Evidence map›Paper›PMID 29903534›Full record

ReviewTrends in genetics : TIG2018

Harnessing Tumor Evolution to Circumvent Resistance.

Katherine L Pogrebniak, Christina Curtis

Abstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
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  9. Review
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  11. Article
  12. Article
  13. Treatment of evolving cancers will require dynamic decision support.Annals of oncology : official journal of the European Society for Medical Oncology · 2023
    Review
  14. Application of single-cell RNA sequencing in head and neck squamous cell carcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023
    Article
  15. Evolving therapeutic landscape of advanced hepatocellular carcinoma.Nature reviews. Gastroenterology & hepatology · 2023
    Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. Connecting Metabolic Rewiring With Phenotype Switching in Melanoma.Frontiers in cell and developmental biology · 2022
    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

2 authors.

Katherine L PogrebniakCancer Biology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; http://med.stanford.edu/curtislab.html.
Christina CurtisCancer Biology Program, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; http://med.stanford.edu/curtislab.html. Electronic address: cncurtis@stanford.edu.

Funding

Integrated genomic analysis and multi-scale modeling of therapeutic resistanceR01CA182514 · NCI · STANFORD UNIVERSITY · PI CURTIS, CHRISTINA N · 2014 to 2018
$2.4M
NCI NIH HHS R01 CA182514
6 · The paper itself

Abstract

High-throughput sequencing can be used to measure changes in tumor composition across space and time. Specifically, comparisons of pre- and post-treatment samples can reveal the underlying clonal dynamics and resistance mechanisms. Here, we discuss evidence for distinct modes of tumor evolution and their implications for therapeutic strategies. In addition, we consider the utility of spatial tissue sampling schemes, single-cell analysis, and circulating tumor DNA to track tumor evolution and the emergence of resistance, as well as approaches that seek to forestall resistance by targeting tumor evolution. Ultimately, characterization of the (epi)genomic, transcriptomic, and phenotypic changes that occur during tumor progression coupled with computational and mathematical modeling of tumor evolutionary dynamics may inform personalized treatment strategies.

Indexed as

Models, BiologicalAnimalsBiomarkers, TumorCell Transformation, NeoplasticClonal EvolutionComputer SimulationDisease ProgressionDrug Resistance, NeoplasmGenetic HeterogeneityHumansMolecular Targeted TherapyNeoplasmsRadiation ToleranceBiomarkers, Tumorclonal dynamicscomputational modelingtherapeutic resistancetissue correlative studiestumor evolution

Identifiers

PMID29903534
PMCPMC6368975

What OpenQuestion holds

Textmetadata
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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.