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      LRP1B mutation is associated with tumor HPV status and promotes poor disease outcomes with a higher mutation count in HPV-related cervical carcinoma and head & neck squamous cell carcinoma

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          Abstract

          Human papillomavirus (HPV) infection and gene mutations were reputed as key factors in cervical carcinoma (CC) and head and neck squamous cell carcinoma (HNSCC). However, the associations of HPV status and gene mutations remain to be determined. This study aims to identify molecular patterns of LRP1B mutation and HPV status via rewiring tumor samples of HNSCC (n=1478) and CC (n=178) from the TCGA dataset. Here, we found that LRP1B mutation was associated with HPV status in CC ( P=0.040) and HNSCC ( P=0.044), especially in HPV 16 integrated CC ( P=0.036). Cancer survival analysis demonstrated that samples with LRP1B mutation showed poor disease outcomes in CC ( P=0.013) and HNSCC ( P=0.0124). In addition, the expression status of LPR1B was more favorable for prediction than TP53 or RB1 in CC and HNSCC. Mutation clustering analysis showed that samples with LRP1B mutation showed higher mutation count in CC ( P=1.76e-67) and HNSCC ( P<10e-10). Further analysis identified 289 co-occurrence genes in these two cancer types, which were enriched in PI3K signaling, cell division process, and chromosome segregation process, et al. The 289-co-occurrence gene signature identified a cluster of patients with a higher portion of copy number variation (CNV) lost in the genome, different tumor HPV status ( P<10e-10), higher mutation count ( P<10e-10), higher fraction genome altered value ( P=2.078e-4), higher aneuploidy score ( P=3.362e-4), and earlier started the smoking year ( P=2.572e-4), which were associated with shorter overall survival ( P=0.0103) in CC and HNSCC samples. Overall, LRP1B mutation was associated with tumor HPV status and was an unfavorable prognostic biomarker for CC and HNSCC.

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          Most cited references37

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          Hallmarks of Cancer: The Next Generation

          The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

            A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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              GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

              Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
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                Author and article information

                Journal
                Int J Biol Sci
                Int J Biol Sci
                ijbs
                International Journal of Biological Sciences
                Ivyspring International Publisher (Sydney )
                1449-2288
                2021
                22 April 2021
                : 17
                : 7
                : 1744-1756
                Affiliations
                [1 ]Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Guangdong, 518036, China.
                [2 ]Department of Critical Care Medicine, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
                [3 ]Department of Gynecology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
                Author notes
                ✉ Corresponding authors: Xi Xia (E-mail: xixia1126@ 123456hotmail.com ), Yu Shi (E-mail: shiyu@ 123456pkuszh.com ) & Zhi-ying Yu (E-mail: lizheyzy@ 123456163.com ).

                Competing Interests: The authors have declared that no competing interest exists.

                Article
                ijbsv17p1744
                10.7150/ijbs.56970
                8120457
                33994859
                295baa02-d875-48a6-ba62-569b5f89f9d3
                © The author(s)

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.

                History
                : 9 December 2020
                : 5 April 2021
                Categories
                Research Paper

                Life sciences
                lrp1b mutation,tumor hpv status,cervical carcinoma,head and neck squamous cell carcinoma,tumor mutation count

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