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.

Molecular Characterization and Putative Pathogenic Pathways of Tuberous Sclerosis Complex-Associated Renal Cell Carcinoma.
Paper ID
Park JH, Lee C, Chang MS, Kim K, Choi S, Lee H, Lee HS and Moon KC
Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Pathology, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea.
Translational oncology, 2018;11(4):962-970
ISSN: 1936-5233
PMID: 29925043 (view at PubMed or Europe PMC)
Tuberous sclerosis complex-associated renal cell carcinoma (TSC-RCC) has distinct clinical and histopathologic features and is considered a specific subtype of RCC. The genetic alterations of TSC1 or TSC2 are responsible for the development of TSC. In this study, we assessed the mTOR pathway activation and aimed to evaluate molecular characteristics and pathogenic pathways of TSC-RCC. Two cases of TSC-RCC, one from a 31-year-old female and the other from an 8-year-old male, were assessed. The mTOR pathway activation was determined by immunohistochemistry. The mutational spectrum of both TSC-RCCs was evaluated by whole exome sequencing (WES), and pathogenic pathways were analyzed. Differentially expressed genes were analyzed by NanoString Technologies nCounter platform. The mTOR pathway activation and the germline mutations of TSC2 were identified in both TSC-RCC cases. The WES revealed several cancer gene alterations. In Case 1, genetic alterations of CHD8, CRISPLD1, EPB41L4A, GNA11, NOTCH3, PBRM1, PTPRU, RGS12, SETBP1, SMARCA4, STMN1, and ZNRF3 were identified. In Case 2, genetic alterations of IWS1 and TSC2 were identified. Further, putative pathogenic pathways included chromatin remodeling, G protein-coupled receptor, Notch signaling, Wnt/β-catenin, PP2A and the microtubule dynamics pathway in Case 1, and mRNA processing and the PI3K/AKT/mTOR pathway in Case 2. Additionally, the ALK and CRLF2 mRNA expression was upregulated and CDH1, MAP3K1, RUNX1, SETBP1, and TSC1 mRNA expression was downregulated in both TSC-RCCs. We present mTOR pathway activation and molecular characteristics with pathogenic pathways in TSC-RCCs, which will advance our understanding of the pathogenesis of TSC-RCC.
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)