Evidence map›Paper›PMID 38473206›Full record

ArticleCancers2024

Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition.

Thomas Rachman, David Bartlett, William LaFramboise, Patrick Wagner, Russell Schwartz, Oana Carja

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Circulating tumor DNA-based detection of molecular residual disease in isocitrate dehydrogenase-mutant cholangiocarcinoma for biomarker-guided therapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  2. Association of ctDNAJournal of gastrointestinal oncology · 2026
    Article
  3. Review
  4. Article
  5. Review
  6. Early ctDNA kinetics as a dynamic biomarker of cancer treatment response.bioRxiv : the preprint server for biology · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Thomas RachmanComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0001-9304-5934
David BartlettAllegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA.
William LaFramboiseAllegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA.
Patrick WagnerAllegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA.
Russell SchwartzComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Oana CarjaComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Funding

Integrated Interdisciplinary, inter-university PhD Program Computational Biology (T32)T32EB009403 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET, BAR-JOSEPH, ZIV · 2009 to 2023
$4.4M
From pattern to function: eco-evolutionary representations of complex spatial structure for the new era of spatial biologyR35GM147445 · NIGMS · CARNEGIE-MELLON UNIVERSITY · PI Oana Carja · 2022 to 2026
$1.9M
Reconstructing mechanisms of somatic variation in diverse cellular lineagesR01HG010589 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI SCHWARTZ, RUSSELL S · 2020 to 2023
$1.4M
NHGRI NIH HHS R01 HG010589NIBIB NIH HHS T32 EB009403NIGMS NIH HHS R35 GM147445
6 · The paper itself

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.

Indexed as

ctDNAspatial evolutiontumor DNA sheddingtumor evolutiontumor growth model

Identifiers

PMID38473206
PMCPMC10930890

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.