RNA Biomarkers: Diagnostic and Prognostic Potentials and Recent Developments of Electrochemical Biosensors

Md Nazmul Islam, Mostafa Kamal Masud, Md Hakimul Haque, Md Shahriar Al Hossain, Yusuke Yamauchi, Nam-Trung Nguyen, Muhammad J. A. Shiddiky

    Research output: Contribution to journalArticlepeer-review


    Ribonucleic acids (RNAs) are considered as effective and minimally invasive biomarkers for disease diagnosis and prognosis due to their critical role in the regulation of different cellular processes. Over the past several years, the rapid progress in RNA biomarker research has resulted in the development of a large number of high‐performance RNA‐detection methods. Most of these methods are based on molecular‐biology techniques such as quantitative reverse transcription polymerase chain reaction (RT‐qPCR), microarrays, and RNA sequencing. In recent years, considerable attention has also been dedicated to developing RNA biosensors, exploiting micro‐ and nanofabrication technologies, and various readout strategies, including electrochemical and optical transducers. Here, the recent developments of RNA biosensors are concisely reviewed with a special emphasis on electrochemical‐detection approaches. The following points are also highlighted: i) all the types of clinically relevant RNAs (mRNAs, miRNAs, lncRNAs) and their diagnostic and prognostic potential in cancer are outlined, ii) major challenges associated with current techniques are identified, followed by a critical analysis of how these challenges have been addressed by different biosensing approaches, and iii) the current requirements that still need to be met for effective screening of RNA biomarkers in both research and clinical settings.
    Original languageEnglish
    Article number1700131
    JournalSmall Methods
    Issue number7
    Early online date5 Jun 2017
    Publication statusPublished - 6 Jul 2017


    Dive into the research topics of 'RNA Biomarkers: Diagnostic and Prognostic Potentials and Recent Developments of Electrochemical Biosensors'. Together they form a unique fingerprint.

    Cite this