Evidence map›Paper›PMID 29352488›Full record

ReviewCancer science2018

Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling.

Atsushi Niida, Satoshi Nagayama, Satoru Miyano, Koshi Mimori

Erratum issuedAbstract readReview
In one paragraph

Review in Cancer science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Modeling colorectal cancer evolution.Journal of human genetics · 2021
    Review
  8. CORRECTION.Cancer science · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Intratumoral Heterogeneity in Ductal Carcinoma In Situ: Chaos and Consequence.Journal of mammary gland biology and neoplasia · 2018
    Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Atsushi NiidaDivision of Health Medical Computational Science, Health Intelligence Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
Satoshi NagayamaDepartment of Gastroenterological Surgery, Gastroenterological Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.ORCID http://orcid.org/0000-0001-9632-914X
Satoru MiyanoDivision of Health Medical Computational Science, Health Intelligence Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
Koshi MimoriDepartment of Surgery, Kyushu University Beppu Hospital, Beppu, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle-level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting.

Indexed as

Colorectal NeoplasmsGenetic HeterogeneityGenomeHumansModels, Theoreticalcolorectal cancerevolutionintratumor heterogeneitymathematical modelingmultiregion sequencing

Identifiers

PMID29352488
PMCPMC5891172

What OpenQuestion holds

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LicenceCC BY-NC
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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.