Evidence map›Paper›PMID 30481267›Full record

Trial reportAnnals of oncology : official journal of the European Society for Medical Oncology2018

A seven-Gene Signature assay improves prognostic risk stratification of perioperative chemotherapy treated gastroesophageal cancer patients from the MAGIC trial.

E C Smyth, G Nyamundanda, D Cunningham, E Fontana, C Ragulan, I B Tan, S J Lin, A Wotherspoon, M Nankivell, M Fassan and 13 more

Open access · bronzeAbstract readClinical Trial, Phase IIIRandomized Controlled TrialValidation Study
In one paragraph

Trial report in Annals of oncology : official journal of the European Society for Medical Oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 5% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients.Frontiers in bioengineering and biotechnology · 2020
    Pooled it
  2. Multimodal features and prognostic risk assessment in locally advanced gastric cancer patients following neoadjuvant therapy based on machine learning algorithms: a multicenter study.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors at 10 institutions in 5 countries.

E C SmythRoyal Marsden Hospital, London, UK.
G NyamundandaDivision of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
D CunninghamRoyal Marsden Hospital, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
E FontanaDivision of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
C RagulanDivision of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
I B TanMedical Oncology, National Cancer Centre Singapore, Singapore.
S J LinBioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Victoria, Australia; Division of Research, Peter MacCallum Cancer Centre, University of Melbourne, Victoria, Australia.
A WotherspoonRoyal Marsden Hospital, London, UK.
M NankivellClinical Trials Unit, Medical Research Council, University College London, London, UK.
M FassanDepartment of Pathology, University of Padua, Padua, Italy.
A LampisDivision of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
J C HahneDivision of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
A R DaviesGuys & St Thomas' Hospital, London, UK.
J LagergrenGuys & St Thomas' Hospital, London, UK; Upper Gastrointestinal Surgery, Department of Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
J A GossageGuys & St Thomas' Hospital, London, UK.
N MaiseyGuys & St Thomas' Hospital, London, UK.
M GreenGuys & St Thomas' Hospital, London, UK.
J L ZylstraDepartment of Pathology, University of Padua, Padua, Italy.
W H AllumRoyal Marsden Hospital, London, UK.
R E LangleyClinical Trials Unit, Medical Research Council, University College London, London, UK.
P TanCancer and Stem Cell Biology, Duke-NUS Medical School, Singapore.
N ValeriRoyal Marsden Hospital, London, UK; Division of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK.
A SadanandamDivision of Molecular Pathology, Institute of Cancer Research, London, UK; Centre for Molecular Pathology, Royal Marsden Hospital, London, UK. Electronic address: anguraj.sadanandam@icr.ac.uk.
Royal Marsden Hospital · GBSt Thomas' Hospital · GBUniversity of Padua · ITDuke-NUS Medical School · SGInstitute of Cancer Research · GBKarolinska University Hospital · SEMedical Research Council · GBNational Cancer Centre Singapore · SGUniversity College London · GBWalter and Eliza Hall Institute of Medical Research · AU

Funding

Cancer Research UK 18052Cancer Research UK C20023/A7217Medical Research Council MC_UU_12023/28
6 · The paper itself

Abstract

Background: Following neoadjuvant chemotherapy for operable gastroesophageal cancer, lymph node metastasis is the only validated prognostic variable; however, within lymph node groups there is still heterogeneity with risk of relapse. We hypothesized that gene profiles from neoadjuvant chemotherapy treated resection specimens from gastroesophageal cancer patients can be used to define prognostic risk groups to identify patients at risk for relapse. Patients and methods: The Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) trial (n = 202 with high quality RNA) samples treated with perioperative chemotherapy were profiled for a custom gastric cancer gene panel using the NanoString platform. Genes associated with overall survival (OS) were identified using penalized and standard Cox regression, followed by generation of risk scores and development of a NanoString biomarker assay to stratify patients into risk groups associated with OS. An independent dataset served as a validation cohort. Results: Regression and clustering analysis of MAGIC patients defined a seven-Gene Signature and two risk groups with different OS [hazard ratio (HR) 5.1; P < 0.0001]. The median OS of high- and low-risk groups were 10.2 [95% confidence interval (CI) of 6.5 and 13.2 months] and 80.9 months (CI: 43.0 months and not assessable), respectively. Risk groups were independently prognostic of lymph node metastasis by multivariate analysis (HR 3.6 in node positive group, P = 0.02; HR 3.6 in high-risk group, P = 0.0002), and not prognostic in surgery only patients (n = 118; log rank P = 0.2). A validation cohort independently confirmed these findings. Conclusions: These results suggest that gene-based risk groups can independently predict prognosis in gastroesophageal cancer patients treated with neoadjuvant chemotherapy. This signature and associated assay may help risk stratify these patients for post-surgery chemotherapy in future perioperative chemotherapy-based clinical trials.

Indexed as

AdultAgedAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorChemotherapy, AdjuvantEsophageal NeoplasmsEsophagectomyEsophagusFemaleGastrectomyGene Expression ProfilingHumansKaplan-Meier EstimateMaleMiddle AgedNeoadjuvant TherapyBiomarkers, Tumor

Identifiers

PMID30481267
PMCPMC6311954
OpenAlexW2903543725

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.