Evidence map›Paper›PMID 29270389›Full record

ArticleFrontiers in oncology2017

Domesticating Cancer: An Evolutionary Strategy in the War on Cancer.

Gustav van Niekerk, Theo Nell, Anna-Mart Engelbrecht

Abstract read
In one paragraph

Article in Frontiers in oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Gustav van NiekerkDepartment of Physiological Sciences, Stellenbosch University, Stellenbosch, South Africa.
Theo NellDepartment of Physiological Sciences, Stellenbosch University, Stellenbosch, South Africa.
Anna-Mart EngelbrechtDepartment of Physiological Sciences, Stellenbosch University, Stellenbosch, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since cancer shares the same molecular machinery as the host, most therapeutic interventions that aim to target cancer would inadvertently also adversely affect the host. In addition, cancer continuously evolves, streamlining its host-derived genome for a new single-celled existence. In particular, short-term clinical success observed with most antineoplastic therapies directly relate to the fact that cancer is constantly evolving. However, the clonal evolution of cancer occasionally also render cancer cells uniquely susceptible to therapeutic interventions, as is exemplified by the clinical relevance of synthetic lethality. Synthetic lethality describes a situation where the simultaneous loss of function in two genes results in lethality, but where a loss of function in either single gene is tolerated. This observation suggests that the evolution of cancer, usually seen as a major clinical challenge, may also afford a key opportunity in lowering on-target toxicities accosted with chemotherapy. As an example, by subjecting cancer to specific selection regimes, cancer can in effect be placed on evolutionary trajectories leading to the development of "targetable" phenotypes such as synthetic lethal interactions. However, such a selection regime would have to overcome a range of obstacles such as on-target toxicity and the selection of an evolvable trait. Since the majority of cancer evolution manifests as a loss of function, we suggest that the induction of auxotrophic phenotypes (i.e., where an organism lose the ability to synthesize specific organic compounds required for growth and thus become dependent on it from dietary sources) may represent an attractive therapeutic option. As an example, animals can obtain vitamin C either by

Indexed as

auxotrophycancerchemoresistanceevolutionsynthetic lethality

Identifiers

PMID29270389
PMCPMC5725441

What OpenQuestion holds

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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.