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

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.
Reuse Permissions
  • Downloads
    PDF (2 MB)
    Download count: 1

    Details

    Title
    • Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach
    Contributors
    Date Created
    2017-02-20
    Resource Type
  • Text
  • Collections this item is in
    Identifier
    • Digital object identifier: 10.1038/srep42741
    • Identifier Type
      International standard serial number
      Identifier Value
      2045-2322
    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

    Machine-readable links