Paper-Microfluidic Platform with Cloud-Based Capillary Flow Analysis for Detection of HPV 16 DNA Towards Oropharyngeal Cancer Screening
Human papillomavirus (HPV) is an oncogenic virus that can lead to the development of many different types of cancers, including oropharyngeal cancer (OPC). While HPV is not the sole cause of OPC, it does account for the majority of cases, and HPV-positive OPC cases are predicted to continue rising in the future. While several HPV-positive OPC detection methods have been developed, all have limitations in ease of use, portability, and assay time, often lacking specificity and/or sensitivity. This work showcases capillary flow analysis on paper microfluidic platforms, combined with smartphone- and cloud-based detection, to rapidly identify HPV 16 amplicons. HPV template DNA was amplified using recombinase polymerase amplification (RPA), an isothermal method that achieves exponential amplification in 20 minutes with a low reaction temperature of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$39^{\circ} \mathrm{C}$</tex>. A smartphone captured a video clip as the samples flowed through wax-printed paper microfluidic channels. Amine-functionalized microspheres with diameters of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.5 \mu ~\mathrm{m}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.0 \mu ~\mathrm{m}$</tex> were preloaded onto the chips to boost the flow velocity differences between the no-target control (NTC) and HPV samples. Capillary flow velocities were automatically analyzed in a cloud using custom Python code. The initial slopes of the flow velocity profiles and the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.0 \mu ~\mathrm{m}$</tex> microspheres showed the maximum differences between NTC and HPV samples and between the amplicons of varied lengths.
Authors
- Jeong‐Yeol Yoon (ORCID: https://orcid.org/0000-0002-9720-6472)
- Bofan Song (ORCID: https://orcid.org/0000-0002-1171-8478)
- Rongguang Liang (ORCID: https://orcid.org/0000-0003-2792-3457)
- Reid S. Loeffler
- Cho Lik Chan
- Darya Pershina
Institutions
- University of Arizona (US)
Publication Details
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1109/hi-poct64255.2024.10876197
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00