Toward Precision Medicine: A Cancer Molecular Subtyping Nano-Strategy for RNA Biomarkers in Tumor and Urine: Beyond the Abstract

In recent years, there is overwhelming evidence that cancer histological subtypes comprises of a complex series of intricate molecular subtypes which require different treatment strategies.1 For instance, prostate cancer (PCa) is a heterogeneous disease comprising of both clinically significant (aggressive and lethal) and insignificant (slow-growing and non-life threatening) subtypes.

The current single PSA biomarker test, on its own, is inadequate in discriminating between these different PCa subtypes, thus leading to unnecessary medical procedures such as biopsies and prostatectomies. Therefore, the detection of multiple oncogenic PCa biomarkers is required for accurate patient subtyping/profiling2 and effective tailored treatment (i.e., precision medicine) (Figure 1). Multiplexed assays are required for the identification of multiple aberrations but current multiplexed strategies are limited by: (i) time-consuming and complex assay protocols; (ii) difficulty in interpreting broad overlapping spectral peaks of conventional fluorescence readouts; and (iii) high assay costs which impede widespread usage. 

In this study, we have developed a novel nano-subtyping platform3 for rapid multiplexed detection of PCa biomarkers, while addressing the limitations of current methodologies. A panel of five promising RNA biomarker targets for PCa subtyping and risk stratification were chosen in this study. These include the two most common TMPRSS2:ERG gene fusion variants4: TMPRSS2 exon 1-ERG exon 4 (T1E4) and TMPRSS2 exon 1-ERG exon 5 (T1E5); PCA3;5 ARV7;6 and an endogenously-expressed housekeeping RNA (RN7SL1). In our approach, RNA is extracted from samples before a five-plexed isothermal reverse transcription-recombinase polymerase amplification (RT-RPA) of biomarker targets and finally, surface-enhanced Raman spectroscopy (SERS) to both identify (unique spectral peak) and quantify (peak intensity) the target biomarkers. 

Our approach is two times faster (80 min sample-to-answer time) than current techniques and could detect as little as 200 zmol (100 copies) of RNA targets. The potential for clinical translation was demonstrated by profiling PCa patient clinical samples such as tissue biopsy and urine specimens. This is the first translational application of a RT-RPA/SERS-based platform for multiplexed cancer biomarker detection to address a clinical need. 

The genetic subtyping of PCa is still an evolving field today. While this method was developed with the above-stated biomarkers as model targets, this approach could be readily-tailored to accommodate newly-discovered biomarkers in the future. Nonetheless, given its current performance, the proposed strategy could aid in providing more timely and effective tailored-made therapy plans for each individual cancer patient. The rapid turnover of the assay also suggests a possible application in monitoring treatment response whereby constant and precise biomarker interrogation is required. We believe that as ongoing PCa genetic profiling work matures, our contribution could be a platform strategy for enabling precision medicine. 




Written by: Kevin M. Koo1, Eugene J.H. Wee1*, Paul N. Mainwaring1, Yuling Wang1*, Matt Trau1, 2* 

¹Centre for Personalized Nanomedicine, Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, QLD 4072, Australia
²School of Chemistry and Molecular Biosciences, The University of Queensland, QLD 4072, Australia 

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