{"title":"提高免疫疗法的精确度","authors":"Erik N. Bergstrom, Ludmil B. Alexandrov","doi":"10.1038/s43018-024-00802-4","DOIUrl":null,"url":null,"abstract":"Recent advancements in targeted immune checkpoint blockade (ICB) therapy have reshaped cancer treatment paradigms. However, many patients do not respond, highlighting the need for robust biomarkers. A study now introduces an approach using multi-omics data and machine learning to improve patient selection for ICB therapy, offering more effective treatment.","PeriodicalId":18885,"journal":{"name":"Nature cancer","volume":null,"pages":null},"PeriodicalIF":23.5000,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced precision in immunotherapy\",\"authors\":\"Erik N. Bergstrom, Ludmil B. Alexandrov\",\"doi\":\"10.1038/s43018-024-00802-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent advancements in targeted immune checkpoint blockade (ICB) therapy have reshaped cancer treatment paradigms. However, many patients do not respond, highlighting the need for robust biomarkers. A study now introduces an approach using multi-omics data and machine learning to improve patient selection for ICB therapy, offering more effective treatment.\",\"PeriodicalId\":18885,\"journal\":{\"name\":\"Nature cancer\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":23.5000,\"publicationDate\":\"2024-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature cancer\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.nature.com/articles/s43018-024-00802-4\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature cancer","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s43018-024-00802-4","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
Recent advancements in targeted immune checkpoint blockade (ICB) therapy have reshaped cancer treatment paradigms. However, many patients do not respond, highlighting the need for robust biomarkers. A study now introduces an approach using multi-omics data and machine learning to improve patient selection for ICB therapy, offering more effective treatment.
期刊介绍：
Cancer is a devastating disease responsible for millions of deaths worldwide. However, many of these deaths could be prevented with improved prevention and treatment strategies. To achieve this, it is crucial to focus on accurate diagnosis, effective treatment methods, and understanding the socioeconomic factors that influence cancer rates.
Nature Cancer aims to serve as a unique platform for sharing the latest advancements in cancer research across various scientific fields, encompassing life sciences, physical sciences, applied sciences, and social sciences. The journal is particularly interested in fundamental research that enhances our understanding of tumor development and progression, as well as research that translates this knowledge into clinical applications through innovative diagnostic and therapeutic approaches. Additionally, Nature Cancer welcomes clinical studies that inform cancer diagnosis, treatment, and prevention, along with contributions exploring the societal impact of cancer on a global scale.
In addition to publishing original research, Nature Cancer will feature Comments, Reviews, News & Views, Features, and Correspondence that hold significant value for the diverse field of cancer research.
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