{"title":"基于免疫逃逸的免疫治疗宫颈癌新靶点的生物信息学分析。","authors":"Ying-Hao Han, DA-Yu Ma, Seung-Jae Lee, Ying-Ying Mao, Shuai-Yang Sun, Mei-Hua Jin, Hu-Nan Sun, Taeho Kwon","doi":"10.21873/cgp.20390","DOIUrl":null,"url":null,"abstract":"<p><strong>Background/aim: </strong>Cervical cancer (CC) is a high-risk disease in women, and advanced CC can be difficult to treat even with surgery, radiotherapy, and chemotherapy. Hence, developing more effective treatment methods is imperative. Cancer cells undergo a renewal process to escape immune surveillance and then attack the immune system. However, the underlying mechanisms remain unclear. Currently, only one immunotherapy drug has been approved by the Food and Drug Administration for CC, thus indicating the need for and importance of identifying key targets related to immunotherapy.</p><p><strong>Materials and methods: </strong>Data on CC and normal cervical tissue samples were downloaded from the National Center for Biotechnology Information database. Transcriptome Analysis Console software was used to analyze differentially expressed genes (DEGs) in two sample groups. These DEGs were uploaded to the DAVID online analysis platform to analyze biological processes for which they were enriched. Finally, Cytoscape was used to map protein interaction and hub gene analyses.</p><p><strong>Results: </strong>A total of 165 up-regulated and 362 down-regulated genes were identified. Among them, 13 hub genes were analyzed in a protein-protein interaction network using the Cytoscape software. The genes were screened out based on the betweenness centrality value and average degree of all nodes. The hub genes were as follows: ANXA1, APOE, AR, C1QC, CALML5, CD47, CTSZ, HSP90AA1, HSP90B1, NOD2, THY1, TLR4, and VIM. We identified the following 12 microRNAs (miRNAs) that target the hub genes: hsa-miR-2110, hsa-miR-92a-2-5p, hsa-miR-520d-5p, hsa-miR-4514, hsa-miR-4692, hsa-miR-499b-5p, hsa-miR-5011-5p, hsa-miR-6847-5p, hsa-miR-8054, hsa-miR-642a-5p, hsa-miR-940, and hsa-miR-6893-5p.</p><p><strong>Conclusion: </strong>Using bioinformatics, we identified potential miRNAs that regulated the cancer-related genes and long noncoding RNAs (lncRNAs) that regulated these miRNAs. We further elucidated the mutual regulation of mRNAs, miRNAs, and lncRNAs involved in CC occurrence and development. These findings may have major applications in the treatment of CC by immunotherapy and the development of drugs against CC.</p>","PeriodicalId":9516,"journal":{"name":"Cancer Genomics & Proteomics","volume":"20 4","pages":"383-397"},"PeriodicalIF":2.6000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320560/pdf/cgp-20-383.pdf","citationCount":"0","resultStr":"{\"title\":\"Bioinformatics Analysis of Novel Targets for Treating Cervical Cancer by Immunotherapy Based on Immune Escape.\",\"authors\":\"Ying-Hao Han, DA-Yu Ma, Seung-Jae Lee, Ying-Ying Mao, Shuai-Yang Sun, Mei-Hua Jin, Hu-Nan Sun, Taeho Kwon\",\"doi\":\"10.21873/cgp.20390\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background/aim: </strong>Cervical cancer (CC) is a high-risk disease in women, and advanced CC can be difficult to treat even with surgery, radiotherapy, and chemotherapy. Hence, developing more effective treatment methods is imperative. Cancer cells undergo a renewal process to escape immune surveillance and then attack the immune system. However, the underlying mechanisms remain unclear. Currently, only one immunotherapy drug has been approved by the Food and Drug Administration for CC, thus indicating the need for and importance of identifying key targets related to immunotherapy.</p><p><strong>Materials and methods: </strong>Data on CC and normal cervical tissue samples were downloaded from the National Center for Biotechnology Information database. Transcriptome Analysis Console software was used to analyze differentially expressed genes (DEGs) in two sample groups. These DEGs were uploaded to the DAVID online analysis platform to analyze biological processes for which they were enriched. Finally, Cytoscape was used to map protein interaction and hub gene analyses.