Evidence map›Paper›PMID 31594033›Full record

ReviewCancer science2019

Experimental identification of cancer driver alterations in the era of pan-cancer genomics.

Michael Korenjak, Jiri Zavadil

Abstract readReview
In one paragraph

Review in Cancer science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
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  8. Review
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  13. Identification ofSaudi medical journal · 2021
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  16. Review
  17. 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.

Michael KorenjakMolecular Mechanisms and Biomarkers Group, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Jiri ZavadilMolecular Mechanisms and Biomarkers Group, International Agency for Research on Cancer, World Health Organization, Lyon, France.ORCID https://orcid.org/0000-0003-0640-5562

Funding

ITMO CANCER INCa - INSERM Plan Cancer 2015 Grant ENV201507World Health Organization 001
6 · The paper itself

Abstract

Rapidly accumulating data from large-scale cancer genomics studies have been generating important information about genes and their somatic alterations underlying cell transformation, cancer onset and tumor progression. However, these events are usually defined by using computational techniques, whereas the understanding of their actual functional roles and impact typically warrants validation by experimental means. Critical information has been obtained from targeted genetic perturbation (gene knockout) studies conducted in animals, yet these investigations are cost-prohibitive and time-consuming. In addition, the 3R principles (replacement, reduction, refinement) have been set in place to reduce animal use burden and are increasingly observed in many areas of biomedical research. Consequently, the focus has shifted to new designs of innovative cell-based experimental models of cell immortalization and transformation in which the critical cancer driver events can be introduced by mutagenic insult and studied functionally, at the level of critical phenotypic readouts. From these efforts, primary cell-based selective barrier-bypass models of cell immortalization have emerged as an attractive system that allows studies of the functional relevance of acquired mutations as well as their role as candidate cancer driver events. In this review, we provide an overview of various experimental systems linking carcinogen exposure-driven cell transformation with the study of cancer driver events. We further describe the advantages and disadvantages of the currently available cell-based models while outlining future directions for in vitro modeling and functional testing of cancer driver events.

Indexed as

GenomicsCell Transformation, NeoplasticChromatinHumansMutationNeoplasmsChromatinbioinformaticscarcinogenesisepigeneticsexperimental cell culture systemsgenomic analysis

Identifiers

PMID31594033
PMCPMC6890429

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.