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I-Corps: Rapid Ultrasensitive Biodetection Chip for Early Lung Cancer Diagnosis

$50,000FY2023TIPNSF

University Of Texas At Austin, Austin TX

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is the development of a rapid, ultrasensitive biomarker detection chip for applications in early lung cancer diagnosis. Lung cancer is the leading cause of cancerous deaths. This cancer claimed approximately 150,000 lives in the US in 2016, accounting for 25 percent of all cancer deaths. This disease is perilous due to the difficulties in its early-stage diagnosis and poor five-year survival rate (18%). Nevertheless, if detected early, the five-year survival rate can dramatically improve to 56%. Indeed, there is a dire need to develop user-friendly and low-cost, early-stage, lung-cancer diagnosis techniques based on simple body fluids, such as blood, saliva, and urine, for integration into regular wellness checks. In meeting this demand, this project seeks to develop a robust and portable cancer biomarker detection platform for early-stage lung cancer diagnosis from simple bodily fluids. This I-Corps project is based on the development of an on-chip lung-cancer biomarker detection platform. Currently, the use of biomarker sensing is intrinsically difficult for both ultra-sensitivity and high speed in detecting biomarkers in fluidic samples. To overcome this challenge, a light-pinpointed biomolecule concentrating technology that allows for simultaneous focusing and detection of biomarkers has been developed. The proposed technology may enable high fidelity and accuracy in diagnosing lung cancer at an early stage using simple bodily fluids, such as blood and saliva, during a regular wellness check. In addition, this diagnostic method may accelerate applications of nanobiosensing in practical, early-stage cancer diagnoses. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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