Evidence map›Paper›PMID 24466029›Full record

ArticlePloS one2014

Investigation of radiosensitivity gene signatures in cancer cell lines.

John S Hall, Rohan Iype, Joana Senra, Janet Taylor, Lucile Armenoult, Kenneth Oguejiofor, Yaoyong Li, Ian Stratford, Peter L Stern, Mark J O'Connor and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

28 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

12 authors at 3 institutions in 1 country.

John S HallTranslational Radiobiology Group, The University of Manchester, Manchester, United Kingdom.
Rohan IypeTranslational Radiobiology Group, The University of Manchester, Manchester, United Kingdom.
Joana SenraExperimental Oncology Group, The University of Manchester, Manchester, United Kingdom ; Gray Institute for Radiation Oncology and Biology, The University of Oxford, Oxford, United Kingdom.
Janet TaylorTranslational Radiobiology Group, The University of Manchester, Manchester, United Kingdom ; Applied Computational Biology and Bioinformatics Group, CRUK Manchester Institute, Manchester, United Kingdom.
Lucile ArmenoultTranslational Radiobiology Group, The University of Manchester, Manchester, United Kingdom.
Kenneth OguejioforTranslational Radiobiology Group, The University of Manchester, Manchester, United Kingdom.
Yaoyong LiApplied Computational Biology and Bioinformatics Group, CRUK Manchester Institute, Manchester, United Kingdom.
Ian StratfordExperimental Oncology Group, The University of Manchester, Manchester, United Kingdom.
Peter L SternImmunology Group. CRUK Manchester Institute, Manchester, United Kingdom.
Mark J O'ConnorCancer Bioscience, Astra Zeneca, Macclesfield, United Kingdom.
Crispin J MillerApplied Computational Biology and Bioinformatics Group, CRUK Manchester Institute, Manchester, United Kingdom.
Catharine M L WestTranslational Radiobiology Group, The University of Manchester, Manchester, United Kingdom.
University of Manchester · GBAstraZeneca (United Kingdom) · GBCancer Research UK Manchester Institute · GB

Funding

Cancer Research UK 15675Cancer Research UK C1094/A9437Cancer Research UK C147/A6058Medical Research Council C1467/A7286Medical Research Council G0500366Medical Research Council GO801525
6 · The paper itself

Abstract

Intrinsic radiosensitivity is an important factor underlying radiotherapy response, but there is no method for its routine assessment in human tumours. Gene signatures are currently being derived and some were previously generated by expression profiling the NCI-60 cell line panel. It was hypothesised that focusing on more homogeneous tumour types would be a better approach. Two cell line cohorts were used derived from cervix [n = 16] and head and neck [n = 11] cancers. Radiosensitivity was measured as surviving fraction following irradiation with 2 Gy (SF2) by clonogenic assay. Differential gene expression between radiosensitive and radioresistant cell lines (SF2</> median) was investigated using Affymetrix GeneChip Exon 1.0ST (cervix) or U133A Plus2 (head and neck) arrays. There were differences within cell line cohorts relating to tissue of origin reflected by expression of the stratified epithelial marker p63. Of 138 genes identified as being associated with SF2, only 2 (1.4%) were congruent between the cervix and head and neck carcinoma cell lines (MGST1 and TFPI), and these did not partition the published NCI-60 cell lines based on SF2. There was variable success in applying three published radiosensitivity signatures to our cohorts. One gene signature, originally trained on the NCI-60 cell lines, did partially separate sensitive and resistant cell lines in all three cell line datasets. The findings do not confirm our hypothesis but suggest that a common transcriptional signature can reflect the radiosensitivity of tumours of heterogeneous origins.

Indexed as

TranscriptomeCarcinoma, Squamous CellCell Line, TumorCluster AnalysisFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHead and Neck NeoplasmsHumansMaleOrgan SpecificityProteomeProteomicsRadiation ToleranceReproducibility of ResultsSignal TransductionProteome

Identifiers

PMID24466029
PMCPMC3899227
OpenAlexW1989235871

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.