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Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes


Gastric cancer, a leading cause of cancer-related deaths, is a heterogeneous disease. We aim to establish clinically relevant molecular subtypes that would encompass this heterogeneity and provide useful clinical information. We use gene expression data to describe four molecular subtypes linked to distinct patterns of molecular alterations, disease progression and prognosis. The mesenchymal-like type includes diffuse-subtype tumors with the worst prognosis, the tendency to occur at an earlier age and the highest recurrence frequency (63%) of the four subtypes. Microsatellite-unstable tumors are hyper-mutated intestinal-subtype tumors occurring in the antrum; these have the best overall prognosis and the lowest frequency of recurrence (22%) of the four subtypes. The tumor protein 53 (TP53)-active and TP53-inactive types include patients with intermediate prognosis and recurrence rates (with respect to the other two subtypes), with the TP53-active group showing better prognosis. We describe key molecular alterations in each of the four subtypes using targeted sequencing and genome-wide copy number microarrays. We validate these subtypes in independent cohorts in order to provide a consistent and unified framework for further clinical and preclinical translational research.

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Figure 1: The four distinct subtypes in GC.
Figure 2: Molecular subtype and survival association.
Figure 3: Molecular alteration landscape of ACRG GC.

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Gene Expression Omnibus


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The Asian Cancer Research Group (ACRG, is a non-profit consortium of pharmaceutical industry and academic medical centers and genomics companies dedicated to accelerating research, and ultimately improving treatment for patients affected with the most commonly-diagnosed cancers in Asia. ACRG seeks to increase and improve the knowledge of cancers prevalent in Asia by generating comprehensive genomic data sets and sharing them freely with the scientific community in order to accelerate drug discovery efforts. This study is primarily supported by the ACRG. Samsung Medical Center provided partial support through grant no. GF01140111 (K.-M.K. and J. Lee).

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Authors and Affiliations



J. Lee, C.R., A.A. and S.K. conceptualized and planned the study. M.G.C., T.S.S., J.H.L., S.T.K., W.K.K., S.H.P. and J.M.B. contributed to collection of surgical samples and associated clinical information. K.-M.K. and I.-G.D. conducted the pathology assessment. A.A., K.-M.K., A.L. and J. Lee coordinated the data generation and led the data analysis. L.G. and S.L. generated the targeted sequencing data. S.S.W. analyzed the sequencing data. J.G.J. and J.F. generated the Affymetrix gene expression and Affymetrix SNP6 data. R. Cristescu, M.N., J.C.T., K.Y., J.W., Y.G.Y., J. Liu and A.L. processed, analyzed and participated in discussions related to the genomics data. I.S. and S.-H.J. conducted the statistical analysis of the clinical data. P.T., J.H., R. Chen, X.S.Y., M.A. and D.H. participated in discussions, provided critical scientific input, analysis suggestions and logistical support toward the project. R. Cristescu, J. Lee, M.N., K.-M.K. and A.A. wrote the manuscript.

Corresponding authors

Correspondence to Andrey Loboda, Sung Kim or Amit Aggarwal.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 and Supplementary Table 1 (PDF 1209 kb)

Supplementary Data 1

Clinical Information ACRG Cohort (XLS 216 kb)

Supplementary Data 2

Case Summary and Mean Median survival time (all cohorts) (XLSX 19 kb)

Supplementary Data 3

Summarized Clinical Information TCGA SINGAPORE SMC2 cohort (XLSX 23 kb)

Supplementary Data 4

Targeted sequencing data (XLSX 376 kb)

Supplementary Data 5

Gene Signatures (XLSX 20 kb)

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Cristescu, R., Lee, J., Nebozhyn, M. et al. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes. Nat Med 21, 449–456 (2015).

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