GRCh38 · COSMIC v82


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 WTSI Cancer Genome Project, or imported from the ICGC/TCGA. You can see more information on the help pages.

The coding genome of splenic marginal zone lymphoma: activation of NOTCH2 and other pathways regulating marginal zone development.
Paper ID
Rossi D, Trifonov V, Fangazio M, Bruscaggin A, Rasi S, Spina V, Monti S, Vaisitti T, Arruga F, Famà R, Ciardullo C, Greco M, Cresta S, Piranda D, Holmes A, Fabbri G, Messina M, Rinaldi A, Wang J, Agostinelli C, Piccaluga PP, Lucioni M, Tabbò F, Serra R, Franceschetti S, Deambrogi C, Daniele G, Gattei V, Marasca R, Facchetti F, Arcaini L, Inghirami G, Bertoni F, Pileri SA, Deaglio S, Foà R, Dalla-Favera R, Pasqualucci L, Rabadan R and Gaidano G
Division of Hematology and 9 Laboratory of Medical Informatics, Department of Translational Medicine, Amedeo Avogadro University of Eastern Piedmont, 28100 Novara, Italy.
The Journal of experimental medicine 2012;209(9):1537-51
Splenic marginal zone lymphoma (SMZL) is a B cell malignancy of unknown pathogenesis, and thus an orphan of targeted therapies. By integrating whole-exome sequencing and copy-number analysis, we show that the SMZL exome carries at least 30 nonsilent gene alterations. Mutations in NOTCH2, a gene required for marginal-zone (MZ) B cell development, represent the most frequent lesion in SMZL, accounting for ∼20% of cases. All NOTCH2 mutations are predicted to cause impaired degradation of the NOTCH2 protein by eliminating the C-terminal PEST domain, which is required for proteasomal recruitment. Among indolent B cell lymphoproliferative disorders, NOTCH2 mutations are restricted to SMZL, thus representing a potential diagnostic marker for this lymphoma type. In addition to NOTCH2, other modulators or members of the NOTCH pathway are recurrently targeted by genetic lesions in SMZL; these include NOTCH1, SPEN, and DTX1. We also noted mutations in other signaling pathways normally involved in MZ B cell development, suggesting that deregulation of MZ B cell development pathways plays a role in the pathogenesis of ∼60% SMZL. These findings have direct implications for the treatment of SMZL patients, given the availability of drugs that can target NOTCH, NF-κB, and other pathways deregulated in this disease.
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


The negatives shown on this page are only from targeted gene screens, but does not include negatives from whole exome/systematic screens( these negatives should be inferred ).

Non-Mutant Genes Gene Id (COSG)


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)