B-211 Quantum dot-DNA nanocomposite enhanced single-molecule flow (SiM-Flow) for ultrasensitive microRNA detection in metastatic castrate-resistant prostate cancer

Abstract

Abstract Background MicroRNAs (miRs) like miR-375 and miR-1290 are associated with cancer progression and chemoresistance in metastatic castrate-resistant prostate cancer (mCRPC). However, these prognostic biomarkers are typically present in low abundance (0.1∼1 fM) in patient plasma, which is close to the detection limit of the current gold standard techniques, quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). Therefore, we tested a nanomaterial that incorporates quantum dots (QDs) and DNA amplicons for enhanced in-solution counting applications in plasma from a cohort of mCRPC patients. The QD-DNA nanocomposite increases the fluorescent intensity of an individual amplicon for ultrasensitive flow-counting and provides higher multiplex capacity due to the narrow emission band of QD for simple instrumentation. Methods QDs were synthesized with spectrally distinct emission bands by tuning the size or composition of CdSe core. QDs were then coated with multidentate polymer allowing further bioconjugations and better solubility in aqueous solution. The oligonucleotides complementary to amplicons generated from selected miR targets (prognostic biomarkers: miR-1290 and miR-375; normalization biomarkers: miR-16, miR-30a-5p, and cel-39) were then conjugated to QDs with optimized ratio. Total RNA was extracted from a screening cohort of 14 mCRPC patients from Huntsman Cancer Institute where platelet-poor plasma was uniformly processed with exogenous spike-in, cel-39, added in. qRT-PCR was performed using TaqMan miRNA assays, and SiM-Flow was conducted using a commercial flow cytometry to count QD barcoded enzymatic-extended miRs nanoparticles. The DNA template used for extending miRs was designed by our lab and purchased from IDT-DNA. Pearson correlation and interclass agreement analysis were applied to evaluate the concordance between the two assays. The mCRPC cohort was followed for clinical outcomes, and survival analysis for the time of progression from mCRPC to death/last follow-up was performed to determine the prognostic value of the QD-DNA nanoparticle counts. The Cox proportional hazards model was applied to linearly incorporate multiple hazard factors of patients for multivariate survival analysis. Results We demonstrated the multiplex ability of QDs with less than 5% false positive rate. The machine learning-guided optimized assay shows a 1000-time improved limit of detection of assay compared to the published literature. Interclass agreement > 0.9 and Pearson correlation of 0.94 between SiM-Flow and RT-qPCR on human plasma extracts suggest high specificity of SiM-Flow on miR detection. Also, miR-375 was identified among all the samples through SiM-Flow, although it was unidentified by qRT-PCR in 14 samples. Higher levels of miR-1290, miR-375, and prostate-specific antigen were significantly associated with poor overall survival (p=0.019) in the initial survival analysis. Survival analysis replication is ongoing in an independent mCRPC cohort. Conclusions SiM-Flow was able to detect target miRs in mCRPC patients’ plasma with a high agreement with qRT-PCR and lower detection limit and demonstrated multiplex ability with a simple optical set-up. This shows technological advancement in the detection of cancer-associated biomarkers and will aid in precision medicine therapeutic and point-of-care applications with both prognostic and predictive potential.