Top Challenges of Biofluid Samples when Profiling FFPE miRNA Biomarkers
In 1993, Dr. Victor Ambros’ lab discovered a small RNA sequence, Lin-4, that was “essential for the normal temporal control of diverse postembryonic developmental events in C. Elegans”. Sequence analysis revealed that the molecule was 22 nucleotides long and didn’t encode for a protein but contained sequences complementary to a repeated sequence element in the 3’ region of the Lin-14 mRNA. MicroRNA (miRNA) was discovered.
Since then, almost 2,000 of these 21-25 nucleotide miRNAs have been identified. They are responsible for the post-transcriptional gene regulation of an estimated 60% of the genes in the human genome, thus regulating almost all fundamental cell processes—proliferation, apoptosis, differentiation, migration, metabolism, and stress response.
Furthermore, aberrant miRNA expression is frequently observed in human illnesses. This, and the fact that miRNAs are stable and can freely circulate outside the cells and in biofluids – urine, sweat, cerebrospinal liquid, blood – makes them ideal candidates for biomarkers. miRNAs have traditionally been measured using quantitative PCR, microarrays, or NGS, but these methods require heavy sample manipulation, increasing the probability of introducing bias. Plus, these methods involve long processing times.
nCounter® miRNA Expression Panels, Ideal for FFPE and Biofluids Analysis
The technology behind the NanoString® nCounter® platform allows scientists to literally count RNA molecules that have been tagged with sequence-specific fluorescent barcodes. This method accommodates low RNA input down to 25 ng and measures RNA without cDNA conversion, amplification, or library preparation.
Because the technology has proven ideal for rescuing poor-quality RNA from “difficult samples” such as FFPE tissue, biofluids, and cell lysates, it has also become an ideal tool to detect miRNA in biofluids; nCounter miRNA Expression Assay Panels allow for the analysis of up to 800 biologically relevant miRNAs in human, mouse, and rat samples in less than 24 hours and unambiguously discriminates between miRNAs that have single nucleotide differences.
In this on-demand webinar, former NanoString Senior Application Scientist Dr. Kirsteen Maclean walks us through the chemistry that makes the NanoString miRNA panels the ideal solution for studying miRNA expression in all tissues and introduces some of the cutting-edge, peer-reviewed research from customers who have used a NanoString miRNA panel for biomarker discoveries. Here are a few examples of the research she presents:
The Power of Interrogating the Brain’s Health Without any Brain Tissue
Alzheimer’s disease (AD) is a critical condition that is hard to distinguish at an early stage. Diagnosis is time-consuming, invasive, and expensive: a minimally invasive, fast (within 24 hours!) and robust blood test for AD would be extremely helpful for early diagnosis, disease progression monitoring, and clinical care.
The versatility of the nCounter platform for robustly measuring miRNA in challenging samples allowed for a global profiling approach, and the researchers measured circulating plasma miRNA in a total of 11 AD patients and 20 controls. The group, led by Pavan Kumar, measured a total of 654 human miRNAs, out of which 12 miRNAs displayed differential expression in AD samples. Of these 12 miRNAs, seven were then validated in an independent cohort resulting in positive correlations across the two independent cohorts with up to 95% accuracy.
mRNA and miRNA analysis on the Same Sample
Because a network of genes and the molecules that regulate them work in concert to influence molecular pathways, assessment of gene expression by profiling only mRNA without the regulatory influence of miRNAs will not adequately explain complex biological mechanisms. Cascione and colleagues took this integrative approach in a study aimed to stratify triple-negative breast cancer (TNBC).
By studying over 250 FFPE tissue samples, the team linked two specific miRNA signatures to overall survival and distant disease-free survival, respectively, in patients ≥ 50 years of age. By measuring differential gene expression with a NanoString gene expression assay, the investigators identified three subclasses of clinically and genetically distinct TNBC with an inverse correlation between miRNA and mRNA.
- Pavan Kumar et al.: Circulating miRNA Biomarkers for Alzheimer’s Disease. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0069807
- Luciano Cascione et al.: Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0055910