While massive parallel sequencing technology is quite mature, a problematic aspect is that plasma tumor
markers are measured relative to total DNA, and total DNA levels vary with biologic factors like inflammation
and with pre-analytic interferences such as leukocyte lysis during blood collection and handling ex vivo. This
research aims to develop a novel strategy to quantify tumor markers in ‘copies per mL of plasma’, thus
harmonizing the massive parallel sequencing assay with gold standard values generated by quantitative PCR.
First, we will spike plasma with synthetic DNAs (called “EndoGenus Spikes”) which are then targeted for
enrichment during library preparation and are quantified using informatic scripts after massive parallel
sequencing. By normalizing levels of each tumor marker to the fractional recovery of spiked DNAs, numerical
values are reportable in units of “copies per mL of plasma”, which we will show reflect clonal abundance. This
new capability for absolute quantification of clonal abundance is likely to benefit basic scientists studying tumor
heterogeneity and clonal evolution, and is likely to benefit patients and healthcare providers who seek more
informative ways to monitor tumor burden, to evaluate the impact of medical interventions, and to find
emerging drug resistance clones so that alternate therapy may be considered in a timely fashion. At the
conclusion of this study, we will have developed and validated the ‘EndoGenus Toolkit’, comprised of synthetic
DNAs, reagents to enrich for them during library preparation, and bioinformatic scripts to convert tumor marker
levels from fractions to absolute concentrations. We will show that applying the ‘Toolkit’ to mock plasma
specimens yields sensitive, specific, linear and reproducible sequencing results for multiple tumor markers. In
blood from active cancer subjects, we will show that the ‘Toolkit’ helps overcome pre-analytic problems
associated with blood storage. These tools should facilitate future clinical trials aimed at setting numeric
thresholds for changing patient management.
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