Effective administration of targeted therapeutics and monitoring of cancer require frequent profiling of a patient’s tumor mutations. Plasma and tissue biopsies containing very low tumor content can confound standard assays, particularly when the few tumor molecules that may be present are massively outnumbered by normal DNA.
The Challenge
The fundamental challenge with genomic profiling of tumors is one of finding needles in a haystack. Only OnTarget™ can deliver high sensitivity and accuracy,
Mutation detection in tissue
Mutation analysis of biopsy tissue is the current standard for targeted therapy selection. Unfortunately, there are two major shortcomings:
- Tissue biopsies vary in tumor content and abundance of cells carrying mutations that influence therapy efficacy. This means that some biopsies carry mutations relevant to treatment selection, but below levels that are detectable by current methods. Higher sensitivity assays are required to ensure correct treatment selection for all patients.
- Mutation profiling through a biopsy is only applicable at the beginning of treatment when tumor tissue is available. Tissue testing is therefore not appropriate for ongoing monitoring of a patient’s evolving tumor mutation profile.
Mutation detection in plasma
Blood plasma has been shown to carry cell-free DNA containing tumor mutations, indicating that plasma tests can be a non-invasive alternative to tissue biopsies, and can indicate tumor load and recurrence. However, detection of tumor mutations in plasma poses a significant challenge as tumor DNA is heavily diluted by DNA from normal cells, to abundances that can be as low as 0.01%. While this makes tumor DNA in plasma difficult to detect, there is tremendous potential benefit in continuous monitoring of recurrence and evolving tumor mutations.
Amplification errors arise in conventional assays due to an abundance of wild-type alleles
PCR and sequencing assays are typically limited in detection of tumor mutations due to high false positive background. The combination of low amounts of target DNA, sequence similarity of the target and wild-type alleles, and amplification errors made on the large excess of wild-type sequence limit mutation detection by existing technologies to abundances greater than ~0.1 – 1%.
Even digital PCR methods require prior amplification of the sample, introducing errors that ultimately limit specificity and sensitivity. Not only do amplification errors on wild-type sequences pose a fundamental limitation on accuracy of current assays; but the large abundance of wild-type DNA leads to a very inefficient use of assay resources, whether sequencing lanes or digital PCR droplets, to detect the small fraction of tumor information in the sample.
The challenge facing current technologies for low abundance mutation detection lies in the fact that each mutant allele may be outnumbered by the nearly identical wild-type allele by as much as 10,000 to 1. Errors made on the abundant wild-type allele lead to false positives which limits sensitivity. The diagram above demonstrates an attempt at direct detection of mutations present at only 0.01% of total DNA without OnTarget™. Errors introduced at 0.1% frequency by PCR or amplification during next generation sequencing generate false positives from the wild-type alleles and make the mutant signal indistinguishable from noise.
Effective diagnostics require highly multiplexed detection without compromising assay sensitivity.
There is increasing evidence that multiple mutations play a role in drug response or resistance, suggesting that in order to be informative, assays will need to test for multiple mutations without sacrificing sensitivity. Background mutation levels in healthy individuals (~1 mutation in 1,000,000) as well as ever changing mutation profiles, can confound assays that are limited to analyzing only a few mutations. Correct interpretation of assay results will require a comparison of relative abundance over a large number of tumor-related mutations in order to identify significant mutational events that signal emerging disease or drug resistance.