Evidence map›Paper›PMID 31851321›Full record

ArticleJournal of the National Cancer Institute2020

HER2-HER3 Heterodimer Quantification by FRET-FLIM and Patient Subclass Analysis of the COIN Colorectal Trial.

Paul R Barber, Gregory Weitsman, Katherine Lawler, James E Barrett, Mark Rowley, Manuel Rodriguez-Justo, David Fisher, Fangfei Gao, Iain D C Tullis, Jinhai Deng and 8 more

Abstract readValidation Study
In one paragraph

Article in Journal of the National Cancer Institute, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. Review of FRET biosensing and its application in biomolecular detection.American journal of translational research · 2023
    Review
  5. Article
  6. Article
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  8. 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

18 authors.

Paul R BarberUCL Cancer Institute, Paul O'Gorman Building, University College London, London, UK.
Gregory WeitsmanRichard Dimbleby Laboratory of Cancer Research, School of Cancer & Pharmaceutical Sciences, King's College London, London, UK.
Katherine LawlerRichard Dimbleby Laboratory of Cancer Research, School of Cancer & Pharmaceutical Sciences, King's College London, London, UK.
James E BarrettRichard Dimbleby Laboratory of Cancer Research, School of Cancer & Pharmaceutical Sciences, King's College London, London, UK.
Mark RowleyInstitute for Mathematical and Molecular Biomedicine, King's College London, Guy's Medical School Campus, London, UK.
Manuel Rodriguez-JustoUCL Cancer Institute, Paul O'Gorman Building, University College London, London, UK.
David FisherMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, London, UK.
Fangfei GaoUCL Cancer Institute, Paul O'Gorman Building, University College London, London, UK.
Iain D C TullisDepartment of Oncology, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK.
Jinhai DengRichard Dimbleby Laboratory of Cancer Research, School of Cancer & Pharmaceutical Sciences, King's College London, London, UK.
Louise BrownMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, London, UK.
Richard KaplanMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, London, UK.
Daniel HochhauserUCL Cancer Institute, Paul O'Gorman Building, University College London, London, UK.
Richard AdamsSchool of Medicine, Cardiff University, Cardiff, UK.
Timothy S MaughanDepartment of Oncology, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK.
Borivoj VojnovicDepartment of Oncology, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK.
Anthony C C CoolenInstitute for Mathematical and Molecular Biomedicine, King's College London, Guy's Medical School Campus, London, UK.
Tony NgUCL Cancer Institute, Paul O'Gorman Building, University College London, London, UK.

Funding

Cancer Research UK 16463Cancer Research UK 25350Cancer Research UK 26553Cancer Research UK C1210/A4850Cancer Research UK C1519/A10331Cancer Research UK C1519/A16463Cancer Research UK C416/A25145Cancer Research UK C7893/A26233Department of Health 11/100/50Medical Research Council G0701770Medical Research Council MC_UU_12023/20Medical Research Council MC_UU_12023/25Medical Research Council MC_UU_12023/3Medical Research Council MR/M016587/1
6 · The paper itself

Abstract

backgroundThe phase III MRC COIN trial showed no statistically significant benefit from adding the EGFR-target cetuximab to oxaliplatin-based chemotherapy in first-line treatment of advanced colorectal cancer. This study exploits additional information on HER2-HER3 dimerization to achieve patient stratification and reveal previously hidden subgroups of patients who had differing disease progression and treatment response.

methodsHER2-HER3 dimerization was quantified by fluorescence lifetime imaging microscopy in primary tumor samples from 550 COIN trial patients receiving oxaliplatin and fluoropyrimidine chemotherapy with or without cetuximab. Bayesian latent class analysis and covariate reduction was performed to analyze the effects of HER2-HER3 dimer, RAS mutation, and cetuximab on progression-free survival and overall survival (OS). All statistical tests were two-sided.

resultsLatent class analysis on a cohort of 398 patients revealed two patient subclasses with differing prognoses (median OS = 1624 days [95% confidence interval [CI] = 1466 to 1816 days] vs 461 days [95% CI = 431 to 504 days]): Class 1 (15.6%) showed a benefit from cetuximab in OS (hazard ratio = 0.43, 95% CI = 0.25 to 0.76, P = .004). Class 2 showed an association of increased HER2-HER3 with better OS (hazard ratio = 0.64, 95% CI = 0.44 to 0.94, P = .02). A class prediction signature was formed and tested on an independent validation cohort (n = 152) validating the prognostic utility of the dimer assay. Similar subclasses were also discovered in full trial dataset (n = 1630) based on 10 baseline clinicopathological and genetic covariates.

conclusionsOur work suggests that the combined use of HER dimer imaging and conventional mutation analyses will be able to identify a small subclass of patients (>10%) who will have better prognosis following chemotherapy. A larger prospective cohort will be required to confirm its utility in predicting the outcome of anti-EGFR treatment.

Indexed as

Fluorescence Resonance Energy TransferAdenocarcinomaAgedAntineoplastic Combined Chemotherapy ProtocolsBayes TheoremCapecitabineCohort StudiesColorectal NeoplasmsErb-b2 Receptor Tyrosine KinasesFemaleHumansLatent Class AnalysisMaleMicroscopyMiddle AgedOxaloacetatesCapecitabineERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesERBB3 protein, humanOxaloacetatesReceptor, ErbB-3

Identifiers

PMID31851321
PMCPMC7492762

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.