Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis

Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis

RSC Advances

10.1039/d3ra05723b

http://dx.doi.org/10.1039/d3ra05723b

Shuyan Zhang, Steve Qing Yang Wu, Melissa Hum, Jayakumar Perumal, Ern Yu Tan, Ann Siew Gek Lee, Jinghua Teng, U. S. Dinish, Malini Olivo

23 January 2024

Zhang, S., Wu, S. Q. Y., Hum, M., Perumal, J., Tan, E. Y., Lee, A. S. G., Teng, J., Dinish, U. S., & Olivo, M. (2024). Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis. RSC Advances, 14(5), 3599–3610. https://doi.org/10.1039/d3ra05723b

With the multi-modal approach combining ATR-FTIR and SERS, we achieved an extended spectral range for molecular fingerprint detection of RNA biomarkers. Machine learning results shows 91.6% blind test accuracy for label-free breast cancer diagnosis.

Attribution 4.0 International (CC BY 4.0)

This research / project is supported by the Agency for Science, Technology and Research, Singapore - IAF-PP
Grant Reference no. : H19H6a0025

This research / project is supported by the National Medical Research Council - Cooperative Basic Research Grant
Grant Reference no. : NMRC/CBRG/0087/2015

This research / project is supported by the BMRC - UIBR Grant
Grant Reference no. : N.A

NA

https://oar.a-star.edu.sg/communities-collections/articles/20062

2046-2069

Skin Research Lab