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.

Whole-exome sequencing defines the mutational landscape of pheochromocytoma and identifies KMT2D as a recurrently mutated gene.
Paper ID
Juhlin CC, Stenman A, Haglund F, Clark VE, Brown TC, Baranoski J, Bilguvar K, Goh G, Welander J, Svahn F, Rubinstein JC, Caramuta S, Yasuno K, Günel M, Bäckdahl M, Gimm O, Söderkvist P, Prasad ML, Korah R, Lifton RP and Carling T
Yale Endocrine Neoplasia Laboratory, Yale School of Medicine, New Haven, CT, 06520.
Genes, chromosomes & cancer 2015;54(9):542-54
As subsets of pheochromocytomas (PCCs) lack a defined molecular etiology, we sought to characterize the mutational landscape of PCCs to identify novel gene candidates involved in disease development. A discovery cohort of 15 PCCs wild type for mutations in PCC susceptibility genes underwent whole-exome sequencing, and an additional 83 PCCs served as a verification cohort for targeted sequencing of candidate mutations. A low rate of nonsilent single nucleotide variants (SNVs) was detected (6.1/sample). Somatic HRAS and EPAS1 mutations were observed in one case each, whereas the remaining 13 cases did not exhibit variants in established PCC genes. SNVs aggregated in apoptosis-related pathways, and mutations in COSMIC genes not previously reported in PCCs included ZAN, MITF, WDTC1, and CAMTA1. Two somatic mutations and one constitutional variant in the well-established cancer gene lysine (K)-specific methyltransferase 2D (KMT2D, MLL2) were discovered in one sample each, prompting KMT2D screening using focused exome-sequencing in the verification cohort. An additional 11 PCCs displayed KMT2D variants, of which two were recurrent. In total, missense KMT2D variants were found in 14 (11 somatic, two constitutional, one undetermined) of 99 PCCs (14%). Five cases displayed somatic mutations in the functional FYR/SET domains of KMT2D, constituting 36% of all KMT2D-mutated PCCs. KMT2D expression was upregulated in PCCs compared to normal adrenals, and KMT2D overexpression positively affected cell migration in a PCC cell line. We conclude that KMT2D represents a recurrently mutated gene with potential implication for PCC development.
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)