Toward Precision Medicine: A Cancer Molecular Subtyping Nano‐Strategy for RNA Biomarkers in Tumor and Urine. Issue 45 (26th September 2016) - Koo, Kevin M.; Wee, Eugene J. H.; Mainwaring, Paul N.; Wang, Yuling; Trau, Matt
Abstract : Cancer is a heterogeneous disease which manifests as different molecular subtypes due to the complex nature of tumor initiation, progression, and metastasis. The concept of precision medicine aims to exploit this cancer heterogeneity by incorporating diagnostic technology to characterize each cancer patient's molecular subtype for tailored treatments. To characterize cancer molecular subtypes accurately, a suite of multiplexed bioassays have currently been developed to detect multiple oncogenic biomarkers. Despite the reliability of current multiplexed detection techniques, novel strategies are still needed to resolve limitations such as long assay time, complex protocols, and difficulty in interpreting broad overlapping spectral peaks of conventional fluorescence readouts. Herein a rapid (80 min) multiplexed platform strategy for subtyping prostate cancer tumor and urine samples based on their RNA biomarker profiles is presented. This is achieved by combining rapid multiplexed isothermal reverse transcription‐recombinase polymerase amplification (RT‐RPA) of target RNA biomarkers with surface‐enhanced Raman spectroscopy (SERS) nanotags for "one‐pot" readout. This is the first translational application of a RT‐RPA/SERS‐based platform for multiplexed cancer biomarker detection to address a clinical need. With excellent sensitivity of 200 zmol (100 copies) and specificity, we believed that this platform methodology could be a useful tool for rapid multiplexed subtyping of cancers. Abstract : Cancer is a heterogeneous disease manifesting as a variety of intricate subtypes, which requires different treatment strategies. Herein a rapid (80 min) multiplexed platform strategy for subtyping prostate cancer tumor and urine samples based on their RNA biomarker profiles is presented. This platform methodology could be a useful cancer subtyping tool for personalized treatment decisions (i.e., precision medicine).