{"title":"肾细胞癌的泛组学研究及其对未来临床实践的意义。","authors":"Jennifer J Huang, James J Hsieh","doi":"10.3233/KCA-200085","DOIUrl":null,"url":null,"abstract":"<p><p>Renal cell carcinoma has traditionally been classified based on histological features. Contemporary studies have identified genomic, transcriptomic, epigenomic, and metabolomic signatures that correspond to or even transcend histological subtypes. Much remains to be learned about improving the algorithm of pan-omics integration for precision oncology, which will not only advance our understanding of RCC pathobiology and treatment response but also result in novel therapeutic opportunities. Accordingly, this review focuses on recent RCC multi-omics literature. Encouragingly, a few reports on omics integration into routinely employed prognostic risk models have shown early promise that could lay the foundation for future development of precision kidney cancer therapies. Hence, this article serves as a primer on what we have learned and how we might better realize the clinical potential of the burgeoning pan-omics data.</p>","PeriodicalId":74039,"journal":{"name":"Kidney cancer (Clifton, Va.)","volume":"4 3","pages":"121-129"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/KCA-200085","citationCount":"1","resultStr":"{\"title\":\"The Pan-Omics Landscape of Renal Cell Carcinoma and Its Implication on Future Clinical Practice.\",\"authors\":\"Jennifer J Huang, James J Hsieh\",\"doi\":\"10.3233/KCA-200085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Renal cell carcinoma has traditionally been classified based on histological features. Contemporary studies have identified genomic, transcriptomic, epigenomic, and metabolomic signatures that correspond to or even transcend histological subtypes. Much remains to be learned about improving the algorithm of pan-omics integration for precision oncology, which will not only advance our understanding of RCC pathobiology and treatment response but also result in novel therapeutic opportunities. Accordingly, this review focuses on recent RCC multi-omics literature. Encouragingly, a few reports on omics integration into routinely employed prognostic risk models have shown early promise that could lay the foundation for future development of precision kidney cancer therapies. Hence, this article serves as a primer on what we have learned and how we might better realize the clinical potential of the burgeoning pan-omics data.</p>\",\"PeriodicalId\":74039,\"journal\":{\"name\":\"Kidney cancer (Clifton, Va.)\",\"volume\":\"4 3\",\"pages\":\"121-129\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3233/KCA-200085\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Kidney cancer (Clifton, Va.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/KCA-200085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kidney cancer (Clifton, Va.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/KCA-200085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Pan-Omics Landscape of Renal Cell Carcinoma and Its Implication on Future Clinical Practice.
Renal cell carcinoma has traditionally been classified based on histological features. Contemporary studies have identified genomic, transcriptomic, epigenomic, and metabolomic signatures that correspond to or even transcend histological subtypes. Much remains to be learned about improving the algorithm of pan-omics integration for precision oncology, which will not only advance our understanding of RCC pathobiology and treatment response but also result in novel therapeutic opportunities. Accordingly, this review focuses on recent RCC multi-omics literature. Encouragingly, a few reports on omics integration into routinely employed prognostic risk models have shown early promise that could lay the foundation for future development of precision kidney cancer therapies. Hence, this article serves as a primer on what we have learned and how we might better realize the clinical potential of the burgeoning pan-omics data.