Jing Wang1, Kevin M. Koo1, Eugene J. H. Wee1, Yuling Wang3,* and Matt Trau1,2,*

 

1Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
2School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD, Australia
3
Department of Chemistry and Biomolecular Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia

 

Simple nucleic acid detection could facilitate the progress of disease diagnostics for clinical uses. Whilst methods such as reverse transcription-polymerase chain reaction (RT-PCR) or next generation sequencing (NGS) are typically used for nucleic acid detection, simpler and more cost-efficient methods are on high demand, which could facilitate the progress of disease diagnostics, particularly in cancer subtyping. Label-free surface-enhanced Raman scattering (SERS) is one potential strategy. However, current label-free SERS approaches for DNA/RNA biomarker detection are still limited to short and synthetic nucleic acid targets and require large quantities of starting materials. To resolve these limitations and enable label-free SERS for clinical applications (clinical samples are of limited quantities and target DNA/RNA are typically in trace amounts), we herein present a proof-of-concept strategy for non-invasive subtyping of prostate cancer (PCa) by a combination of multiplex reverse transcription-recombinase polymerase amplification (RT-RPA) to enrich for multiple specific RNA biomarkers, followed by label-free SERS aided by multivariate statistical analysis to identify and distinguish between multiple long (~200 bp) sequences. In a modest sample size of 43 urinary samples, we could subtype the samples with 95.3% sensitivity, 93.0% specificity, and 94.2% accuracy. We believe that our proposed assay could pave the way for simple and direct label-free SERS detection of multiple long nucleic acid sequences in patient samples, and thus facilitate rapid cancer molecular subtyping for personalized therapies.

References

Wang, J.; Koo, K. M.; Wee, E. J.; Wang, Y.; Trau, M., Nanoscale 2017, 9, 3496-3503.

Biographic Details

Name: Jing Wang
Title: Ms
Affiliation, Country: Centre for Personalised Nanomedicine, Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
Phone: 0410898505 E-mail: jing.wang14@uq.net.au
Research interests: Biomedicine, SERS, Nanoparticle characterization