Horizon Diagnostics (HDx) Quantitative Molecular Reference Standards are available primarily in two formats, as Formalin-Fixed, Paraffin-Embedded (FFPE) cells, and as genomic DNA (gDNA). FFPE-derived reference standards are ideal tools used to test the full integrity of a molecular assay workflow from extraction through to quantification to molecular testing and data analysis.
Laboratories often assume that a failed assay is as a result of a failed analytical step, however root cause analysis often shows that problems with DNA extraction or issues with DNA quantification are really at fault (e.g. over-estimating sample DNA concentration leading to the assay being under loaded). Analyzing the cause of a failed assay is a particular challenge for laboratories not used to handling FFPE samples, or for laboratories using quantification methodologies that tend to overestimate the amount of DNA in a sample when measuring concentrations below 20 ng per microliter (e.g. NanoDrop).
Mutant cell lines embedded in FFPE are all heterozygotes, and in the majority of cases this means there is a single mutant allele and a single normal allele. Where the copy number is 2N, a 100% mutant gDNA sample indicates that 100% of the cells the gDNA was extracted from contained the mutation, however as only one of the two copies of the gene from that cell will actually contain the mutation, the sample actually will have an allelic frequency of 50% for that mutation. Mutant and “normal” cell lines can be precisely blended to generate samples with specific allelic frequencies typically ranging between 1% and 50%.
Sources of variabitlity within a standard molecular assay workflow
Successful execution of the analytical phase is completely dependent on correct performance during the pre-analytical phase
Tumor profiles and genotype can often be specific to individual samples and depending on the sample the proportion of normal versus tumor cells can be highly variable. Genoytping a sample from a 10% tumor cell population may challenge the limit of detection of the molecular assay compared to a sample from a 100% tumor cell population.
Sample fixation processes are highly variable and will impact on the quality of the extractable DNA. High-grade formalin for a short time (i.e. less than 24 hours) will preserve the quality DNA within the samples and provide a greater DNA yield compared to Low-grade formalin for a longer time (i.e. more than 24 hours).
Success or failure in DNA analysis applications often comes down to whether or not the appropriate amount of nucleic acid is used in the analysis and if the quality of that nucleic acid is sufficient. UV absorbance is one of the most popular methods for quantitating nucleic acids, however, there are many methods available, each with its own strengths and weaknesses.
At DNA concentrations below 10ng/µl UV absorbance is often inaccurate up to a factor of 3 - 5 fold.
The limit of detection of a molecular diagnostic assay can vary from 1% to 25%. This is dependent on the assay design as well as the platform choice. Not all platforms are capable of distinguishing between subtle nucleic acid changes.
Isolation of genomic DNA from formalin fixed paraffin embedded (FFPE) tissues is a critical step for molecular diagnostic (MDx) assays. It is essential that the maximum amount of DNA is recovered from the FFPE tissues and its quality is sufficient to perform the necessary MDx assays.
The quality and quantity of DNA can vary widely depending on the extraction method/kit used.
Sanger Sequencing has a limit of detection cutoff between 15% and 25% and this sensitivity depends on the gene, mutation and assay design.
A quantitative polymerase chain reaction (qPCR) will have a limit of deteciton of between 1% and 10%. This sensitivity will be defined by the assay design and specificity of the probe(s).
Next generation sequencing (NGS) is offering a way to quickly and affordably establish baseline tumor genetics and the limit of detection is between 1% and 5%.
The format of the molecular assays output will be different depending on the platform and software used.
Analysis and interpretation of sample data is critical for effective tumor profiliing. This is becoming more difficult with multiplex NGS platforms and our reference standards can be used to assist with data interpretation and benchmarking.