Evidence map›Paper›PMID 34433859›Full record

ArticleScientific reports2021

Migrations of cancer cells through the lens of phylogenetic biogeography.

Antonia Chroni, Sayaka Miura, Olumide Oladeinde, Vivian Aly, Sudhir Kumar

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Resolving tumor evolution: a phylogenetic approach.Journal of the National Cancer Center · 2024
    Review
  3. Onco-Breastomics: An Eco-Evo-Devo Holistic Approach.International journal of molecular sciences · 2024
    Review
  4. Review
  5. Article
  6. Article
  7. Tumors Are Evolutionary Island-Like Ecosystems.Genome biology and evolution · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Antonia ChroniInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, 19122, USA.
Sayaka MiuraInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, 19122, USA.
Olumide OladeindeInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, 19122, USA.
Vivian AlyInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, 19122, USA.
Sudhir KumarInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, 19122, USA. s.kumar@temple.edu.

Funding

Bioinformatics of metastatic migration historiesR01LM013385 · NLM · TEMPLE UNIV OF THE COMMONWEALTH · PI KUMAR, SUDHIR · 2020 to 2023
$1.4M
NLM NIH HHS R01 LM013385
6 · The paper itself

Abstract

Malignant cells leave their initial tumor of growth and disperse to other tissues to form metastases. Dispersals also occur in nature when individuals in a population migrate from their area of origin to colonize other habitats. In cancer, phylogenetic biogeography is concerned with the source and trajectory of cell movements. We examine the suitability of primary features of organismal biogeography, including genetic diversification, dispersal, extinction, vicariance, and founder effects, to describe and reconstruct clone migration events among tumors. We used computer-simulated data to compare fits of seven biogeographic models and evaluate models' performance in clone migration reconstruction. Models considering founder effects and dispersals were often better fit for the clone phylogenetic patterns, especially for polyclonal seeding and reseeding of metastases. However, simpler biogeographic models produced more accurate estimates of cell migration histories. Analyses of empirical datasets of basal-like breast cancer had model fits consistent with the patterns seen in the analysis of computer-simulated datasets. Our analyses reveal the powers and pitfalls of biogeographic models for modeling and inferring clone migration histories using tumor genome variation data. We conclude that the principles of molecular evolution and organismal biogeography are useful in these endeavors but that the available models and methods need to be applied judiciously.

Indexed as

Founder EffectHuman MigrationModels, GeneticPhylogenyBreast NeoplasmsEvolution, MolecularFemaleGene FrequencyHumansMalePolymorphism, Genetic

Identifiers

PMID34433859
PMCPMC8387374

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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.