Enhanced precision in immunotherapy

IF 23.5 1区医学 Q1 ONCOLOGY

Nature cancer Pub Date : 2024-08-12 DOI:10.1038/s43018-024-00802-4

Erik N. Bergstrom, Ludmil B. Alexandrov

引用次数: 0

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.

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提高免疫疗法的精确度

靶向免疫检查点阻断疗法（ICB）的最新进展重塑了癌症治疗模式。然而，许多患者并没有响应，这凸显了对可靠生物标志物的需求。现在的一项研究介绍了一种利用多组学数据和机器学习来改进ICB疗法患者选择的方法，从而提供更有效的治疗。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature cancer Medicine-Oncology

CiteScore

31.10

自引率

1.80%

发文量

129

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.