MicroRNAs: The next generation of cancer biomarkers
Adeel Khan 1, 2 *, Haroon Khan 3, Fizza Mehwish 1, Osama Alam 1, Muhammad Irfan Khan 1, Ahmad Ullah 1, Syed Atiq 4, Mushtaq Ahmad 1 *
1 Department of Biotechnology, University of Science & Technology Bannu 28100, Khyber Pakhtunkhwa, Pakistan
2 School of Biological Science and Medical Engineering, Southeast University, Nanjing 210000, China
3 Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai,20030, China
4 Department of Chemistry, University of Science & Technology Bannu,28100 Khyber Pakhtunkhwa, Pakistan
Abstract
MicroRNAs (miRNAs) are a class of small, non-coding RNA molecules that have been shown to be involved in a wide range of biological processes, including cancer. miRNAs are known to regulate the expression of genes, and their dysregulation has been linked to the development of cancer. In recent years a great deal of attention is received by miRNAs due to their potential as biomarkers for cancer. Biomarkers are measurable indicators of a biological state, and they can be used to diagnose, monitor, and treat diseases. miRNAs can be detected in biological fluids such as blood and saliva. This makes them ideal candidates for early cancer detection and monitoring. We herein reviewed current methods for the isolation of circulating miRNAs. Provide the most recent update about clinical trials aiming at using miRNAs as biomarkers for cancer. Additionally, we highlighted some pitfalls that should be realized to take advantage of the massive potential of miRNAs as a cancer biomarker. However, the potential of miRNAs as cancer biomarkers is very promising but advancements in factors such as miRNA isolation methods, and the type of samples are critical to incorporate miRNA-based diagnostic and prognostic markers in modern-day treatment regimens for cancer. This review concludes that miRNAs have enormous clinical significance as cancer biomarkers and recommends carefully selecting methods for the isolation of miRNAs based on the type of sample, and the downstream applications to generate clinically relevant results.