Abstract 6621: Simulating the distortion of clonal fractions in ctDNA due to spatially heterogenous selection

Abstract

Abstract Time-series circulating tumor DNA (ctDNA) sequencing has the potential to reveal emerging variants in the tissue in real time, and there is now substantial evidence that it can detect tumor growth and treatment-resistant mutations long before growth is visible. However, the reliability of ctDNA for profiling the primary tumor may be compromised by spatial heterogeneity in the tumor genetics, for example due to selective effects of differential drug penetration, immune infiltration, and oxygenation. We explore the influence of spatial factors on tumor genetics through a lattice-based branching process model of solid tumor evolution and ctDNA shedding with the goal of understanding where spatially variable selection pressure could lead to a significant difference between the clonal fractions in the blood and the tissue. The lattice model divides space into regions with different growth rates which result in different rates of driver mutation accumulation. The effects of regional differences in selection cause different apoptosis rates to correlate with the location of expanding driver clones. Using these rates to simulate ctDNA shedding, our model found that clones fit enough to invade a hostile region are temporarily amplified in the blood compared to their tissue frequency by as much as 300% for a limited window of time before the population expands further and the clonal fraction in the blood returns to close agreement with tissue. The results suggest evolutionary contexts in which liquid biopsy might provide highly biased estimates of tumor state, but also shows how this effect might be exploited to provide more sensitive detection of clonal expansion with implications for blood-based detection of recurrence and metastasis. Citation Format: Thomas W. Rachman, Oana Carja, Russell Schwartz. Simulating the distortion of clonal fractions in ctDNA due to spatially heterogenous selection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6621.