GRCh38 · COSMIC v89

Overview

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.

Reference
Two classes of intrahepatic cholangiocarcinoma defined by relative abundance of mutations and copy number alterations.
Paper ID
COSP41202
Authors
Kim YH, Hong EK, Kong SY, Han SS, Kim SH, Rhee JK, Hwang SK, Park SJ and Kim TM
Affiliation
Translational Epidemiology Research Branch, Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea.
Journal
Oncotarget, 2016;7(17):23825-36
ISSN: 1949-2553
PMID: 27009864 (view at PubMed or Europe PMC)
Abstract
Intrahepatic cholangiocarcinoma (ICC) is a biliary tree-origin epithelial malignancy in liver with unfavorable clinical outcomes. Systematic genome analyses may advance our understanding of ICC pathogenesis also improving current diagnostic and therapeutic modalities. In this study, we analyzed 17 ICC tumor-vs-matched normal pairs using either whole-exome (n = 7), transcriptome sequencing (n = 7) or both platforms (n = 3). For somatic mutations, we identified recurrent mutations of previously reported genes such as KRAS, TP53, APC as well as epigenetic regulators and those of TGFβ signaling pathway. According to the abundance of somatic mutations and DNA copy number alterations (CNA), ten ICC exome cases were distinguished into two classes as those primarily driven by either somatic mutations (M class) or CNAs (C class). Compared to M class ICCs (92-147 somatic mutations; n = 5) with a relative deficit of CNAs, C class ICCs (54-84 mutations; n = 5) harbor recurrent focal CNAs including deletions involving CDKN2A, ROBO1, ROBO2, RUNX3, and SMAD4. We also show that transcriptome sequencing can be used for expression-based ICC categorization but the somatic mutation calling from the transcriptome can be heavily influenced by the gene expression level and potentially, by posttranscriptional modification such as nonsense mediated decay. Along with a substantial level of mutational heterogeneity of ICC genomes, our study reveals previously unrecognized two ICC classes defined by relative abundance of somatic mutations over CNAs or vice versa, which should be considered in the selection of genotyping platforms and sensitive screening of targets for ICC therapeutics.
Paper Status
Curated
Genes Analysed
1591
Mutated Samples
17
Total No. of Samples
17

Mutation Matrix

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

Genes

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

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

Variants

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

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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.

CNV

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

Samples

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)