Tumor cells are known to shed nano-scale objects called circulating microvesicles (C?Vs) into patients'blood. These C?Vs have been shown to carry molecular information from the tumor, which can potentially be used to diagnose and monitor cancer using only a blood test. However, due to their extremely small size (d ~ 50 nm), there has not been a clinically viable method to detect and profile these C?Vs. To address these challenges, we propose a microchip-based platform that can quantitatively profile C?Vs directly in unprocessed whole blood. On this chip, we harness the small feature size of microelectronics and combine it with the biocompatibility of microfluidics and magnetic nanoparticles (MNPs) to measure these nano-scale objects. Our proposed device is handheld and aims to reduce measurement times from several hours using conventional equipment to less than thirty minutes. Moreover, due to the high sensitivity of our micro-magnetic sensing method, the biomarker specific limit of detection (100 C?V/mL) will exceed that of conventional techniques. This innovative, clinically practical approach to C?V detection has great potential for non-invasive, routine monitoring of disease progression, drug efficacy, and metastasis, offering tremendous benefits for patients.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA182336-01A1
Application #
8733954
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Sorbara, Lynn R
Project Start
2014-09-01
Project End
2017-07-31
Budget Start
2014-09-01
Budget End
2015-07-31
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Ko, J; Hemphill, M; Yang, Z et al. (2018) Diagnosis of traumatic brain injury using miRNA signatures in nanomagnetically isolated brain-derived extracellular vesicles. Lab Chip 18:3617-3630
Ko, Jina; Baldassano, Steven N; Loh, Po-Ling et al. (2018) Machine learning to detect signatures of disease in liquid biopsies - a user's guide. Lab Chip 18:395-405
Jeong, Heon-Ho; Yadavali, Sagar; Issadore, David et al. (2017) Liter-scale production of uniform gas bubbles via parallelization of flow-focusing generators. Lab Chip 17:2667-2673
Liu, Jessica F; Yadavali, Sagar; Tsourkas, Andrew et al. (2017) Microfluidic diafiltration-on-chip using an integrated magnetic peristaltic micropump. Lab Chip 17:3796-3803
Ko, Jina; Bhagwat, Neha; Yee, Stephanie S et al. (2017) A magnetic micropore chip for rapid (<1 hour) unbiased circulating tumor cell isolation and in situ RNA analysis. Lab Chip 17:3086-3096
Ko, Jina; Carpenter, Erica; Issadore, David (2016) Detection and isolation of circulating exosomes and microvesicles for cancer monitoring and diagnostics using micro-/nano-based devices. Analyst 141:450-460
Ko, Jina; Yelleswarapu, Venkata; Singh, Anup et al. (2016) Magnetic Nickel iron Electroformed Trap (MagNET): a master/replica fabrication strategy for ultra-high throughput (>100 mL h(-1)) immunomagnetic sorting. Lab Chip 16:3049-57
Ko, Jina; Hemphill, Matthew A; Gabrieli, David et al. (2016) Smartphone-enabled optofluidic exosome diagnostic for concussion recovery. Sci Rep 6:31215
Magaraci, Michael S; Bermudez, Jessica G; Yogish, Deeksha et al. (2016) Toolbox for Exploring Modular Gene Regulation in Synthetic Biology Training. ACS Synth Biol 5:781-5
Jeong, Heon-Ho; Yelleswarapu, Venkata R; Yadavali, Sagar et al. (2015) Kilo-scale droplet generation in three-dimensional monolithic elastomer device (3D MED). Lab Chip 15:4387-92

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