Extracellular RNAs (exRNA) have previously been introduced in plasma and other body fluids as novel biomarkers and potential cell-cell communicators. microRNAs (miRNA) have been involved in a wide variety of illnesses, such as heart failure, cancer, and multiple sclerosis, and are the most researched class of exRNAs to date. miRNA s are small non-coding RNAs that have the capacity to control the transcription and translation of entire gene networks. They are usually observed in extracellular vesicles, bound to lipoproteins, or complexed with Argonaute-2 in the circulation. In vitro studies have also revealed that a variety of cell types are capable of releasing miRNA in these complexes. As a result, exRNA profiling may reflect cellular content and identify disease-specific expression variations. More recently, the use of next-generation sequencing for exRNA discovery has resulted in the discovery that biofluids contain a variety of other RNA species. While not as well studied as miRNAs, new evidence suggests that these other RNA species may play a role in disease as prognostic biomarkers and possible disease mediators.
Figure 1. microRNAs as biofluid markers of urological tumours (Fendler, 2016)
NGS or qPCR are the two platforms used to profile microRNAs in biofluids.
If you want to find new microRNA sequences or learn more about isomiRs or microRNA editing, NGS is the way to go. The most bountiful isomiR for a given microRNA may differ depending on the sample type. NGS has the advantage of being able to detect all isomiRs, whereas traditional microRNA qPCR assays are intended to identify the specific isomiR listed in miRBase as the major sequence for that microRNA, which may or may not be the main isomiR visible in your sample type.
qPCR is appropriate for precise differential expression analysis of a defined set of microRNAs and can be used for miRNome profiling or validation of a subset of microRNAs (which can contain custom qPCR assays designed to identify novel microRNAs or isomiRs).
microRNA profiling in biofluid samples has a lot of potentials, but there are a lot of obstacles to overcome before such experiments can be done successfully. To begin with, biofluids contain very little RNA. This means that standard RNA quality control methods such as Bioanalyzer or OD measurements are ineffective for these samples.
Second, microRNAs detected in biofluids could be cellular or extracellular, and both could be useful for biomarker discovery. CTCs (circulating tumor cells) can be isolated and their cellular microRNA profile studied. Cellular contamination and hemolysis must be avoided if the aim is to evaluate the extracellular microRNA profile of biofluids.
Third, biofluids contain reverse transcriptase and polymerase inhibitors, which can prevent enzymatic reactions in RT-qPCR or library preparation for NGS. Minimizing inhibitor carry-over into the RNA sample, as well as monitoring sample quality, are significant challenges to consider.
Finally, normalization of qPCR data from biofluid samples can be difficult, and selecting controls for normalization should be done with caution. Some of the larger small RNA species commonly used as reference genes (such as U6 snRNA) are not secreted or shielded in cell-free biofluids in the same way that microRNAs are.