The Dual-Response-Single-Amplification Fluorescent Nanomachine for Tumor Imaging and Gastric Cancer Diagnosis

Gastriccancer (GC) is one of the most common tumors worldwideand is the leading cause of tumor-related mortality. Traditional biomarkersand screening methods cannot meet the clinical demands. There is anurgent need for highly sensitive diagnostic markers as well as accuratequantification methods for early gastric cancer (EGC) screening. Herea dual-target cooperatively responsive fluorescent nanomachine bythe innovative application of two targets responsive strandmigration system with a single-amplification-cycle element was developedfor the simultaneous detection of GC biomarkers miR-5585-5p and PLS3mRNA, which were selected by next-generation sequencing and RT-qPCR.It was also an RNA extraction-free, PCR-free, and nonenzymatic biosensorto achieve tumor cell imaging and serum diagnosis. Requiring onlya 20 & mu;L serum sample and 20 min incubation time, the nanomachineachieved an ultrasensitive detection limit of fM level with a broadlinear range from fM to nM. More importantly, a higher AUC value (0.884)compared to the clinically used biomarker CA 72-4 was obtained bythe nanomachine to distinguish GC patients successfully. Notably,for the key concerns of diagnosis of EGC patients, the nanomachinealso achieved a satisfactory AUC value of 0.859. Taken together, thiswork has screened and obtained multiple biomarkers and developed afluorescent nanomachine for combination diagnosis of GC, providingan ingenious design of a functionalized DNA nanomachine and a feasiblestrategy for the transformation of serum biomarkers into clinicaldiagnosis.

Automated summary

Gastric cancer (GC) is a common and deadly tumor, and better diagnostic markers and methods are needed. This study developed a fluorescent nanomachine that can detect GC biomarkers miR-5585-5p and PLS3mRNA with high sensitivity. It is a PCR-free biosensor that allows tumor cell imaging and serum diagnosis. The nanomachine achieved ultrasensitive detection and performed better than clinically used biomarkers in distinguishing GC patients.