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. © 2022 The Pathological Society of Great Britain and Ireland.
Keywords: artificial intelligence; cancer; computational pathology; deep learning; heterogeneity; mass spectrometry; pathology; proteomics.
© 2022 The Pathological Society of Great Britain and Ireland.