Description
Technologies capable of characterizing the full breadth of cellular systems need to be able to measure millions of proteins, isoforms, and complexes simultaneously. We describe an approach that fulfils this criterion: Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT). ADAPT employs an enriched library of single-stranded oligodeoxynucleotides (ssODNs) to profile complex biological samples, thus achieving an unprecedented coverage of system-wide, native biomolecules. We used ADAPT as a highly specific profiling tool that distinguishes women with or without breast cancer based on circulating exosomes in their blood. To develop ADAPT, we enriched a library of ~10[superscript 11] ssODNs for those associating with exosomes from breast cancer patients or controls. The resulting 10[superscript 6] enriched ssODNs were then profiled against plasma from independent groups of healthy and breast cancer-positive women. ssODN-mediated affinity purification and mass spectrometry identified low-abundance exosome-associated proteins and protein complexes, some with known significance in both normal homeostasis and disease. Sequencing of the recovered ssODNs provided quantitative measures that were used to build highly accurate multi-analyte signatures for patient classification. Probing plasma from 500 subjects with a smaller subset of 2000 resynthesized ssODNs stratified healthy, breast biopsy-negative, and -positive women. An AUC of 0.73 was obtained when comparing healthy donors with biopsy-positive patients.
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Title
- Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach
Contributors
- Domenyuk, Valeriy (Author)
- Zhong, Zhenyu (Author)
- Stark, Adam (Author)
- Xiao, Nianqing (Author)
- O'Neill, Heather A. (Author)
- Wei, Xixi (Author)
- Wang, Jie (Author)
- Tinder, Teresa T. (Author)
- Tonapi, Sonal (Author)
- Duncan, Janet (Author)
- Hornung, Tassilo (Author)
- Hunter, Andrew (Author)
- Miglarese, Mark R. (Author)
- Schorr, Joachim (Author)
- Halbert, David D. (Author)
- Quackenbush, John (Author)
- Poste, George (Author)
- Berry, Donald A. (Author)
- Mayer, Gunter (Author)
- Famulok, Michael (Author)
- Spetzler, David (Author)
- Consortium for Biosocial Complex Systems (Contributor)
- Complex Adaptive Systems Initiative (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2017-02-20
Resource Type
Collections this item is in
Identifier
- Digital object identifier: 10.1038/srep42741
- Identifier TypeInternational standard serial numberIdentifier Value2045-2322
Note
- The final version of this article, as published in Scientific Reports, can be viewed online at: https://www.nature.com/articles/srep42741
Citation and reuse
Cite this item
This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.
Domenyuk, V., Zhong, Z., Stark, A., Xiao, N., O’Neill, H. A., Wei, X., . . . Spetzler, D. (2017). Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach. Scientific Reports, 7, 42741. doi:10.1038/srep42741