GRCh38 · COSMIC v91


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.

Targeted deep sequencing improves outcome stratification in chronic myelomonocytic leukemia with low risk cytogenetic features.
Paper ID
Palomo L, Garcia O, Arnan M, Xicoy B, Fuster F, Cabezón M, Coll R, Ademà V, Grau J, Jiménez MJ, Pomares H, Marcé S, Mallo M, Millá F, Alonso E, Sureda A, Gallardo D, Feliu E, Ribera JM, Solé F and Zamora L
MDS Research Group, Josep Carreras Leukaemia Research Institute, ICO-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Badalona, Spain.
Oncotarget, 2016
ISSN: 1949-2553
PMID: 27486981 (view at PubMed or Europe PMC)
Clonal cytogenetic abnormalities are found in 20-30% of patients with chronic myelomonocytic leukemia (CMML), while gene mutations are present in >90% of cases. Patients with low risk cytogenetic features account for 80% of CMML cases and often fall into the low risk categories of CMML prognostic scoring systems, but the outcome differs considerably among them. We performed targeted deep sequencing of 83 myeloid-related genes in 56 CMML patients with low risk cytogenetic features or uninformative conventional cytogenetics (CC) at diagnosis, with the aim to identify the genetic characteristics of patients with a more aggressive disease. Targeted sequencing was also performed in a subset of these patients at time of acute myeloid leukemia (AML) transformation. Overall, 98% of patients harbored at least one mutation. Mutations in cell signaling genes were acquired at time of AML progression. Mutations in ASXL1, EZH2 and NRAS correlated with higher risk features and shorter overall survival (OS) and progression free survival (PFS). Patients with SRSF2 mutations associated with poorer OS, while absence of TET2 mutations (TET2wt) was predictive of shorter PFS. A decrease in OS and PFS was observed as the number of adverse risk gene mutations (ASXL1, EZH2, NRAS and SRSF2) increased. On multivariate analyses, CMML-specific scoring system (CPSS) and presence of adverse risk gene mutations remained significant for OS, while CPSS and TET2wt were predictive of PFS. These results confirm that mutation analysis can add prognostic value to patients with CMML and low risk cytogenetic features or uninformative CC.
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 all copy number data. This includes non-numeric data with descriptive definitions of gain/loss.

To Include only high value (numeric) copy number data, please click here. 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)