Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition
- Thomas Rachman 1,2, David Bartlett 3, William LaFramboise 3, Patrick Wagner 3, Russell Schwartz 1, Oana Carja 1
- Thomas Rachman 1,2, David Bartlett 3, William LaFramboise 3
- 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
- 2Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA.
- 3Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA.
- 0Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
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View abstract on PubMed
Summary
This summary is machine-generated.Spatially variable cell death in tumors can distort circulating tumor DNA (ctDNA) profiles. This bias in ctDNA may lead to inaccurate cancer assessments and treatment decisions, highlighting a critical area for future research.
Area Of Science
- Oncology
- Genomics
- Computational Biology
Background
- Circulating tumor DNA (ctDNA) monitoring is crucial for real-time tumor evolution tracking, diagnosis, treatment guidance, and prognosis.
- Current ctDNA analysis primarily relies on DNA from apoptotic or necrotic cells, which can be influenced by tumor microenvironment factors like chemotherapy and immune infiltration.
Purpose Of The Study
- To investigate how spatially variable cell death rates at tumor boundaries impact driver mutation accumulation and ctDNA representation.
- To model the effects of biased cell shedding on clonal composition, mutation detectability, and variant allele frequencies (VAFs) in ctDNA.
Main Methods
- Utilized a stochastic evolutionary model of boundary-driven tumor growth.
- Simulated conditions with elevated cell death rates on the tumor periphery.
- Analyzed the impact on driver mutation accumulation, clonal representation, and VAFs in ctDNA.
Main Results
- Spatially variable cell death can lead to over-representation of invasive clones in ctDNA.
- Observed potential inflation of subclonal VAFs and apparent elevation of clonal diversity in blood samples.
- Demonstrated that quiescent tumors with spatial shedding bias are less detectable, and detection limits influence perceived bias.
Conclusions
- Spatially structured cell death can significantly bias ctDNA profiles, potentially misrepresenting the true tumor state.
- While biased shedding may enhance detection of expanding clones, it risks guiding treatment towards subclonal variants.
- Further research is needed to understand the clinical implications of spatially variable cell death on ctDNA composition and its impact on cancer management.
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