GRCh38 · COSMIC v91


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.

Nature and nurture: a case of transcending haematological pre-malignancies in a pair of monozygotic twins adding possible clues on the pathogenesis of B-cell proliferations.
Paper ID
Hansen MC, Nyvold CG, Roug AS, Kjeldsen E, Villesen P, Nederby L and Hokland P
Department of Haematology, Aarhus University Hospital, Aarhus, Denmark.
British journal of haematology, 2015;169(3):391-400
ISSN: 1365-2141
PMID: 25752595 (view at PubMed or Europe PMC)
We describe a comprehensive molecular analysis of a pair of monozygotic twins, who came to our attention when one experienced amaurosis fugax and was diagnosed with JAK2+ polycythaemia vera. He (Twin A) was also found to have an asymptomatic B-cell chronic lymphocytic leukaemia (B-CLL). Although JAK2-, Twin B was subsequently shown to have a benign monoclonal B-cell lymphocytosis (MBL). Flow cytometric and molecular analyses of the B-cell compartments revealed different immunoglobulin light and heavy chain usage in each twin. We hypothesized that whole exome sequencing could help delineating the pattern of germline B-cell disorder susceptibility and reveal somatic mutations potentially contributing to the differential patterns of pre-malignancy. Comparing bone marrow cells and T cells and employing in-house engineered integrative analysis, we found aberrations in Twin A consistent with a myeloid neoplasm, i.e. in TET2, RUNX1, PLCB1 and ELF4. Employing the method for detecting high-ranking variants by extensive annotation and relevance scoring, we also identified shared germline variants in genes of proteins interacting with B-cell receptor signalling mediators and the WNT-pathway, including IRF8, PTPRO, BCL9L, SIT1 and SIRPB1, all with possible implications in B-cell proliferation. Similar patterns of IGHV-gene usage to those demonstrated here have been observed in inherited acute lymphoblastic leukaemia. Collectively, these findings may help in facilitating identification of putative master gene(s) involved in B-cell proliferations in general and MBL and B-CLL in particular.
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)