Integrating Computational Pathology and Proteomics to Overcome Tumor Heterogeneity
This Journal of Pathology review addresses why precision medicine trials have underperformed in many malignancies, attributing much of the failure to proteogenomic discordances and spatially distributed tumor heterogeneity. The authors propose integrating mass-spectrometry-based global proteomics with computational imaging to guide regional tissue sampling, thereby capturing biologically relevant variation that bulk analyses miss. The framework offers a practical strategy for more accurate molecular profiling in heterogeneous tumors.
The original study
Integrating computational pathology and proteomics to address tumor heterogeneity.
- Authors
- Dent A, Diamandis P
- Journal
- The Journal of pathology
- Type
- Journal Article, Review, Research Support, Non-U.S. Gov't
- PMID
- 35373360
Original abstract
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.