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. DESIGN: 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. CONCLUSION: 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.
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. DESIGN: 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. CONCLUSION: 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.
Authors: Oscar Krijgsman; Daniëlle Israeli; Hendrik F van Essen; Paul P Eijk; Michel L M Berens; Clemens H M Mellink; Aggie W Nieuwint; Marjan M Weiss; Renske D M Steenbergen; Gerrit A Meijer; Bauke Ylstra Journal: Cell Oncol (Dordr) Date: 2012-11-02 Impact factor: 6.730
Authors: Jennifer B Dennison; Maria Shahmoradgoli; Wenbin Liu; Zhenlin Ju; Funda Meric-Bernstam; Charles M Perou; Aysegul A Sahin; Alana Welm; Steffi Oesterreich; Matthew J Sikora; Robert E Brown; Gordon B Mills Journal: Clin Cancer Res Date: 2016-05-12 Impact factor: 12.531
Authors: A C West; K Tang; H Tye; L Yu; N Deng; M Najdovska; S J Lin; J J Balic; E Okochi-Takada; P McGuirk; B Keogh; W McCormack; P S Bhathal; M Reilly; M Oshima; T Ushijima; P Tan; B J Jenkins Journal: Oncogene Date: 2017-05-08 Impact factor: 9.867
Authors: Razvan Cristescu; Jeeyun Lee; Michael Nebozhyn; Kyoung-Mee Kim; Jason C Ting; Swee Seong Wong; Jiangang Liu; Yong Gang Yue; Jian Wang; Kun Yu; Xiang S Ye; In-Gu Do; Shawn Liu; Lara Gong; Jake Fu; Jason Gang Jin; Min Gew Choi; Tae Sung Sohn; Joon Ho Lee; Jae Moon Bae; Seung Tae Kim; Se Hoon Park; Insuk Sohn; Sin-Ho Jung; Patrick Tan; Ronghua Chen; James Hardwick; Won Ki Kang; Mark Ayers; Dai Hongyue; Christoph Reinhard; Andrey Loboda; Sung Kim; Amit Aggarwal Journal: Nat Med Date: 2015-04-20 Impact factor: 53.440