Xiaoyun Lei, Song Mao, Yinshuang Li, Shi Huang, Jinchen Li, Wei Du, Chunmei Kuang, Kai Yuan
{"title":"ERVcancer: A web resource designed for querying activation of human endogenous retroviruses across major cancer types","authors":"Xiaoyun Lei, Song Mao, Yinshuang Li, Shi Huang, Jinchen Li, Wei Du, Chunmei Kuang, Kai Yuan","doi":"10.1016/j.jgg.2024.09.004","DOIUrl":null,"url":null,"abstract":"Human endogenous retroviruses (HERVs) comprise approximately 8% of the human genome, co-opted into the dynamic regulatory network of cellular potency in early embryonic development. In recent studies, resurgent HERVs' transcriptional activity has been frequently observed in many types of human cancers, suggesting their potential functions in the occurrence and progression of malignancy. However, a dedicated web resource for querying the relationship between activation of HERVs and cancer development is lacking. Here, we have constructed a database to explore the sequence information, expression profiles, survival prognosis, and genetic interactions of HERVs in diverse cancer types. Our database currently contains RNA sequencing data of 580 HERVs across 16,246 samples, including that of 6478 tumoral and 634 normal tissues, 932 cancer cell lines, as well as 151 early embryonic and 8051 human adult tissues. The primary goal is to provide an easily accessible and user-friendly database for professionals in the fields of bioinformatics, pathology, pharmacology, and related areas, enabling them to efficiently screen the activity of HERVs of interest in normal and cancerous tissues and evaluate the clinical relevance. The ERVcancer database is available at .","PeriodicalId":54825,"journal":{"name":"Journal of Genetics and Genomics","volume":"8 1","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Genetics and Genomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.jgg.2024.09.004","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Human endogenous retroviruses (HERVs) comprise approximately 8% of the human genome, co-opted into the dynamic regulatory network of cellular potency in early embryonic development. In recent studies, resurgent HERVs' transcriptional activity has been frequently observed in many types of human cancers, suggesting their potential functions in the occurrence and progression of malignancy. However, a dedicated web resource for querying the relationship between activation of HERVs and cancer development is lacking. Here, we have constructed a database to explore the sequence information, expression profiles, survival prognosis, and genetic interactions of HERVs in diverse cancer types. Our database currently contains RNA sequencing data of 580 HERVs across 16,246 samples, including that of 6478 tumoral and 634 normal tissues, 932 cancer cell lines, as well as 151 early embryonic and 8051 human adult tissues. The primary goal is to provide an easily accessible and user-friendly database for professionals in the fields of bioinformatics, pathology, pharmacology, and related areas, enabling them to efficiently screen the activity of HERVs of interest in normal and cancerous tissues and evaluate the clinical relevance. The ERVcancer database is available at .
期刊介绍:
The Journal of Genetics and Genomics (JGG, formerly known as Acta Genetica Sinica ) is an international journal publishing peer-reviewed articles of novel and significant discoveries in the fields of genetics and genomics. Topics of particular interest include but are not limited to molecular genetics, developmental genetics, cytogenetics, epigenetics, medical genetics, population and evolutionary genetics, genomics and functional genomics as well as bioinformatics and computational biology.