquitination-based cell cycle indicator (Fucci) technology. An average F1-Score of 87.7% was achieved with this framework. Furthermore, the method was validated on distinct cell types reaching recall values higher than 89%. Our method is a robust approach to identify cells in G1 or S/G2 at the individual level, with implications in research and clinical applications.This work was supported by FEDER funds through the Operational Programme for Competitiveness Factors (COMPETE 2020), Programa Operacional de Competitividade e Internacionalização (POCI), Programa Opera-cional Regional do Norte (Norte 2020) and by National Funds through the Portuguese Foundation for Science and Technology (FCT), under the projects PTDC/BBB-IMG/0283/2014, PTDC/BTM-SAL/30383/2017, LARSyS-UIDB/50009/2020, LARSyS-UID/EEA/50009/2019, NORTE-01-0145-FEDER-000029 and doctoral grant SFRH/ BD/114687/2016. The authors acknowledge the American Association of Patients with Hereditary Gastric Cancer “No Stomach for Cancer” for funding Seruca’s research and the support of the i3S Scientific Platform Advanced Light Microscopy, member of the PPBI (PPBI-POCI-01-0145-FEDER-022122)

Proteomics Reveals mRNA Regulation and the Action of Annexins in Thyroid Cancer

Differentiated thyroid cancer is the most common malignancy of the endocrine system. Although most thyroid nodules are benign, given the high incidence of thyroid nodules in the population, it is important to understand the differences between benign and malignant thyroid cancer and the molecular alterations associated with malignancy to improve detection and signal potential diagnostic, prognostic, and therapeutic targets. Proteomics analysis of benign and malignant human thyroid tissue largely revealed changes indicating modifications in RNA regulation, a common cancer characteristic. In addition, changes in the immune system and cell membrane/endocytic processes were also suggested to be involved. Annexin A1 was considered a potential malignancy biomarker and, similarly to other annexins, it was found to increase in the malignant group. Furthermore, a bioinformatics approach points to the transcription factor Sp1 as being potentially involved in most of the alterations seen in the malignant thyroid nodules

Geometric compensation applied to image analysis of cell populations with morphological variability: A new role for a classical concept

Immunofluorescence is the gold standard technique to determine the level and spatial distribution of fluorescent-tagged molecules. However, quantitative analysis of fluorescence microscopy images faces crucial challenges such as morphologic variability within cells. In this work, we developed an analytical strategy to deal with cell shape and size variability that is based on an elastic geometric alignment algorithm. Firstly, synthetic images mimicking cell populations with morphological variability were used to test and optimize the algorithm, under controlled conditions. We have computed expression profiles specifically assessing cell-cell interactions (IN profiles) and profiles focusing on the distribution of a marker throughout the intracellular space of single cells (RD profiles). To experimentally validate our analytical pipeline, we have used real images of cell cultures stained for E-cadherin, tubulin and a mitochondria dye, selected as prototypes of membrane, cytoplasmic and organelle-specific markers. The results demonstrated that our algorithm is able to generate a detailed quantitative report and a faithful representation of a large panel of molecules, distributed in distinct cellular compartments, independently of cell's morphological features. This is a simple end-user method that can be widely explored in research and diagnostic labs to unravel protein regulation mechanisms or identify protein expression patterns associated with disease.This work was supported by FEDER funds through the Operational Programme for Competitiveness Factors (COMPETE) and National Funds through the Portuguese Foundation for Science and Technology (FCT), under the projects PTDC/BIM-ONC/0171/2012, PTDC/BIM-ONC/0281/2014, PTDC/BBB-IMG/0283/2014; Post-Doctoral grants SFRH/BPD/87705/2012-JF and SFRH/BPD/104208/2014-BS; and Doctoral grant SFRH/ BD/108009/2015-SM. We acknowledge the Programa IFCT (FCT Investigator) for funding JP research. We also thank to the American Association of Patients with Hereditary Gastric Cancer “No Stomach for Cancer” for funding the projects “Today’s present, tomorrow’s future on the study of germline E-cadherin missense mutations” and “Today’s Present, Tomorrow’s Future on the Study of Germline E-Cadherin Missense Mutations: A Step Forward on Providing Informed Genetic Counseling to Everyone”

Obesity and brain cancer: proteomic analyzes of the influence of the adipocyte secretome on glioma Gl261 cells

Glioma is the most frequent form of malignant brain tumor in the adults and childhood. There is a global tendency toward a higher incidence of gliomas in highly developed and industrialized countries. Simultaneously obesity is reaching epidemic proportions in such developed countries. It has been highly accepted that obesity may play an important role in the biology of several types of cancer. We have developed an in vitro method for the understanding of the influence of obesity on glioma mouse cells (Gl261).info:eu-repo/semantics/publishedVersio

H-Ferritin Is Essential for Macrophages' Capacity to Store or Detoxify Exogenously Added Iron

Macrophages are central cells both in the immune response and in iron homeostasis. Iron is both essential and potentially toxic. Therefore, iron acquisition, transport, storage, and release are tightly regulated, by several important proteins. Cytosolic ferritin is an iron storage protein composed of 24 subunits of either the L- or the H-type chains. H-ferritin differs from L-ferritin in the capacity to oxidize Fe2+ to Fe3+. In this work, we investigated the role played by H-ferritin in the macrophages' ability to respond to immune stimuli and to deal with exogenously added iron. We used mice with a conditional deletion of the H-ferritin gene in the myeloid lineage to obtain bone marrow-derived macrophages. These macrophages had normal viability and gene expression under basal culture conditions. However, when treated with interferon-gamma and lipopolysaccharide they had a lower activation of Nitric Oxide Synthase 2. Furthermore, H-ferritin-deficient macrophages had a higher sensitivity to iron-induced toxicity. This sensitivity was associated with a lower intracellular iron accumulation but a higher production of reactive oxygen species. These data indicate that H-ferritin modulates macrophage response to immune stimuli and that it plays an essential role in protection against iron-induced oxidative stress and cell death.Tis work was fnanced by FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE2020 - Operacional Programme for Competitiveness and Internationalization (POCI), Portugal 2020, and by Portuguese funds through FCT - Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project PTDC/IMI-MIC/1683/2014 (POCI-01-0145-FEDER-016590). PFO and MGA acknowledge FCT for the Investigador FCT 2015. We thank the valuable collaboration of the following i3S Scientifc Platforms: Cell Culture and Genotyping Core Facility (CCGen), [Histology and Electron Microscopy Service (HEMS), and BioSciences Screening], member of the PPBI (PPBI-POCI-01-0145-FEDER-022122)], Animal Facility, and Flow Cytometry Unit (TraCy). We acknowledge Lukas Kuhn (Swiss Institute for Experimental Cancer Research, Lausanne, Switzerland) for kindly providing the frst breeding pairs of Fth1−/− mice. Te authors also acknowledge Marisa Castro, from Departamento de Biologia Molecular from ICBAS, Clara Bento, from i3S, and Edgar Pinto from LAQV – REQUIMTE for technical assistance at diferent stages of the project