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      Microfibril Associated Protein 5 (MFAP5) Is Related to Survival of Ovarian Cancer Patients but Not Useful as a Prognostic Biomarker

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          Abstract

          Ovarian cancer (OC) is usually diagnosed late due to its nonspecific symptoms and lack of reliable tools for early diagnostics and screening. OC studies concentrate on the search for new biomarkers and therapeutic targets. This study aimed to validate the MFAP5 gene, and its encoded protein, as a potential prognostic biomarker. In our previous study, we found that patients with high-grade serous OC who had higher MFAP5 mRNA levels had shorter survival, as compared with those with lower levels. Here, we used the Kaplan-Meier Plotter and CSIOVDB online tools to analyze possible associations of MFAP5 expression with survival and other clinico-pathological features. In these analyses, higher MFAP5 mRNA expression was observed in the more advanced FIGO stages and high-grade tumors, and was significantly associated with shorter overall and progression-free survival. Next, we analyzed the expression of the MFAP5 protein by immunohistochemistry (IHC) in 108 OC samples and tissue arrays. Stronger MFAP5 expression was associated with stronger desmoplastic reaction and serous vs. non-serous histology. We found no significant correlation between IHC results and survival, although there was a trend toward shorter survival in patients with the highest IHC scores. We searched for co-expressed genes/proteins using cBioPortal and analyzed potential MFAP5 interaction networks with the STRING tool. MFAP5 was shown to interact with many extracellular matrix proteins, and was connected to the Notch signaling pathway. Therefore, although not suitable as a prognostic biomarker for evaluation with a simple diagnostic tool like IHC, MFAP5 is worth further studies as a possible therapeutic target.

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          Most cited references43

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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              The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.

              The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications. © 2012 AACR.
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                Author and article information

                Contributors
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                Journal
                IJMCFK
                International Journal of Molecular Sciences
                IJMS
                MDPI AG
                1422-0067
                December 2022
                December 15 2022
                : 23
                : 24
                : 15994
                Article
                10.3390/ijms232415994
                9787877
                36555638
                cf96d7d6-25b0-49e7-9100-b7f81dd9c3bd
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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