Journal
JOURNAL OF PATHOLOGY
Volume 257, Issue 4, Pages 445-453Publisher
WILEY
DOI: 10.1002/path.5905
Keywords
mass spectrometry; proteomics; artificial intelligence; pathology; computational pathology; deep learning; heterogeneity; cancer
Funding
- Terry Fox New Investigator Award program
- Canadian Institute of Health Research
- Brain Tumor Foundation of Canada
- Ontario Institute for Cancer Research
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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.
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