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      PRINS lncRNA Is a New Biomarker Candidate for HPV Infection and Prognosis of Head and Neck Squamous Cell Carcinomas

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          Abstract

          Numerous studies have shown that human papillomavirus (HPV) infection is one of the important risk factors for head and neck squamous cell carcinoma (HNSCC) progression and affects the expression of multiple genes, which might serve as new biomarkers. This study examines the effects of HPV infection on long non-coding RNA (lncRNA) expression and the immune system, particularly PRINS (Psoriasis susceptibility-related RNA Gene Induced by Stress). The Cancer Genome Atlas (TCGA) expression data for lncRNA genes and clinical data were analyzed by GraphPad Prism 5/7. The expressions of PRINS, CDKN2B-AS1, TTTY14, TTTY15, MEG3, and H19 were significantly different in HPV-positive and HPV-negative patients. HPV-positive patients with high PRINS expression demonstrated significantly better overall survival (OS) and disease-free survival (DFS). HPV-positive patients with high PRINS expression showed changes in gene expression associated with immune and antiviral responses. A majority of HPV-positive patients with high PRINS expression demonstrated a high number of immune cells within tumors. PRINS expression was significantly associated with HPV-infection HNSCC tumors. Validation of these results using data set from Gene Expression Omnibus (GEO) indicated that PRINS is upregulated in HPV active infections and in “atypical 1 (IR)” HNSCC clusters, negatively influencing patients’ overall survival. Patients with high PRINS expression display different immunological profiles than those with low expression levels. For instance, they have active HPV infection status or are clustered in the “atypical 1 (IR)” subtype of HNSCC which influences both viral infection and patients’ survival. It is likely that PRINS could be used as a potential biomarker for HNSCC patients, but its role is dual. On the one hand, it stimulates patients’ immune response, while on the other it can be favorable in virus replication.

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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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            UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses1

            Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.
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              Long Noncoding RNAs in Cancer Pathways.

              Genome-wide cancer mutation analyses are revealing an extensive landscape of functional mutations within the noncoding genome, with profound effects on the expression of long noncoding RNAs (lncRNAs). While the exquisite regulation of lncRNA transcription can provide signals of malignant transformation, we now understand that lncRNAs drive many important cancer phenotypes through their interactions with other cellular macromolecules including DNA, protein, and RNA. Recent advancements in surveying lncRNA molecular mechanisms are now providing the tools to functionally annotate these cancer-associated transcripts, making these molecules attractive targets for therapeutic intervention in the fight against cancer.
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                Author and article information

                Journal
                Diagnostics (Basel)
                Diagnostics (Basel)
                diagnostics
                Diagnostics
                MDPI
                2075-4418
                28 September 2020
                October 2020
                : 10
                : 10
                : 762
                Affiliations
                [1 ]Laboratory of Cancer Genetics, Greater Poland Cancer Centre, 15 Garbary Street, Room 5025, 61-866 Poznan, Poland; mg.kopczynska@ 123456gmail.com (M.K.); kacper.guglas@ 123456gmail.com (K.G.); a.s.sobocinska@ 123456gmail.com (J.S.); anna.teresiak@ 123456wco.pl (A.T.); renata.blizniak@ 123456wco.pl (R.B.); kasialam@ 123456o2.pl (K.L.)
                [2 ]Department of Cancer Immunology, Chair of Medical Biotechnology, Poznan University of Medical Sciences, 8 Rokietnicka Street, 60-806 Poznan, Poland; mackiewicz.aa@ 123456gmail.com
                [3 ]Postgraduate School of Molecular Medicine, Medical University of Warsaw, 61 Zwirki i Wigury Street, 02-091 Warsaw, Poland
                [4 ]Department of Diagnostics and Cancer Immunology, Greater Poland Cancer Centre, 15 Garbary Street, 61-866 Poznan, Poland; jmackiewicz@ 123456ump.edu.pl
                [5 ]Department of Medical and Experimental Oncology, Heliodor Swiecicki Clinical Hospital, Poznan University of Medical Sciences, 16/18 Grunwaldzka Street, 60-786 Poznan, Poland
                [6 ]Department of Oncology, Poznan University of Medical Sciences, Poznan University of Medical Sciences, 82-84 Szamarzewskiego Street, 60-569 Poznan, Poland
                Author notes
                Author information
                https://orcid.org/0000-0002-7080-750X
                Article
                diagnostics-10-00762
                10.3390/diagnostics10100762
                7599931
                32998396
                927d9530-b315-4957-99bb-6a6ab4a66101
                © 2020 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
                : 14 August 2020
                : 26 September 2020
                Categories
                Article

                hnscc,hpv,biomarker,personalized medicine,immune response,microenvironment,viral infection

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