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      Proteomic Analysis of Low-Grade, Early-Stage Endometrial Carcinoma Reveals New Dysregulated Pathways Associated with Cell Death and Cell Signaling

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          Low-grade, early-stage endometrial cancer (EC) is the most frequent malignant tumor of the uterine corpus. Our study aimed to assess dysregulated pathways in this specific subset of EC through proteomic analysis. We describe and validate the dysregulation of the SLIT/ROBO signaling pathway, as well as cellular death processes such as necroptosis and ferroptosis. We identify several immune-related pathways, with a dominance of innate immune response associated pathways. Our findings reveal the singular biology of low-grade, early-stage ECs and could guide future research in the field.

          Abstract

          Low-grade, early-stage endometrial carcinoma (EC) is the most frequent malignant tumor of the uterine corpus. However, the molecular alterations that underlie these tumors are far from being fully understood. The purpose of this study is to describe dysregulated molecular pathways from EC patients. Sixteen samples of tumor tissue and paired healthy controls were collected and both were subjected to mass spectrometry (MS)/MS proteomic analysis. Gene ontology and pathway analysis was performed to discover dysregulated pathways and/or proteins using different databases and bioinformatic tools. Dysregulated pathways were cross-validated in an independent external cohort. Cell signaling, immune response, and cell death-associated pathways were robustly identified. The SLIT/ROBO signaling pathway demonstrated dysregulation at the proteomic and transcriptomic level. Necroptosis and ferroptosis were cell death-associated processes aberrantly regulated, in addition to apoptosis. Immune response-associated pathways showed a dominance of innate immune responses. Tumor immune infiltrates measured by immunofluorescence demonstrated diverse lymphoid and myeloid populations. Our results suggest a role of SLIT/ROBO, necroptosis, and ferroptosis, as well as a prominent role of innate immune response in low-grade, early-stage EC. These results could guide future research in this group of tumors.

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Proteomics. Tissue-based map of the human proteome.

            Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. Copyright © 2015, American Association for the Advancement of Science.
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              The PRIDE database and related tools and resources in 2019: improving support for quantification data

              Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                14 February 2021
                February 2021
                : 13
                : 4
                : 794
                Affiliations
                [1 ]Department of Pathology, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain; aljaneiro@ 123456salud.madrid.org (Á.L.-J.); ignacio.ruz@ 123456salud.madrid.org (I.R.-C.); alberto.berjon@ 123456salud.madrid.org (A.B.); laura.yebenes@ 123456salud.madrid.org (L.Y.)
                [2 ]Department of Medical Oncology, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain; jorge.ramon@ 123456hospitalreyjuancarlos.es (J.L.R.-P.); andres.redondo@ 123456salud.madrid.org (A.R.)
                [3 ]Proteomics Facility, Centro de Investigaciones Biológicas (CIB-CSIC), 28039 Madrid, Spain; vrios@ 123456cib.csic.es
                [4 ]Department of Pathology, Clínica Universidad de Navarra, University of Navarra, 31008 Pamplona, Spain; mvillalbae@ 123456unav.es (M.V.E.); ceandrea@ 123456unav.es (C.E.d.A.)
                [5 ]Center for Biomedical Research in the Cancer Network (Centro de Investigación Biomédica en Red de Cáncer, CIBERONC), Instituto de Salud Carlos III, 28046 Madrid, Spain; victoriam.heredia@ 123456salud.madrid.org (V.H.-S.); marta.mendiola@ 123456salud.madrid.org (M.M.)
                [6 ]Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain
                [7 ]Department of Obstetrics & Gynecology, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain; ahernandez@ 123456salud.madrid.org
                [8 ]Faculty of Medicine, Universidad Autónoma de Madrid, 28029 Madrid, Spain
                [9 ]Akoya Biosciences, 100 Campus Drive, 6th Floor, Marlborough, MA 01752, USA; imasetto@ 123456akoyabio.com (I.M.); vgoubert@ 123456akoyabio.com (V.G.)
                [10 ]Lunaphore Technologies SA, Route de Lully 5C, CH-1131 Tolochenaz, Switzerland; ece.kadioglu@ 123456lunaphore.com
                [11 ]Translational Oncology Research Laboratory, Hospital La Paz Institute for Health Research (IdiPAZ), 28046 Madrid, Spain
                [12 ]Chronic Disease Programme, UFIEC, Instituto de Salud Carlos III, 28220 Majadahonda, Madrid, Spain; r.barderasm@ 123456isciii.es
                [13 ]Centro de Investigaciones Biológicas (CIB-CSIC), Department of Molecular Biomedicine, 28039 Madrid, Spain; icasal@ 123456cib.csic.es
                Author notes
                [†]

                Present address: Department of Pathology, Hospital Universitario Ramón y Cajal, IRYCIS, 28034 Madrid, Spain.

                [‡]

                Present address: Department of Medical Oncology, Hospital Universitario Rey Juan Carlos, 28933 Móstoles, Madrid, Spain.

                Author information
                https://orcid.org/0000-0002-2298-4683
                https://orcid.org/0000-0001-5582-6879
                https://orcid.org/0000-0002-9183-0610
                https://orcid.org/0000-0002-3467-106X
                https://orcid.org/0000-0003-3539-7469
                https://orcid.org/0000-0003-1085-2840
                https://orcid.org/0000-0002-5401-3216
                https://orcid.org/0000-0002-2183-3699
                Article
                cancers-13-00794
                10.3390/cancers13040794
                7917913
                33672863
                e9ead081-3c95-428d-934a-ed2f3834f73d
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 December 2020
                : 09 February 2021
                Categories
                Article

                endometrial cancer,low grade,proteomics,pathways,slit/robo,necroptosis,ferroptosis,immune microenvironment

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