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.

Genetic Landscape of Ultra-Stable Chronic Lymphocytic Leukemia Patients.
Paper ID
Raponi S, Del Giudice I, Marinelli M, Wang J, Cafforio L, Ilari C, Piciocchi A, Messina M, Bonina S, Tavolaro S, Bordyuh M, Mariglia P, Peragine N, Mauro FR, Chiaretti S, Molica S, Gentile M, Visentin A, Trentin L, Rigolin GM, Cuneo A, Diop F, Rossi D, Gaidano G, Guarini A, Rabadan R and Foà R
Hematology, Department of Cellular Biotechnologies and Hematology, Sapienza University, Rome, Italy.
Annals of oncology : official journal of the European Society for Medical Oncology, 2018
ISSN: 1569-8041
PMID: 29365086 (view at PubMed or Europe PMC)
Background: Chronic lymphocytic leukemia (CLL) has a heterogeneous clinical course. Beside patients requiring immediate treatment, others show an initial indolent phase followed by progression and others do not progress for decades. The latter two subgroups usually display mutated IGHV genes and a favorable FISH profile.Patients with absence of disease progression for over 10 years (11-30) from diagnosis were defined as ultra-stable CLL (US-CLL). Forty US-CLL underwent extensive characterization including whole exome sequencing (WES), ultra-deep sequencing and copy number aberration (CNA) analysis to define their unexplored genomic landscape. Microarray analysis, comparing US-CLL with non US-CLL with similar immunogenetic features (mutated IGHV/favorable FISH), was also performed to recognize US-CLL at diagnosis.Results: WES was carried out in 20 US-CLL and 84 non-silent somatic mutations in 78 genes were found. When re-tested in a validation cohort of 20 further US-CLL, no recurrent lesion was identified. No clonal mutations of NOTCH1, BIRC3, SF3B1 and TP53 were found, including ATM and other potential progression driving mutations. CNA analysis identified 31 lesions, none with known poor prognostic impact. No novel recurrent lesion was identified: most cases showed no lesions (38%) or an isolated del(13q) (31%). The expression of 6 genes, selected from a gene expression profile analysis by microarray and quantified by droplet digital PCR on a cohort of 79 CLL (58 US-CLL and 21 non US-CLL), allowed to build a decision-tree capable of recognizing at diagnosis US-CLL patients.Conclusions: The genetic landscape of US-CLL is characterized by the absence of known unfavorable driver mutations/CNA and of novel recurrent genetic lesions. Among CLL patients with favorable immunogenetics, a decision-tree based on the expression of 6 genes may identify at diagnosis patients who are likely to maintain an indolent disease for decades.
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)