Dissemin is shutting down on January 1st, 2025

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BMJ Publishing Group, Gut, 11(70), p. 2055-2065, 2020

DOI: 10.1136/gutjnl-2020-322707

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Integrated genomic profiling and modelling for risk stratification in patients with advanced oesophagogastric adenocarcinoma

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

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Preprint: archiving allowed
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Postprint: archiving allowed
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Data provided by SHERPA/RoMEO

Abstract

ObjectivePrognosis of patients with advanced oesophagogastric adenocarcinoma (mEGAC) is poor and molecular determinants of shorter or longer overall survivors are lacking. Our objective was to identify molecular features and develop a prognostic model by profiling the genomic features of patients with mEGAC with widely varying outcomes.DesignWe profiled 40 untreated mEGACs (20 shorter survivors <13 months and 20 longer survivors >36 months) with whole-exome sequencing (WES) and RNA sequencing and performed an integrated analysis of exome, transcriptome, immune profile and pathological phenotypes to identify the molecular determinants, developing an integrated model for prognosis and comparison with The Cancer Genome Atlas (TCGA) cohorts.ResultsKMT2C alterations were exclusively observed in shorter survivors together with high level of intratumour heterogeneity and complex clonal architectures, whereas the APOBEC mutational signatures were significantly enriched in longer survivors. Notably, the loss of heterozygosity in chromosome 4 (Chr4) was associated with shorter survival and ‘cold’ immune phenotype characterised by decreased B, CD8, natural killer cells and interferon-gamma responses. Unsupervised transcriptomic clustering revealed a shorter survivor subtype with distinct expression features (eg, upregulated druggable targets JAK2, MAP3K13 and MECOM). An integrated model was then built based on clinical variables and the identified molecular determinants, which significantly segregated shorter and longer survivors. All the above features and the integrated model have been validated independently in multiple TCGA cohorts.ConclusionThis study discovered novel molecular features prognosticating overall survival in patients with mEGAC and identified potential novel targets in shorter survivors.