Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction

OCCAMS Consortium

doi:10.1002/ijc.32384

Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction

OCCAMS Consortium

Cancer Imaging

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-naïve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.

Original language	English
Pages (from-to)	3389-3401
Number of pages	13
Journal	International Journal of Cancer
Volume	145
Issue number	12
Early online date	3 May 2019
DOIs	https://doi.org/10.1002/ijc.32384
Publication status	Published - 15 Dec 2019

Keywords

Siewert classification
esophageal adenocarcinoma
gastric cancer
gastroesophageal junction
gene expression profiling

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/ijc.32384

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@article{5420545f721a4ba2b7208381f968e330,

title = "Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction",

abstract = "Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-na{\"i}ve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.",

keywords = "Siewert classification, esophageal adenocarcinoma, gastric cancer, gastroesophageal junction, gene expression profiling",

author = "{OCCAMS Consortium} and Jan Bornschein and Lorenz Wernisch and Maria Secrier and Ahmad Miremadi and Juliane Perner and Shona MacRae and Maria O'Donovan and Richard Newton and Suraj Menon and Lawrence Bower and Eldridge, {Matthew D} and Ginny Devonshire and Calvin Cheah and Richard Turkington and Hardwick, {Richard H} and Michael Selgrad and Marino Venerito and Peter Malfertheiner and Fitzgerald, {Rebecca C} and Vicky Goh",

note = "{\textcopyright} 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.",

year = "2019",

month = dec,

day = "15",

doi = "10.1002/ijc.32384",

language = "English",

volume = "145",

pages = "3389--3401",

journal = "International Journal of Cancer",

issn = "0020-7136",

publisher = "John Wiley & Sons, Ltd",

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TY - JOUR

T1 - Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction

AU - OCCAMS Consortium

AU - Bornschein, Jan

AU - Wernisch, Lorenz

AU - Secrier, Maria

AU - Miremadi, Ahmad

AU - Perner, Juliane

AU - MacRae, Shona

AU - O'Donovan, Maria

AU - Newton, Richard

AU - Menon, Suraj

AU - Bower, Lawrence

AU - Eldridge, Matthew D

AU - Devonshire, Ginny

AU - Cheah, Calvin

AU - Turkington, Richard

AU - Hardwick, Richard H

AU - Selgrad, Michael

AU - Venerito, Marino

AU - Malfertheiner, Peter

AU - Fitzgerald, Rebecca C

AU - Goh, Vicky

PY - 2019/12/15

Y1 - 2019/12/15

N2 - Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-naïve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.

AB - Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-naïve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.

KW - Siewert classification

KW - esophageal adenocarcinoma

KW - gastric cancer

KW - gastroesophageal junction

KW - gene expression profiling

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U2 - 10.1002/ijc.32384

DO - 10.1002/ijc.32384

M3 - Article

C2 - 31050820

SN - 0020-7136

VL - 145

SP - 3389

EP - 3401

JO - International Journal of Cancer

JF - International Journal of Cancer

IS - 12

ER -

Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction

Abstract

Keywords

UN SDGs

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