GRCh38 · COSMIC v87

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
Genomic Characterization of Biliary Tract Cancers Identifies Driver Genes and Predisposing Mutations.
Paper ID
COSP44991
Authors
Wardell CP, Fujita M, Yamada T, Simbolo M, Fassan M, Karlic R, Polak P, Kim J, Hatanaka Y, Maejima K, Lawlor RT, Nakanishi Y, Mitsuhashi T, Fujimoto A, Furuta M, Ruzzenente A, Conci S, Oosawa A, Sasaki-Oku A, Nakano K, Tanaka H, Yamamoto Y, Michiaki K, Kawakami Y, Aikata H, Ueno M, Hayami S, Gotoh K, Ariizumi SI, Yamamoto M, Yamaue H, Chayama K, Miyano S, Getz G, Scarpa A, Hirano S, Nakamura T and Nakagawa H
Affiliation
Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan.
Journal
Journal of hepatology 2018
ISSN:1600-0641
PUBMED:29360550
Abstract
Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous with poor response to treatments. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed large scale genome sequencing analyses on BTCs to investigate their somatic and germline driver events and characterize their genomic landscape.Methods: We analyzed 412 BTC samples from Japanese and Italian populations, with 107 whole exome sequencing (WES), 39 whole genome sequencing (WGS), and targeted sequencing of a further 266 samples. The subtypes were 136 intrahepatic cholangiocarcinomas (ICCs), 101 distal cholangiocarcinomas (DCCs), 109 peri-hilar types (PHCs), and 66 gallbladder or cystic duct cancers (GBCs/CDCs). We identified somatic alterations and searched for driver genes in BTCs, and found pathogenic germline variants of cancer-predisposing genes. We predicted cell-of-origin for BTCs by combining somatic mutation patterns and epigenetic features.Results: We identified 32 significantly and commonly mutated genes including TP53, KRAS, SMAD4, NF1, ARID1A, PBRM1, and ATR, some of which negatively affected patient prognosis. A novel deletion of MUC17 at 7q22.1 affected patient prognosis. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes such as BRCA1, BRCA2, RAD51D, MLH1, or MSH2 were detected in 11% of BTC patients.Conclusions: BTCs have distinct genetic features including somatic events and germline predisposition. These findings could be useful to establish treatment and diagnostic strategies for BTCs based on genetic information.We here analyzed genomic features of 412 BTC samples from Japanese and Italian population. 32 significantly and commonly mutated genes were identified, some of which negatively affected patient prognosis, including a novel deletion of MUC17 at 7q22.1. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes were detected in 11% of BTC patients. BTCs have distinct genetic features including somatic events and germline predisposition.
Paper Status
Curated
Genes Analysed
8351
Mutated Samples
315
Total No. of Samples
378

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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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)

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)