Evidence map›Paper›PMID 27736801›Full record

ArticleOncotarget2017

Individual patient oesophageal cancer 3D models for tailored treatment.

John H Saunders, David Onion, Pamela Collier, Matthew S Dorrington, Richard H Argent, Philip A Clarke, Alex M Reece-Smith, Simon L Parsons, Anna M Grabowska

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 33% 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

6 citing papers in PubMed, 16 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

John H SaundersCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
David OnionCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Pamela CollierCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Matthew S DorringtonCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Richard H ArgentCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Philip A ClarkeCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Alex M Reece-SmithCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Simon L ParsonsCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
Anna M GrabowskaCancer Biology Unit, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
University of Nottingham · GBNottingham University Hospitals NHS Trust · GB

Funding

National Centre for the Replacement, Refinement and Reduction of Animals in Research G0900765/1
6 · The paper itself

Abstract

backgroundA model to predict chemotherapy response would provide a marked clinical benefit, enabling tailored treatment of oesophageal cancer, where less than half of patients respond to the routinely administered chemotherapy.

methodsCancer cells were established from tumour biopsies taken from individual patients about to undergo neoadjuvant chemotherapy. A 3D-tumour growth assay (3D-TGA) was developed, in which cancer cells were grown with or without supporting mesenchymal cells, then subjected to chemo-sensitivity testing using the standard chemotherapy administered in clinic, and a novel emerging HDAC inhibitor, Panobinostat.

resultsIndividual patient's cancer cells could be expanded and screened within a clinically applicable timescale of 3 weeks. Incorporating mesenchymal support within the 3D-TGA significantly enhanced both the growth and drug resistance profiles of the patient's cancer cells. The ex vivo drug response in the presence, but not absence, of mesenchymal cells accurately reflected clinical chemo-sensitivity, as measured by tumour regression grade. Combination with Panobinostat enhanced response and proved efficacious in otherwise chemo-resistant tumours.

conclusionsThis novel method of establishing individual patient oesophageal cancers in the laboratory, from small endoscopic biopsies, enables clinically-relevant chemo-sensitivity testing, and reduces use of animals by providing more refined in vitro models for pre-screening of drugs. The 3D-TGA accurately predicted chemo-sensitivity in patients, and could be developed to guide tailored patient treatment. The incorporation of mesenchymal cells as the stromal cell component of the tumour micro-environment had a significant effect upon enhancing chemotherapy drug resistance in oesophageal cancer, and could prove a useful target for future drug development.

Indexed as

Cell Culture TechniquesPrecision MedicineAgedBiomarkersCell Line, TumorCell ProliferationCombined Modality TherapyDrug Resistance, NeoplasmEsophageal NeoplasmsFemaleHumansImmunohistochemistryIn Vitro TechniquesMaleMiddle AgedNeoplasm StagingBiomarkers3D modelschemotherapyoesophageal cancerpersonalised treatmenttumour microenvironment

Identifiers

PMID27736801
PMCPMC5421842
OpenAlexW2529047469

What OpenQuestion holds

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LicenceCC BY
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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.