Lung cancer is the leading incident cancer and cause of cancer death in China. In the next five years, attributed to air pollution and high tobacco consumption, China will likely see an increase in the occurrence of lung cancer with an estimated of over 800,000 new diagnoses and 700,000 deaths per year. Although affordable cancer genotype-specific drugs are increasingly available in China, effective and affordable diagnostics of cancer genotypes is lacking. To address this critical need, I propose a novel inexpensive, point-of-care smartphone-based system for detecting rare mutant alleles in body fluids to enable liquid biopsy of lung cancer in rural China. The proposed system builds on my prior work with minimally instrumented and un-instrumented molecular diagnostics. My system will accept a raw sample, such as whole blood, process the sample, and provide rapid test results. Since the presence of a large abundance of wildtype (WT)-allele challenges detection of rare mutant alleles, my system will include a sample enrichment step that utilizes DNA guided cleaving enzymes of the Argonaute family to digest and deplete WT alleles while sparing the mutant alleles of interest. This will be followed with a loop mediated isothermal amplification (LAMP) that utilizes peptide nucleic acid (PNA) clamp to selectively amplify mutant alleles, but not WT-alleles. For multiplex detection of mutant alleles, the proposed system will firstly enrich the sample with the programmable cleaving enzyme and then subject the enriched sample to a novel two stage, multiplexed isothermal amplification process (Penn-RAMP), in the case of point/deletion/insertion mutations, with PNA clamps to discourage amplification of WT alleles in Penn-RAMP's second stage. Amplicons will be detected with bioluminescent reporters and a smartphone camera. A custom smartphone application will analyze the recorded signal; report test results; and, in the future, transmit these results to the patient's doctor and records and, in de-identified form, to the cloud for spatiotemporal surveillance, allowing public health officials identify hotspots. Our preliminary data indicates that our approach has high likelihood of success. I have developed a training plan in the following three areas: cancer epidemiology, cancer diagnostics and therapy, and medical device design and fabrication. In each of these areas, I have identified coursework and mentorship support from members of the K01 Advisory Committee. The Advisory Committee composed of internationally recognized experts in engineering, cancer epidemiology, lung cancer precision medicine, liquid biopsy, and microbiology has been assembled and will meet periodically to assess my progress and provide guidance. This research has the potential to greatly improve companion diagnosis and screening of lung cancer in China and enable effective therapies. The program will enable me to obtain new skills through field work, research, coursework, and collaborations, all of which will promote and accelerate my transition to an independent investigator for global health.

Public Health Relevance

Lung cancer is the leading incident cancer and cause of cancer death in China. While affordable lung cancer targeted drugs are rapidly becoming available in China, cancer genotyping is limited to select centralized facilities with limited capacity and is unavailable in most of China. This project will develop an inexpensive Smartphone-based mobile platform for detecting rare mutant alleles in blood samples for lung cancer patients, enabling personalized therapy, monitoring evolution of drug resistance, improving outcomes, and reducing cost.

Agency
National Institute of Health (NIH)
Institute
Fogarty International Center (FIC)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
1K01TW011190-01A1
Application #
9889486
Study Section
International and Cooperative Projects - 1 Study Section (ICP1)
Program Officer
Povlich, Laura
Project Start
2019-09-16
Project End
2024-06-30
Budget Start
2019-09-16
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104