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HER2-HER3 heterodimer quantification by FRET-FLIM and patient subclass analysis of the COIN colorectal trial

Research output: Contribution to journalArticle

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, Louise Brown, Richard Kaplan, Daniel Hochhauser, Richard Adams , Timothy S Maughan, Borivoj Vojnovic, Anthony C C Coolen, Tony Ng

Original languageEnglish
JournalJournal of the National Cancer Institute
Early online date18 Dec 2019
Accepted/In press11 Dec 2019
E-pub ahead of print18 Dec 2019


King's Authors


Background: The phase 3 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. Methods: HER2-HER3 dimerization was quantified by “FLIM Histology” in primary tumor samples from 550 COIN trial patients receiving oxaliplatin and fluoropyrimidine chemotherapy +/-cetuximab. Bayesian latent class analysis (LCA) and covariate reduction was performed to analyze the effects of HER2-HER3 dimer, RAS mutation and cetuximab on progression-free survival (PFS) and overall survival (OS). All statistical tests were two-sided. Results: LCA on a cohort of 398 patients revealed two patient subclasses with differing prognoses (median OS: 1624 days [95%CI=1466-1816] vs 461 [95%CI=431-504]): Class 1 (15.6%) showed a benefit from cetuximab in OS (HR=0.43 [95%CI=0.25-0.76]; p=0.004). Class 2 showed an association of increased HER2-HER3 with better OS (HR=0.64 [95%CI=0.44-0.94]; p=0.02). 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=1,630) based on 10 baseline clinicopathological and genetic covariates. Conclusions: Our 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.

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