Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer.
OBJECTIVE
Gastric adenocarcinoma (gastric cancer, GC) is a major cause of global cancer mortality. Identifying molecular programmes contributing to GC patient survival may improve our understanding of GC pathogenesis, highlight new prognostic factors and reveal novel therapeutic targets. The authors aimed to produce a comprehensive inventory of gene expression programmes expressed in primary GCs, and to identify those expression programmes significantly associated with patient survival.


METHODS
Using a network-modelling approach, the authors performed a large-scale meta-analysis of GC transcriptome data integrating 940 gastric transcriptomes from multiple independent patient cohorts. The authors analysed a training set of 428 GCs and 163 non-malignant gastric samples, and a validation set of 288 GCs and 61 non-malignant gastric samples.


RESULTS
The authors identified 178 gene expression programmes ('modules') expressed in primary GCs, which were associated with distinct biological processes, chromosomal location patterns, cis-regulatory motifs and clinicopathological parameters. Expression of a transforming growth factor β (TGF-β) signalling associated 'super-module' of stroma-related genes consistently predicted patient survival in multiple GC validation cohorts. The proportion of intra-tumoural stroma, quantified by morphometry in tissue sections from gastrectomy specimens, was also significantly associated with stromal super-module expression and GC patient survival.


CONCLUSIONS
Stromal gene expression predicts GC patient survival in multiple independent cohorts, and may be closely related to the intra-tumoural stroma proportion, a specific morphological GC phenotype. These findings suggest that therapeutic approaches targeting the GC stroma may merit evaluation.
Cellular and Molecular Research, National Cancer Centre, Singapore.
Yonghui
Y
Wu
Heike
H
Grabsch
Tatiana
T
Ivanova
Iain Beehuat
IB
Tan
Jacinta
J
Murray
Chia Huey
CH
Ooi
Alexander Ian
AI
Wright
Nicholas P
NP
West
Gordon G A
GG
Hutchins
Jeanie
J
Wu
Minghui
M
Lee
Julian
J
Lee
Jun Hao
JH
Koo
Khay Guan
KG
Yeoh
Nicole
N
van Grieken
Bauke
B
Ylstra
Sun Young
SY
Rha
Jaffer A
JA
Ajani
Jae Ho
JH
Cheong
Sung Hoon
SH
Noh
Kiat Hon
KH
Lim
Alex
A
Boussioutas
Ju-Seog
JS
Lee
Patrick
P
Tan
D000230:Adenocarcinoma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D000367:Age Factors; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism; D002454:Cell Differentiation / Q000235:genetics; D030541:Databases, Genetic; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks / Q000235:genetics; D023281:Genomics / Q000379:methods; D006801:Humans; D009367:Neoplasm Staging; D011379:Prognosis; D012737:Sex Factors; D013274:Stomach Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D017154:Stromal Cells / Q000378:metabolism; D059467:Transcriptome; D016212:Transforming Growth Factor beta / Q000235:genetics / Q000378:metabolism
D014408:Biomarkers, Tumor; D016212:Transforming Growth Factor beta