Abstract 2739

Chronic Myeloid Leukemia (CML) is caused by the BCR-ABL1 fusion. It is however unknown if CML patients at diagnosis harbor additional genetic mutations and whether these mutation, if present, contribute to the clinical course of the disease and to the response to tyrosine kinase inhibitors (TKIs).To this aim 8 CML patients (pts) in Chronic Phase (CP) were studied at diagnosis after informed consent and before any specific treatment. Mononuclear cells were obtained from the Peripheral Blood or the Bone Marrow (BM) and consisted of >80% myeloid cells, as evaluated by FACS analysis. Lymphocytes were obtained from PB samples, after culture with PHA/IL2 for 2–3 weeks and consisted of >80% Ph negative lymphoid cells. The exon-capture protocol was performed on myeloid leukemic cells and normal lymphocytes from the same patients using the Illumina TruSeq Exome Enrichment Kit. The enriched DNA was sequenced with a Genome Analyzer IIx (Illumina), using a 60 bases paired-end run protocol and the TruSeq chemistry. On average, 10 Gigabases per exome were generated. The bioinformatic analysis was performed using the Galaxy framework (http://main.g2.bx.psu.edu/); the cross-match between leukemic and normal exomes was performed with dedicated in-house C# software.

The percentage of reads matching the reference human genome was over 90%, with a mean exon coverage of over 73-fold and a percentage of exons with a mean coverage ≥ 20x of over 90% for both the leukemic sample and the control. A total of 61 non synonymous heterozygous somatic mutations were identified (range 1–26/pt), vs 40 synonymous mutations (range 0–20/pt) which were present in ≥35% of reads, corresponding to ≥88% of cells analyzed.A positive correlation (r=0.55, p=0.03) was found between pt age and number of mutations identified, but not with other clinical variables such as Sokal score. Among the 61 variants, 31.4% ranked more than 1.0 and 19.7% more than 2.0 in the GeneRanker cancer scoring system (http://cbio.mskcc.org/tcga-generanker/), including genes such as ASXL1, PATZ1, MAP3K4 and ROR2. The average number of total mutations (see Table) did not differ between pts with positive and negative clinical course (7.3 vs 7.6). However, pts who showed a negative clinical course tended to have more mutations with high scores than pts who responded to first line TKI therapy (7.7±3.7 vs. 3.4±2.8 p=0.08).

These data show that genetic alterations (including genes known to cause cancer) are usually present at the time of CML diagnosis, in addition to the BCR-ABL1 fusion. This fact does not necessarily impair the effect of TKI treatment. The number of mutations is proportional to pt age and pts with TKI treatment failure tend to have a higher number of mutations known to be involved in malignant transformation.

Patient Characteristics

PtAgeSokal scoreSynonimous mutationsNon-synonimous mutationsMCyR by 9 months on imatinib
25 0.8 Yes 
23 0.8 No 
68 1.6 20 26 Yes 
55 2.6 11 15 No 
52 0.66 Yes 
45 0.01 Yes 
49 0.65 Yes 
22 1.52 No 
PtAgeSokal scoreSynonimous mutationsNon-synonimous mutationsMCyR by 9 months on imatinib
25 0.8 Yes 
23 0.8 No 
68 1.6 20 26 Yes 
55 2.6 11 15 No 
52 0.66 Yes 
45 0.01 Yes 
49 0.65 Yes 
22 1.52 No 

Disclosures:

No relevant conflicts of interest to declare.

Author notes

*

Asterisk with author names denotes non-ASH members.

Sign in via your Institution