# Smartphone-based mobile detection platform for lung cancer detection in China

> **NIH NIH K01** · UNIVERSITY OF PENNSYLVANIA · 2020 · $105,580

## Abstract

ABSTRACT
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
c...

## Key facts

- **NIH application ID:** 10018939
- **Project number:** 5K01TW011190-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Jinzhao Song
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $105,580
- **Award type:** 5
- **Project period:** 2019-09-16 → 2021-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10018939

## Citation

> US National Institutes of Health, RePORTER application 10018939, Smartphone-based mobile detection platform for lung cancer detection in China (5K01TW011190-02). Retrieved via AI Analytics 2026-08-17 from https://api.ai-analytics.org/grant/nih/10018939. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*