Structural Analysis of Genomic and Proteomic Signatures Reveal Dynamic Expression of Intrinsically Disordered Regions in Breast Cancer and Tissue
Open accessPreprint — published as 10.1016/j.isci.2024.110640 · Paper page
Abstract
Summary: Structural features of proteins capture underlying information about protein evolution and function, which enhances the analysis of proteomic and transcriptomic data. Here we develop S tructural A nalysis of G ene and protein E xpression S ignatures (SAGES), a method that describes expression data using features calculated from sequence-based prediction methods and 3D structural models. We used SAGES, along with machine learning, to characterize tissues from healthy individuals and those with breast cancer. We analyzed gene expression data from 23 breast cancer patients and genetic mutation data from the COSMIC database as well as 17 breast tumor protein expression profiles. We identified prominent expression of intrinsically disordered regions in breast cancer proteins as well as relationships between drug perturbation signatures and breast cancer disease signatures. Our results suggest that SAGES is generally applicable to describe diverse biological phenomena including disease states and drug effects.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
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- Authors
- Zatorski, N., Sun, Y., Elmas, A., Dallago, C., Karl, T., Stein, D., Rost, B., Huang, K.-L., Walsh, M., & Schlessinger, A.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Technical University of Munich (DE)
- Corresponding author
- Zatorski, Nicole
- ORCID
- Venue
- iScience
- Publisher
- openRxiv
- Published
- 2023-02-24
- Volume
- 27
- Issue
- 9
- Pages
- 110640-110640
- ISSN
- 2589-0042 (ISSN-L)
- PMC
- PMC11416222
- OpenAlex
- W4401386769
- Cited by
- 2
- References
- 1
- Citations by year
- 2025: 2
- FWCI
- 0.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- iScience (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (1r01hd107528-01a1, R01 HD107528)
- National Heart, Lung, and Blood Institute (F30HL160179)
- National Cancer Institute (U01CA271318)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01-HD107528)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- breast cancer, intrinsically disordered regions, protein structural properties, sage, gene expression signatures, proteomic signatures, somatic mutations, protein 3D structure, protein evolution, cancer tissue classification
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