Evidence map›Paper›PMID 31527151›Full record

ReviewMolecular cancer research : MCR2020

Treating Cancer as an Invasive Species.

Javad Noorbakhsh, Zi-Ming Zhao, James C Russell, Jeffrey H Chuang

Abstract readReview
In one paragraph

Review in Molecular cancer research : MCR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Onco-Breastomics: An Eco-Evo-Devo Holistic Approach.International journal of molecular sciences · 2024
    Review
  2. Article
  3. Review
  4. Article
  5. Review
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

4 authors.

Javad Noorbakhsh *The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut.
Zi-Ming Zhao *The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut.
James C RussellThe University of Auckland, Auckland, New Zealand. j.russell@auckland.ac.nz jeff.chuang@jax.org.
Jeffrey H ChuangThe Jackson Laboratory for Genomic Medicine, Farmington, Connecticut. j.russell@auckland.ac.nz jeff.chuang@jax.org.ORCID 0000-0002-3298-2358

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI William Carl Skarnes · 1985 to 2026
$61.9M
PDXNet Data Commons and Coordinating CenterU24CA224067 · NCI · JACKSON LABORATORY · PI Jeffrey Hsu-Min Chuang · 2017 to 2026
$9.8M
Quantitative Computational Methods to Accurately Measure Tumor Heterogeneity in Solid Tumors to Inform Development of Evolution-based Treatment StrategiesR01CA230031 · NCI · JACKSON LABORATORY · PI CHUANG, JEFFREY HSU-MIN · 2018 to 2022
$2.6M
Dissection of Tumor Evolution Using Patient-Derived XenograftsR21CA191848 · NCI · JACKSON LABORATORY · PI CHUANG, JEFFREY HSU-MIN · 2015 to 2016
$531k
NCI NIH HHS P30 CA034196NCI NIH HHS R01 CA230031NCI NIH HHS R21 CA191848NCI NIH HHS U24 CA224067
6 · The paper itself

Abstract

To cure a patient's cancer is to eradicate invasive cells from the ecosystem of the body. However, the ecologic complexity of this challenge is not well understood. Here we show how results from eradications of invasive mammalian species from islands-one of the few contexts in which invasive species have been regularly cleared-inform new research directions for treating cancer. We first summarize the epidemiologic characteristics of island invader eradications and cancer treatments by analyzing recent datasets from the Database of Invasive Island Species Eradications and The Cancer Genome Atlas, detailing the superior successes of island eradication projects. Next, we compare how genetic and environmental factors impact success in each system. These comparisons illuminate a number of promising cancer research and treatment directions, such as heterogeneity engineering as motivated by gene drives and adaptive therapy; multiscale analyses of how population heterogeneity potentiates treatment resistance; and application of ecological data mining techniques to high-throughput cancer data. We anticipate that interdisciplinary comparisons between tumor progression and invasive species would inspire development of novel paradigms to cure cancer.

Indexed as

AnimalsHumansNeoplasms

Identifiers

PMID31527151
PMCPMC6942216

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.