Accurately Define Gene Expression Profiling
The identification of biomarkers has long been used to aid researchers in understanding cellular function in response to disease identification and progression. As with any field, the methodologies used to do this have evolved over time to become more powerful and efficient. Below are brief explanations of four of the most common technologies currently used to identify and validate biomarkers and the challenges associated with each.
Targeted GEP Assays
Targeted gene expression profiling (GEP) is a technique used to quantify RNA expression that requires prior knowledge of the target sequence. A probe is designed based on the target sequence and hybridizes to a complementary oligonucleotide in the sample to capture or protect the target. Gene expression is then quantified either directly through fluorescence or using NGS based detection.
- Streamlined workflow and faster data output
- Lower sample input requirement than RNA-Seq technologies
- Small probes capture fragmented RNA increasing sensitivity to low expressors
- Requires prior knowledge of the target sequence
- de novo transcripts are not identified
- Limited flexibility due to fixed gene lists
RNA-Seq or RNA-Sequencing is a Next Generation Sequencing (NGS) based technique used to identify the presence and quantity of RNA in a biological sample. RNA-Seq utilizes a complex workflow that requires RNA extraction followed by cDNA synthesis using random primers, which allows for nucleotide-level quantification of RNAs without prior knowledge of the genome or transcriptional targets. Because of this, RNA-Seq can identify splice variants, post-transcriptional modifications and mutations.
- Identifies de novo transcripts including mutations and splice variants
- Nucleotide level quantification without prior knowledge of a genome
- Generates a lot of data from each sample
- Requires more sample input than other technologies
- Requires RNA extraction that removes small and degraded RNAs
- Workflow can take several weeks and lacks automation
- Heavy lift for bioinformatics and interpretation
Microarray assays are based on the principle of in situ hybridization and consist of glass slides that are printed with tiny spots in defined positions, each spot is contains a known DNA sequence representing a specific gene. These DNA sequences then hybridize to their RNA or DNA molecules from a sample, based on the principle of complementary nucleic acid sequences. The hybrid molecule is then detected using fluorescence and used to determine the relative abundance of a target sequence.
- Simplified workflow
- Quantify thousands of genes concurrently
- Does not require costly instrumentation
- Relatively low accuracy and sensitivity compared to NGS
- Data normalization
Immunohistochemistry (IHC) is a powerful tool which uses immunostaining, the process of identifying proteins in tissue using antibodies that specifically bind to the protein of interest on a biological tissue sample. Visualization of the antibodies can be accomplished either by colorimetric reaction or fluorescence.
- Current standard for cancer diagnostics
- Quick and relatively inexpensive
- Gather information on the subcellular localization of proteins
- Need antibodies specific for target
- Operator variability and interpretation
- Only evaluate a few proteins at a time