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Updated: Sep 30, 2025

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Cancer Conformational Landscape Shapes Tumorigenesis
Casimir Bamberger1, Jolene Diedrich1, Salvador Martìnez-Bartholomé1
1Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States.
Abstract:
During tumorigenesis, DNA mutations in protein coding sequences can alter amino acid sequences which can change the structures of proteins. While the 3D structure of mutated proteins has been studied with atomic resolution, the precise impact of somatic mutations on the 3D proteome during malignant transformation remains unknown because methods to reveal in vivo protein structures in high throughput are limited. Here, we measured the accessibility of the lysine ε-amine for chemical modification across proteomes using covalent protein painting (CPP) to indirectly determine alterations in the 3D proteome. CPP is a novel, high-throughput quantitative mass spectrometric method that surveyed a total of 8052 lysine sites across the 60 cell lines of the well-studied anticancer cell line panel (NCI60). Overall, 5.2 structural alterations differentiated any cancer cell line from the other 59. Structural aberrations in 98 effector proteins correlated with the selected presence of 90 commonly mutated proteins in the NCI60 cell line panel, suggesting that different tumor genotypes reshape a limited set of effector proteins. We searched our dataset for druggable conformational aberrations and identified 49 changes in the cancer conformational landscape that correlated with the growth inhibition profiles of 300 drug candidates out of 50,000 small molecules. We found that alterations in heat shock proteins are key predictors of anticancer drug efficacy, which implies that the proteostasis network may have a general but hitherto unrecognized role in maintaining malignancy. Individual lysine sites may serve as biomarkers to guide drug selection or may be directly targeted for anticancer drug development.
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