</p><p><strong>Results: </strong>A total of 165 up-regulated and 362 down-regulated genes were identified. Among them, 13 hub genes were analyzed in a protein-protein interaction network using the Cytoscape software. The genes were screened out based on the betweenness centrality value and average degree of all nodes. The hub genes were as follows: ANXA1, APOE, AR, C1QC, CALML5, CD47, CTSZ, HSP90AA1, HSP90B1, NOD2, THY1, TLR4, and VIM. We identified the following 12 microRNAs (miRNAs) that target the hub genes: hsa-miR-2110, hsa-miR-92a-2-5p, hsa-miR-520d-5p, hsa-miR-4514, hsa-miR-4692, hsa-miR-499b-5p, hsa-miR-5011-5p, hsa-miR-6847-5p, hsa-miR-8054, hsa-miR-642a-5p, hsa-miR-940, and hsa-miR-6893-5p.</p><p><strong>Conclusion: </strong>Using bioinformatics, we identified potential miRNAs that regulated the cancer-related genes and long noncoding RNAs (lncRNAs) that regulated these miRNAs. We further elucidated the mutual regulation of mRNAs, miRNAs, and lncRNAs involved in CC occurrence and development. These findings may have major applications in the treatment of CC by immunotherapy and the development of drugs against CC.</p>\",\"PeriodicalId\":9516,\"journal\":{\"name\":\"Cancer Genomics & Proteomics\",\"volume\":\"20 4\",\"pages\":\"383-397\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320560/pdf/cgp-20-383.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Genomics & Proteomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21873/cgp.20390\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Genomics & Proteomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21873/cgp.20390","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Bioinformatics Analysis of Novel Targets for Treating Cervical Cancer by Immunotherapy Based on Immune Escape.
Background/aim: Cervical cancer (CC) is a high-risk disease in women, and advanced CC can be difficult to treat even with surgery, radiotherapy, and chemotherapy. Hence, developing more effective treatment methods is imperative. Cancer cells undergo a renewal process to escape immune surveillance and then attack the immune system. However, the underlying mechanisms remain unclear. Currently, only one immunotherapy drug has been approved by the Food and Drug Administration for CC, thus indicating the need for and importance of identifying key targets related to immunotherapy.
Materials and methods: Data on CC and normal cervical tissue samples were downloaded from the National Center for Biotechnology Information database. Transcriptome Analysis Console software was used to analyze differentially expressed genes (DEGs) in two sample groups. These DEGs were uploaded to the DAVID online analysis platform to analyze biological processes for which they were enriched. Finally, Cytoscape was used to map protein interaction and hub gene analyses.
Results: A total of 165 up-regulated and 362 down-regulated genes were identified. Among them, 13 hub genes were analyzed in a protein-protein interaction network using the Cytoscape software. The genes were screened out based on the betweenness centrality value and average degree of all nodes. The hub genes were as follows: ANXA1, APOE, AR, C1QC, CALML5, CD47, CTSZ, HSP90AA1, HSP90B1, NOD2, THY1, TLR4, and VIM. We identified the following 12 microRNAs (miRNAs) that target the hub genes: hsa-miR-2110, hsa-miR-92a-2-5p, hsa-miR-520d-5p, hsa-miR-4514, hsa-miR-4692, hsa-miR-499b-5p, hsa-miR-5011-5p, hsa-miR-6847-5p, hsa-miR-8054, hsa-miR-642a-5p, hsa-miR-940, and hsa-miR-6893-5p.
Conclusion: Using bioinformatics, we identified potential miRNAs that regulated the cancer-related genes and long noncoding RNAs (lncRNAs) that regulated these miRNAs. We further elucidated the mutual regulation of mRNAs, miRNAs, and lncRNAs involved in CC occurrence and development. These findings may have major applications in the treatment of CC by immunotherapy and the development of drugs against CC.
期刊介绍:
Cancer Genomics & Proteomics (CGP) is an international peer-reviewed journal designed to publish rapidly high quality articles and reviews on the application of genomic and proteomic technology to basic, experimental and clinical cancer research. In this site you may find information concerning the editorial board, editorial policy, issue contents, subscriptions, submission of manuscripts and advertising. The first issue of CGP circulated in January 2004.
Cancer Genomics & Proteomics is a journal of the International Institute of Anticancer Research. From January 2013 CGP is converted to an online-only open access journal.
Cancer Genomics & Proteomics supports (a) the aims and the research projects of the INTERNATIONAL INSTITUTE OF ANTICANCER RESEARCH and (b) the organization of the INTERNATIONAL CONFERENCES OF ANTICANCER RESEARCH.