AbstractMotivationSampling circulating tumor DNA, ctDNA, using liquid biopsies offers clinically important benefits for monitoring of cancer progression. A single ctDNA sample represents a mixture of shed tumor DNA from all known and unknown lesions within a patient. Although shedding levels have been suggested to hold the key to identifying targetable lesions and uncovering treatment resistance mechanisms, the amount of DNA shed by any one specific lesion is still not well characterized. We designed the LSM (Lesion Shedding Model) to order lesions from the strongest to the poorest shedding for a given patient. Our framework intrinsically models for missing/hidden lesions and operates on blood ctDNA and lesion assays to estimate the potential relative shedding levels of lesions into the blood. By characterizing the lesion-specific ctDNA shedding levels, we can better understand the mechanisms of shedding as well as more accurately contextualize and interpret ctDNA assays to improve their clinical impact.ResultsWe verified the accuracy of the LSM under controlled conditions using a simulation approach as well as testing on two gastrointestinal cancer patients. In the simulation we created a synthetic blood ctDNA sample per patient, where specific lesions are assigned predefined shedding levels. The simulated data mirrors real data lesion genomic similarities. The LSM correctly obtains a partial order of the lesions, i.e. accurately stratifies the lesions by their assigned shedding levels for simulations on two patients with strikingly different numbers of biopsied lesions, 4 and 17. The LSM’s accuracy in identifying the top shedding lesion was not impacted by the higher number of lesions considered. We then applied LSM to two gastrointestinal cancer patients with available ctDNA blood samples and multiple biopsied lesions and found that indeed there were lesions that were consistently shedding more than other lesions into the patients’ blood. We also found that in both patients the top shedding lesion was one of the only clinically progressing lesions at the time of biopsy suggesting a connection between high ctDNA shedding and clinical progression. The LSM provides a much needed framework with which to understand ctDNA shedding and how to apply ctDNA assays.AvailabilityBinary is available at https://github.com/ComputationalGenomics/LSM
The size of cell-free mitochondrial DNA in blood is inversely correlated with tumor burden in cancer patients
