期刊
JOURNAL OF PATHOLOGY
卷 257, 期 4, 页码 445-453出版社
WILEY
DOI: 10.1002/path.5905
关键词
mass spectrometry; proteomics; artificial intelligence; pathology; computational pathology; deep learning; heterogeneity; cancer
资金
- Terry Fox New Investigator Award program
- Canadian Institute of Health Research
- Brain Tumor Foundation of Canada
- Ontario Institute for Cancer Research
Despite advances in cancer biology, precision medicine trials face challenges due to molecular inconsistencies and heterogeneous tumor biology. Integrating mass-spectrometry-based global proteomics and computational imaging can overcome these challenges of biologic variation in cancer.
Despite numerous advances in our molecular understanding of cancer biology, success in precision medicine trials has remained elusive for many malignancies. Emerging evidence now supports that these challenges are partly driven by proteogenomic discordances across molecular readouts and heterogeneous biology that is spatially distributed across tumors. Here we discuss these key limitations and how integrating the promise of mass-spectrometry-based global proteomics and computational imaging can help prioritize and direct regional sampling to help overcome these important challenges of biologic variation in cancer. (c) 2022 The Pathological Society of Great Britain and Ireland.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据