One of the major challenges in medicine is the rapid and accurate measurement of protein bio- markers, cells and organisms in different biological samples. During the prior funding period we had developed a broadly applicable, novel, point-of-care diagnostic platform using """"""""magnetic relaxation switches"""""""" as a proximity sensor to amplify molecular interactions. We have shown that highly sensitive and selective measurements (e.g. DNA, mRNA, proteins, metabolites, drugs, bacteria, cells) can be obtained on small volume of unprocessed biological samples. One of the critical limitations of the approach however, was the need for bulky and/or complex NMR systems to carry out the measurements. We have now achieved a technological breakthrough by miniaturizing an entire NMR system onto a single, integrated circuit (IC) chip (dubbed DMR for """"""""diagnostic magnetic resonance""""""""). In preliminary feasibility experiments, we have shown that we can already achieve detection sensitivities of 10-12 M surpassing those of many traditional, time consuming assays. The goal of this competing renewal is to further mature DMR into a cutting-edge detection technology and apply it to molecular and cellular sensing and profiling of cells. Using cancer cells as a specific sensing target, we propose three specific aims to refine and further validate the DMR technology: 1) optimize particle constructs for high efficiency detection of cancer cells;2) determine the detection threshold and specificity for cancer cells and 3) develop real time molecular analysis of cells in biological samples. This proposal addresses a number of unmet needs and aims at optimizing, validating and further improving the novel DMR biodetection platform.

Public Health Relevance

We are developing a handheld sensor to quickly assay blood and tissue samples in cancer patients. Based on fundamentally new designs, this technology allows sensing and rapid profiling of cancer cells in blood.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
3R01EB004626-05A1S1
Application #
7908069
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Zhang, Yantian
Project Start
2004-09-01
Project End
2011-05-31
Budget Start
2009-09-01
Budget End
2011-05-31
Support Year
5
Fiscal Year
2009
Total Cost
$175,968
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
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
Shao, Huilin; Im, Hyungsoon; Castro, Cesar M et al. (2018) New Technologies for Analysis of Extracellular Vesicles. Chem Rev 118:1917-1950
Gee, Michael S; Ghazani, Arezou A; Haq, Rizwan et al. (2017) Point of care assessment of melanoma tumor signaling and metastatic burden from ?NMR analysis of tumor fine needle aspirates and peripheral blood. Nanomedicine 13:821-828
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
Park, Ki Soo; Kim, Hoyoung; Kim, Soojin et al. (2017) Nanomagnetic System for Rapid Diagnosis of Acute Infection. ACS Nano 11:11425-11432
Lin, Hsing-Ying; Huang, Chen-Han; Park, Jongmin et al. (2017) Integrated Magneto-Chemical Sensor For On-Site Food Allergen Detection. ACS Nano 11:10062-10069
Park, Ki Soo; Chung, Hyun Jung; Khanam, Farhana et al. (2016) A magneto-DNA nanoparticle system for the rapid and sensitive diagnosis of enteric fever. Sci Rep 6:32878
Song, Jun; Leon Swisher, Christine; Im, Hyungsoon et al. (2016) Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography. Sci Rep 6:24681
Park, Ki Soo; Huang, Chen-Han; Lee, Kyungheon et al. (2016) Rapid identification of health care-associated infections with an integrated fluorescence anisotropy system. Sci Adv 2:e1600300

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