In this proposed research, we will develop a lipid nanoprobe (LNP) integrated microdevice, LiEVchip, for isolation of extracellular vesicles (EVs) from blood plasma of patients with non-small cell lung cancer (NSCLC). The proposed LiEVchip features high-throughput sample processing, one-step enrichment, and low cost. It is expected to isolate EVs from 1 ml of unprocessed plasma in 20 minutes with over 80% isolation efficiency. Furthermore, combination with duplex sequencing based ultrasensitive DNA mutation detection platform, the LiEVchip will significantly prompt EV-based cancer diagnostics in an invasive way. In our previous study, we developed a two-component LNP system for rapid EV isolation and comprehensively EV molecular analyses. Particularly, we successfully identified EV DNA mutations from four patients with advanced NSCLC. The LNP system overcomes low throughput, low purity and other common shortcomings in EV isolation, showing great potential for clinical use. Hence, we proposed to develop a highly integrated one- component LiEVchip for rapid and efficient EV isolation. Firstly, we will design and fabricate the proposed LiEVchip. The LiEVchip integrates the LNP to capture EVs based on their lipid membrane envelope. The EV isolation efficiency is boosted by the design of microchannel curvature to enhance flow-surface interaction by Dean flow, and the empowerment of electrokinetic enhanced EV isolation by the nanoelectrode array. Then, we will optimize its operational parameters to make a balance between EV isolation efficiency and purity. After comprehensive optimization, we will rigorously validate its performance with spike samples by analyzing EV content, including RNA, DNA, and proteins, and compare with those isolated by the prevalent EV isolation method, OptiPrep density gradient ultracentrifugation (odgUC). Subsequently, we will develop duplex sequencing based DNA mutation detection method with 3rd generation high-throughput sequencer (PacBio). The detection sensitivity of point/deletion mutations and complex structural variations (SVs) will be validated with spiked-in samples. Finally, in a cohort clinical study, we will first recruit 40 NSCLC patients at stage IV to validate the overall technology. EV from plasma will be isolated with LiEVchip, and a panel of 20 most common NSCLC mutated genes will be assayed simultaneously by duplex sequencing. We will further perform EV isolation and duplex sequencing in the additional 120 samples covering stage I-III NSCLC to investigate the potential of this technology in early NSCLC diagnosis. Besides, we will use the developed technology to monitor mutation status of 20 NSCLC patients undergoing targeted therapy to explore its clinical utility in treatment monitoring. The cohort clinical studies not only can testify whether LiEVchp combined with duplex sequencing can be routinely applied to detect diverse malignancies in NSCLC, but also can demonstrate the clinical diagnostic values of EV DNA. Altogether, the successful completion of this proposed project will pave the way for clinical translation of EV diagnostics.

Public Health Relevance

A lipid nanoprobe integrated microdevice, LiEVchip, will be developed and rigorously validated toward large- scale clinical implementation for one-step rapid isolation of extracellular vesicles (EVs) from blood plasma. Combination with duplex sequencing based ultrasensitive DNA mutation detection assay, the LiEVchip will be able to identify mutations from EV derived DNA in patients with non-small cell lung cancer. The successful completion of this proposed study will not only demonstrate the diagnostic value of EV derived DNA but also pave the way for EV-based cancer diagnostics.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
7R01CA230339-02
Application #
9993821
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Ossandon, Miguel
Project Start
2018-08-06
Project End
2023-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Carnegie-Mellon University
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
052184116
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213