Electrical Cartridge Sensor Enables Reliable and Direct Identification of MicroRNAs in Urine of Patients.
Seongchan KimSungwook ParkYoung Soo ChoYounghoon KimJong Hyun TaeTae Il NoJi Sung ShimYoungdo JeongSeok Ho KangKwan Hyi LeePublished in: ACS sensors (2020)
Urinary miRNAs are biomarkers that demonstrate considerable promise for the noninvasive diagnosis and prognosis of diseases. However, because of background noise resulting from complex physiological features of urine, instability of miRNAs, and their low concentration, accurate monitoring of miRNAs in urine is challenging. To address these limitations, we developed a urine-based disposable and switchable electrical sensor that enables reliable and direct identification of miRNAs in patient urine. The proposed sensing platform combining disposable sensor chips composed of a reduced graphene oxide nanosheet and peptide nucleic acid facilitates the label-free detection of urinary miRNAs with high specificity and sensitivity. Using real-time detection of miRNAs in patient urine without pretreatment or signal amplification, this sensor allows rapid, direct detection of target miRNAs in a broad dynamic range with a detection limit down to 10 fM in human urine specimens within 20 min and enables simultaneous quantification of multiple miRNAs. As confirmed using a blind comparison with the results of pathological examination of patients with prostate cancer, the sensor offers the potential to improve the accuracy of early diagnosis before a biopsy is taken. This study holds the usefulness of the practical sensor for the clinical diagnosis of urological diseases.
Keyphrases
- label free
- loop mediated isothermal amplification
- prostate cancer
- nucleic acid
- reduced graphene oxide
- end stage renal disease
- real time pcr
- case report
- endothelial cells
- ejection fraction
- chronic kidney disease
- gold nanoparticles
- air pollution
- artificial intelligence
- prognostic factors
- climate change
- quantum dots
- big data
- deep learning
- patient reported outcomes
- sensitive detection