Over the past several years, the human transcriptome has been repeatedly interrogated, and with the recent breakthrough in sequencing technologies, ribonucleic acids (RNAs) comprising different coding and noncoding transcripts, such as messenger RNA (mRNA), microRNA (miRNA), and long-noncoding RNA (lncRNA), are becoming progressively crucial for revolutionising personalised cancer management. Improved diagnostics, prognostics and streamlined therapeutic potentiality makes them an excellent choice as biomarkers. Non-coding RNAs are key regulators of the gene expression network and are involved in the control of a range of important cellular pathways, such as cell cycle, cell proliferation, differentiation, apoptosis, and post-transcriptional regulation. Abnormalities in the expression of these RNAs can affect one or several of these cellular pathways, which might contribute towards initiation and progression of cancer. Despite recent advances in RNA-based fundamental research, their detection approaches are largely confined to laboratory-based molecular biology techniques, such as quantitative reverse transcription polymerase chain reaction (RT-qPCR), microarrays, and RNA sequencing. Although the analytical performance and reliability of these methods are excellent, most of these methods require enzymatic amplification, cumbersome sample pre-treatment, multi-step assay protocol, high maintenance cost, and technical expertise. The development of a simple, sensitive, and low cost method that can be used for rapid detection of RNA biomarkers for a meaningful clinical application at the time and place of patient care (i.e., point-of-care) is of great importance to clinical and translational research. This PhD project endeavours to engineer such translational approaches to circumvent the aforementioned challenges for developing an inexpensive, sensitive, specific, and portable biosensor platform. This thesis initially studies the biogenesis, diagnostic, and prognostic potential of RNA biomarkers followed by a comprehensive appraisal of recent progress in the development of RNA biosensors with a special emphasis on electrochemical-detection approaches. We then report on the development of a biosensing platform consisting of four novel readout schemes for the simple, rapid, and inexpensive analysis of various RNA biomarkers (i.e., mRNAs, miRNAs and lncRNAs). First, employing the nucleotides’ affinity towards gold, we developed an amplification-free electrochemical assay for the detection of tumour-specific mRNAs. This straightforward sensor adopted differential pulse voltammetry to enable the readout using simple direct adsorption of magnetically isolated analytes on unmodified disposable electrodes. Subsequent to the development of this proof of concept sensor, we attempted to address the increasing demand for detecting the ultralow levels of RNAs from the complex biological sample via introducing two novel readout strategies for detecting miRNAs. Utilising the coupling of electrocatalytic strength of two in-house synthesised porous graphene oxide-loaded iron oxide (GO/IO hybrid material), gold-loaded nanoporous ferric oxide nanocubes (Au-NPFe2O3NC), and [Ru(NH3)6]3+/[Fe(CN)6]3- electrocatalytic cycle, two ultrasensitive assays were reported, where the detection was achieved by chronocoulometric (CC) charge measurement of surface bound cationic [Ru(NH3)6]3+, which was electrostatically attached to the anionic phosphate backbone of target RNAs. In our final readout strategies, we extended our approach towards a translational- focused assay platform which enabled naked-eye, colorimetric and electrochemical interrogation of lncRNA via 3,3′,5,5′-tetramethylbenzidine (TMB)/Horseradish peroxidase (HRP)-based colorimetric assay. All of the readout platforms reported herein have shown excellent analytical performance with high sensitivity (LOD for mRNA and miRNA = picomolar to attomolar level, LOD for lncRNA = single cell approaching) and specificity. The applicability of the assays was also demonstrated in complex biological samples (a cohort of cancer cell lines and patient samples) with high reproducibility. The analytical performance of the assays was also validated with the standard RT-qPCR approach. We believe that our research efforts will lead to the development of a translational-focused point-of-care platform for RNA analysis, which in turn will not only hold the potential to improve patient care and outcomes but might also prove to be a venture of immense commercial significance.