GRCh38 · COSMIC v92


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.

Genomic alterations in fatal forms of non-anaplastic thyroid cancer: Identification of MED12 and RBM10 as novel thyroid cancer genes associated with tumor virulence.
Paper ID
Ibrahimpasic T, Xu B, Landa I, Dogan S, Middha S, Seshan V, Deraje Vasudeva S, Carlson D, Migliacci J, Knauf JA, Untch BR, Berger MF, Morris LG, Tuttle RM, Chan TA, Fagin JA, Ghossein R and Ganly I
Department of Surgery, Memorial Sloan Kettering Cancer Center.
Clinical cancer research : an official journal of the American Association for Cancer Research, 2017
ISSN: 1078-0432
PMID: 28634282 (view at PubMed or Europe PMC)
Purpose. Patients with anaplastic thyroid cancer have a very high death rate. In contrast, deaths from non-anaplastic thyroid cancer are much less common. The genetic alterations in fatal non-anaplastic thyroid cancers have not been reported. <p>Experimental Design. We performed next-generation sequencing of 410 cancer genes from 57 fatal non-anaplastic thyroid primary cancers. Results were compared to The Cancer Genome Atlas study (TCGA study) of papillary thyroid cancers (PTC) and to the genomic changes reported in anaplastic thyroid cancer (ATC).</p> <p>Results. There was a very high prevalence of TERT promoter mutations, comparable to that of anaplastic thyroid cancer, and these co-occurred with BRAF and RAS mutations. A high incidence of chromosome 1q gain was seen highlighting its importance in tumor aggressiveness. Two novel fusion genes DLG5-RET and OSBPL1A-BRAF were identified. There was a high frequency of mutations in MED12 and these were mutually exclusive to TERT promoter mutations and also to BRAF and RAS mutations. In addition, a high frequency of mutations in RBM10 were identified and these co-occurred with RAS mutations and PIK3CA mutations. Compared to the PTCs in TCGA, there were higher frequencies of mutations in TP53, POLE, PI3K/AKT/mTOR pathway effectors, SWI/SNF subunits, and histone methyltransferases.</p> <p>Conclusions. These data support a model whereby fatal non-anaplastic thyroid cancers arise from well-differentiated tumors through the accumulation of key additional genetic abnormalities. The high rate of TERT promoter mutations, MED12 mutations, RBM10 mutations and chromosome 1q gain highlight their likely association with tumor virulence.
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]
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)