Measuring transfer RNA biomarkers in blood samples may offer a simple, cost-effective, precise alternative to invasive cancer diagnostic and prognostic methods, according to a study published on Thursday in Nature Biotechnology.
The method measures both the abundance and modification of the transfer ribonucleic acid (tRNA) molecules in yeast cells.
Cells naturally modify RNA molecules to enhance their stability, structure, and function. With tRNA, incorrect or missing modifications produce faulty proteins. The dysregulation of tRNA modifications is linked to neurodegenerative diseases, metabolic diseases, and cancer.
Certain tRNA modification profiles exist only in specific cancer types and can serve as highly specific cancer biomarkers. Isolating tRNA molecules from blood samples and quantifying their modifications can potentially help diagnose cancers without imaging tests or invasive biopsies. Furthermore, tRNA modifications vary depending on the state of the disease, providing valuable information about the condition’s prognosis. However, capturing tRNA modification information in a timely, precise, and cost-effective manner has been challenging.
Researchers addressed this challenge by developing a method called Nano-tRNAseq that measures both the abundance and modification of tRNA molecules in a single step. Nano-tRNAseq is based on nanopore sequencing, a technology that directly sequences individual RNA molecules by passing them through a tiny pore. Each of the nucleotides that compose an RNA molecule has a slightly different size and shape, with corresponding changes in the electrical current that occurs as each nucleotide passes through the pore. Computer programs detect changes in the current to identify the sequence of the RNA molecules, including modifications. Researchers contend that, compared to previous methods, Nano-tRNAseq is low-cost, high-throughput, and yields rapid results.
As a proof of concept, the researchers used Nano-tRNAseq to accurately measure tRNA abundance and modifications in samples taken from yeast cells exposed to different environmental conditions. However, while tRNA modification profiles of lower eukaryotic species, including yeast, are well characterized, this is not the case for humans. This highlights one current limitation to the new method: the inability to predict which tRNA modification is dysregulated in a given sample unless the precise modification found in that tRNA has been previously identified using other experimental methods. The researchers hope that, by using Nano-tRNAseq in conjunction with other methods, they will be able to describe the modification profiles of the complete set of human tRNAs, and eventually see Nano-tRNAseq used to identify which changes in tRNAs are associated with a given human disease.
“Nano-tRNAseq is a proof-of-concept technology that paves the way for the development of a simple, cost-effective, and highly precise method that can quantify these molecules in a noninvasive manner,” said senior author Dr. Eva Maria Novoa, a researcher at Spain’s Centre for Genomic Regulation, in a statement. “Our aim is to further develop this technology and combine it with artificial intelligence tools to determine the malignancy of a biological sample in less than three hours, and at a cost of no more than 50 euros per sample.”