DNA-framework-based multidimensional molecular classifiers for cancer diagnosis.

A molecular classification of diseases that accurately reflects clinical behaviour lays the foundation of precision medicine. The development of in silico classifiers coupled with molecular implementation based on DNA reactions marks a key advance in more powerful molecular classification, but it nevertheless remains a challenge to process multiple molecular datatypes. Here we introduce a DNA-encoded molecular classifier that can physically implement the computational classification of multidimensional molecular clinical data. To produce unified electrochemical sensing signals across heterogeneous molecular binding events, we exploit DNA-framework-based programmable atom-like nanoparticles with n valence to develop valence-encoded signal reporters that enable linearity in translating virtually any biomolecular binding events to signal gains. Multidimensional molecular information in computational classification is thus precisely assigned weights for bioanalysis. We demonstrate the implementation of a molecular classifier based on programmable atom-like nanoparticles to perform biomarker panel screening and analyse a panel of six biomarkers across three-dimensional datatypes for a near-deterministic molecular taxonomy of prostate cancer patients.

Programming bulk enzyme heterojunctions for biosensor development with tetrahedral DNA framework.

Protein-protein interactions are spatially regulated in living cells to realize high reaction efficiency, as seen in naturally existing electron-transfer chains. Nevertheless, arrangement of chemical/biochemical components at the artificial device interfaces does not possess the same level of control. Here we report a tetrahedral DNA framework-enabled bulk enzyme heterojunction (BEH) strategy to program the multi-enzyme catalytic cascade at the interface of electrochemical biosensors. The construction of interpenetrating network of BEH at the millimeter-scale electrode interface brings enzyme pairs within the critical coupling length (CCL) of ~10 nm, which in turn greatly improve the overall catalytic cascade efficiency by ~10-fold. We demonstrate the BEH generality with a range of enzyme pairs for electrochemically detecting clinically relevant molecular targets. As a proof of concept, a BEH-based sarcosine sensor enables single-step detection of the metabolic biomarker of sarcosine with ultrasensitivity, which hold the potential for precision diagnosis of early-stage prostate cancer.

Valency-Controlled Framework Nucleic Acid Signal Amplifiers.

Weak ligand-receptor recognition events are often amplified by recruiting multiple regulatory biomolecules to the action site in biological systems. However, signal amplification in in vitro biomimetic systems generally lack the spatiotemporal regulation in vivo. Herein we report a framework nucleic acid (FNA)-programmed strategy to develop valence-controlled signal amplifiers with high modularity for ultrasensitive biosensing. We demonstrated that the FNA-programmed signal amplifiers could recruit nucleic acids, proteins, and inorganic nanoparticles in a stoichiometric manner. The valence-controlled signal amplifier enhanced the quantification ability of electrochemical biosensors, and enabled ultrasensitive detection of tumor-relevant circulating free DNA (cfDNA) with sensitivity enhancement of 3-5 orders of magnitude and improved dynamic range.

DNA Tetrahedral Nanostructure-Based Electrochemical miRNA Biosensor for Simultaneous Detection of Multiple miRNAs in Pancreatic Carcinoma.

Specific and sensitive biomarker detection is essential to early cancer diagnosis. In this study, we demonstrate an ultrasensitive electrochemical biosensor with the ability to detect multiple pancreatic carcinoma (PC)-related microRNA biomarkers. By employing DNA tetrahedral nanostructure capture probes to enhance the detection sensitivity as well as a disposable 16-channel screen-printed gold electrode (SPGE) detection platform to enhance the detection efficiency, we were able to simultaneously detect four PC-related miRNAs: miRNA21, miRNA155, miRNA196a, and miRNA210. The detection sensitivity reached to as low as 10 fM. We then profiled the serum levels of the four miRNAs for PC patients and healthy individuals with our multiplexing electrochemical biosensor. Through the combined analyses of the four miRNAs, our results showed that PC patients could be discriminated from healthy controls with fairly high sensitivity. This multiplexing PCR-free miRNA detection sensor shows promising applications in early diagnosis of PC disease.