Evidence map›Paper›PMID 27573059›Full record

ArticleScientific reports2016

In silico modelling of a cancer stem cell-targeting agent and its effects on tumour control during radiotherapy.

Loredana G Marcu, David Marcu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 24% of its field
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

7 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. The RARγ Oncogene: An Achilles Heel for Some Cancers.International journal of molecular sciences · 2021
    Review
  4. Review
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  6. Article
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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 at 2 institutions in 2 countries.

Loredana G MarcuFaculty of Science, University of Oradea, Oradea 410087, Romania.
David MarcuFaculty of Science, University of Oradea, Oradea 410087, Romania.
University of Adelaide · AUUniversity of Oradea · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Head and neck cancers (HNC), like most solid tumours, contain a subpopulation of cancer stem cells (CSC) that are commonly responsible for treatment failure. Conventional therapies are unsuccessful in controlling CSCs, thus novel, targeting therapies are needed. A promising agent is ATRA (All-trans-retinoic acid) that was shown to induce CSC differentiation, cell cycle redistribution and CSCs radiosensitisation. To add to the limited data, this work simulated the effects of ATRA on a virtual HNC and evaluated tumour response to radiotherapy. A Monte Carlo technique was employed to grow a HNC consisting of all lineages of cancer cells. The biologically realistic input parameters led to a pre-treatment CSC population of 5.9%. The Linear Quadratic model was employed to simulate radiotherapy. ATRA-induced differentiation, cell arrest and apoptosis were modelled, based on literature data. While the effect of differentiation was marginal, the strongest influence on CSC subpopulation was displayed by ATRA's cell arrest effect via an exponential behaviour of the dose-response curve. The apoptotic effect induced by ATRA shows linear correlation between the percentage of apoptotic cells and dose required to eradicate CSCs. In conclusion, ATRA is a potent CSC-targeting agent with viable impact on tumour control when combined with radiotherapy.

Indexed as

ApoptosisCarcinoma, Squamous CellCell CycleCell DifferentiationCell ProliferationComputer SimulationHead and Neck NeoplasmsHumansMonte Carlo MethodNeoplastic Stem Cells

Identifiers

PMID27573059
PMCPMC5004146
OpenAlexW2518615277

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.