Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition
Year: 2024
Type: article
Abstract: Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones are over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.
Source: Cancers
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,296
Awards: Integrated Interdisciplinary, inter-university PhD Program Computational Biology (T32), Reconstructing mechanisms of somatic variation in diverse cellular lineages, THE OPEN SCIENCE GRID The Next Five Years: Distributed High Throughput Computing for the Nation's Scientists, Researchers, Educators, and Students, From pattern to function: eco-evolutionary representations of complex spatial structure for the new era of spatial biology
OpenAlex ID: W4391981316