Detection of reliable markers of therapy response and drug resistance remains a major clinical challenge in ovarian cancer. This is particularly true for a series of nanotherapeutics entering the clinical arena. One little explored opportunity lies in the analysis of exosomes, 50-200 nm sized vesicles continuously shed into the circulation. Importantly such tumor derived exosomes are abundant (1011 vesicles/ml of peripheral blood in cancer patients), are fairly stable over time and contain proteins reflective of those found in parent tumors. A current major challenge and opportunity is the development of methods for rapidly determining the abundance and composition of cMVs from clinical samples. We have recently developed a highly sensitive, nanotechnology-based, point-of-care diagnostic method termed nPLEX (nano Plasmonic Exosome) which comprises periodic nanohole arrays fabricated in an opaque gold film for transmission plasmon imaging (Nat Biotechnol 2014;32, 490-5). We have shown that i) such analyses are exquisitely sensitive, ii) allow profiling of dozens of proteins on and inside exosomes thus allowing cell of origin studies and iii) that nPLEX analysis allows sophisticated therapy assessment. The goal of this application is to advance the nPLEX technology by i) expanding it to allow parallel profiling of protein and RNA, ii) validating it as a therapeutic read-out of nanoparticle therapeutics in mouse models and in the clinic. We hypothesize that the approach will be more sensitive and comprehensive in exosomal analysis than is currently possible and allow treatment evaluation. The proposed integrated profiling method has the potential to transform nano therapeutic trials, cancer research and clinical practice. It will enable objective therapeutic read-outs, events that occur before conventional clinical metrics. It will facilitate extensive profiling of exosome in paucicellular clinical specimens, significantly reduce costs, and can be easily combined with other downstream analyses.
We propose to further develop a new analysis technique to study key cancer cell proteins and mRNA in exosomes, small vesicles shed from cancer cells. The method not only allows much more extensive and robust profiling than what is currently possible but uses less material obviating the need for more invasive core biopsies, is cost effective, scalable and samples are not destroyed during the analytical process. The proposed profiling method has the potential to transform nano-therapy cancer trials as it provides broad, quantitative readouts.
| Park, Jongmin; Im, Hyungsoon; Hong, Seonki et al. (2018) Analyses of Intravesicular Exosomal Proteins Using a Nano-Plasmonic System. ACS Photonics 5:487-494 |
| Min, Jouha; Nothing, Maria; Coble, Ben et al. (2018) Integrated Biosensor for Rapid and Point-of-Care Sepsis Diagnosis. ACS Nano 12:3378-3384 |
| Kim, Sung-Jin; Wang, Chuangqi; Zhao, Bing et al. (2018) Deep transfer learning-based hologram classification for molecular diagnostics. Sci Rep 8:17003 |
| Shao, Huilin; Im, Hyungsoon; Castro, Cesar M et al. (2018) New Technologies for Analysis of Extracellular Vesicles. Chem Rev 118:1917-1950 |
| Im, Hyungsoon; Lee, Kyungheon; Weissleder, Ralph et al. (2017) Novel nanosensing technologies for exosome detection and profiling. Lab Chip 17:2892-2898 |
| Min, Changwook; Park, Jongmin; Mun, Jae Kyoung et al. (2017) Integrated microHall magnetometer to measure the magnetic properties of nanoparticles. Lab Chip 17:4000-4007 |
| Park, Yong Il; Kim, Eunha; Huang, Chen-Han et al. (2017) Facile Coating Strategy to Functionalize Inorganic Nanoparticles for Biosensing. Bioconjug Chem 28:33-37 |
| Yang, Katherine S; Im, Hyungsoon; Hong, Seonki et al. (2017) Multiparametric plasma EV profiling facilitates diagnosis of pancreatic malignancy. Sci Transl Med 9: |
| Hong, Seonki; Park, Ki Soo; Weissleder, Ralph et al. (2017) Facile silicification of plastic surface for bioassays. Chem Commun (Camb) 53:2134-2137 |
| Park, Jongmin; Lin, Hsing-Ying; Assaker, Jean Pierre et al. (2017) Integrated Kidney Exosome Analysis for the Detection of Kidney Transplant Rejection. ACS Nano 11:11041-11046 |
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