Logical Analysis of Multiple miRNAs with Isothermal Molecular Classifiers Based on LATE-RCA

Abstract

Logical analysis of multiple-miRNA expression information and immediate output of diagnostic results facilitates early cancer detection. In this work, we constructed an isothermal molecular classifier capable of performing computations on multiple miRNAs and directly providing diagnosis results. First, we developed linear-after-the-exponential rolling circle amplification (LATE-RCA), a nearly linear isothermal amplification that does not destroy the original quantitative information about miRNAs. By designing different numbers of weighted coding sequences on the circular template, we naturally implemented multiplication in the LATE-RCA process. Summation, subtraction, and reporting were then carried out by strand displacement reactions. The entire workflow of the classifier was validated using synthetic gastric cancer and healthy miRNA samples with an accuracy of 100%, demonstrating its robustness and accuracy. Compared with existing molecular classifiers, our approach performs under isothermal conditions, streamlines computational procedures, and simplifies probe design. We believe that this isothermal molecular classifier has promising prospects in personalized precision medicine.