GRCh38 · COSMIC v87


This section shows a general overview of information for the selected study (COSU identifier) or publication (COSP identifier). Studies may have been performed by the Sanger Institute Cancer Genome Project, or imported from the ICGC/TCGA. You can see more information on the help pages.

Metastatic tumor evolution and organoid modeling implicate TGFBR2 as a cancer driver in diffuse gastric cancer.
Paper ID
Nadauld LD, Garcia S, Natsoulis G, Bell JM, Miotke L, Hopmans ES, Xu H, Pai RK, Palm C, Regan JF, Chen H, Flaherty P, Ootani A, Zhang NR, Ford JM, Kuo CJ and Ji HP
Genome biology 2014;15(8):428
Background: Gastric cancer is the second-leading cause of global cancer deaths, with metastatic disease representing the primary cause of mortality. To identify candidate drivers involved in oncogenesis and tumor evolution, we conduct an extensive genome sequencing analysis of metastatic progression in a diffuse gastric cancer. This involves a comparison between a primary tumor from a hereditary diffuse gastric cancer syndrome proband and its recurrence as an ovarian metastasis.Results: Both the primary tumor and ovarian metastasis have common biallelic loss-of-function of both the CDH1 and TP53 tumor suppressors, indicating a common genetic origin. While the primary tumor exhibits amplification of the Fibroblast growth factor receptor 2 (FGFR2) gene, the metastasis notably lacks FGFR2 amplification but rather possesses unique biallelic alterations of Transforming growth factor-beta receptor 2 (TGFBR2), indicating the divergent in vivo evolution of a TGFBR2-mutant metastatic clonal population in this patient. As TGFBR2 mutations have not previously been functionally validated in gastric cancer, we modeled the metastatic potential of TGFBR2 loss in a murine three-dimensional primary gastric organoid culture. The Tgfbr2 shRNA knockdown within Cdh1-/-; Tp53-/- organoids generates invasion in vitro and robust metastatic tumorigenicity in vivo, confirming Tgfbr2 metastasis suppressor activity.Conclusions: We document the metastatic differentiation and genetic heterogeneity of diffuse gastric cancer and reveal the potential metastatic role of TGFBR2 loss-of-function. In support of this study, we apply a murine primary organoid culture method capable of recapitulating in vivo metastatic gastric cancer. Overall, we describe an integrated approach to identify and functionally validate putative cancer drivers involved in metastasis.
Paper Status
Genes Analysed
Mutated Samples
Total No. of Samples

Mutation Matrix

This section shows the correlation plot between the top 20 genes and samples. There is more information in our help pages.


This table shows genes with mutations in the selected study/paper [more details]
Genes Mutated Samples
This table shows genes without mutations in the selected study/paper [more details]

Table Information


This is a whole exome/systematic screen paper and the negatives for this paper should be inferred.


This tab shows genes with mutations in the selected study/paper [more details]

Genes Samples CDS Mutation AA Mutation

This tab shows non coding variant in the selected study/paper [more details]

Sample ID Sample Name ID NCV Annotation Zygosity Chromosome Genome start Genome stop Genome version Strand WT seq Mut seq FATHMM-MKL

This tab shows the gene expression and copy number variation data for this study [more details]

Table Information


The table currently shows only high value (numeric) copy number data. Copy number segments are excluded if the total copy number and minor allele values are unknown.

Click here to include all copy number data. For more detailed information about copy number data and gain/loss definitions click here.

Sample Gene Expression Expr Level (Z-Score)

Over Expressed; Z-Score > 2.0

Under Expressed; Z-Score < -2.0

Normal; Z-Score within the range -2.0 to 2.0

CN Type Minor Allele Copy Number CN Segment Posn. Average Ploidy

1. N/A represents cases where the average ploidy value is not available( mostly ICGC samples). For some TCGA samples where the minor allele information is not available the average ploidy value could not be calculated.

2. For TCGA samples, the ASCAT algorithm was used to calculate the average ploidy.

3. For CGP samples, the PICNIC algorithm was used to calculate the average ploidy.


This table lists the samples in the selected study which have low/high methylation for each gene. [more details]

No data

This tab shows the fusion mutations observed in this sample [more details]

Gene Sample Name Id Sample(COSS) CDS Mutation Somatic status Zygosity Validated Type


This table shows mutated samples in the selected study/paper.

Sample Name Mutation Count

This table shows samples without mutations in the selected study/paper.

Non-Mutant Samples Sample Id (COSS)