Structural analysis of genomic and proteomic signatures reveal dynamic expression of intrinsically disordered regions in breast cancer
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Abstract
Structural features of proteins capture underlying information about protein evolution and function, which enhances the analysis of proteomic and transcriptomic data. Here, we develop Structural Analysis of Gene and protein Expression Signatures (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 Catalog of Somatic Mutations In Cancer 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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Cites
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
Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer
Chung, W., Eum, H. H., Lee, H.-O., Lee, K.-M., Lee, H.-B., Kim, K.-T., Ryu, H. S., Kim, S., Lee, J. E., Park, Y. H., et al. (2017) · Nature Communications · doi:10.1038/ncomms15081 · Cited by 992 · cited 1× · see citing works
“(4) where TP is true positives and FP is false positives, recall Eq.”
Structure-based prediction of protein–protein interactions on a genome-wide scale
Zhang, Q. C., Petrey, D., Deng, L., Qiang, L., Shi, Y., Thu, C. A., Bisikirska, B., Lefebvre, C., Accili, D., Hunter, T., et al. (2012) · Nature · doi:10.1038/nature11503 · Cited by 723 · 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
- Elsevier BV
- Published
- 2024-09
- Volume
- 27
- Issue
- 9
- Pages
- 110640
- ISSN
- 2589-0042 (ISSN-L)
- PMC
- PMC11416222
- OpenAlex
- W4401386769
- Cited by
- 2
- References
- 3
- Citations by year
- 2025: 2
- FWCI
- 0.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- 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 Heart Lung and Blood Institute (F30 HL160179)
- National Institutes of Health (U01 CA271318, 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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