Abstract

Abstract 126

Relapse is the major cause of treatment failure in pediatric acute lymphoblastic leukemia (ALL). Recent studies have shown a complex, dynamic architecture of clonal diversity in ALL and other leukemia subtypes, both at diagnosis and relapse. This multiclonal diversity follows a Darwinian model of evolution, and likely contributes to the selective outgrowth of therapy-resistant leukemic cells during or after chemotherapy treatment, resulting in relapse.

In order to gain more insight into the multiclonal architecture of ALL, we selected two cytogenetically normal B-cell precursor ALL patients treated according to the DCOG-ALL9 protocol who, based on a previous study (Kuiper et al, Leukemia 2010, 24:1258–64), developed relapses with only minor genomic alterations as compared to diagnosis. Patient 1 had an IKZF1 deletion (exons 4 to 8) and a 23-nt insertion in IKZF1 exon 4 at diagnosis and developed a relapse after 12 months, whereas patient 2 was IKZF1 wild-type, and developed two relapses at 32 months and 4.5 years after diagnosis, respectively. Comparison of clonal rearrangements in the Ig and TCR genes between diagnosis and relapse(s) revealed that both leukemias were genomically stable. Copy number analysis revealed an acquired intragenic PAX5 deletion at relapse in patient 1 and two acquired copy number changes in the second relapse of patient 2 (Kuiper et al., 2010). In the current study, we performed whole exome sequencing on diagnosis, remission and relapse samples of both patients, and identified and confirmed 21 and 7 somatic missense, frameshift or splicesite mutations in the diagnosis and/or relapse samples, respectively. These variants were subsequently selected for amplicon-based ultra-deep sequencing (IonTorrent PGM with 318 chip, Applied Biosystems), using 15 ng of genomic DNA (corresponding to 2,200 haploid genome copies), reaching an average read-depth of 15,000x. All amplicons were mixed at equimolar levels and barcoded per patient sample. In patient 1, 19 mutations, including the 23-nt insertion in IKZF1 exon 4, were detected in 44–52% of the reads at both diagnosis and relapse, thus confirming that this leukemia was genomically stable. Two mutations were present at subclonal levels both at diagnosis and relapse, of which one (FMN1) was detected at 4-fold higher levels in relapse (Table 1). The second patient showed substantially more subclonal variability, revealing a mutation in GHR at diagnosis that was lost at relapse, and three mutations that appeared as novel mutations in the second relapse. These latter mutations thus may have been induced during treatment of the first relapse. Three mutations were detected at subclonal levels already at diagnosis, albeit in very low amounts for RANBP17 (Table 1). Based on these findings, we conclude that i) using paired whole-exome sequencing of diagnosis, remission and relapse samples we have identified novel somatic mutations in childhood ALL, ii) amplicon-based ultra-deep sequencing allows the sensitive detection of relapse-prone subclones at diagnosis, iii) this sequencing effort provides insight into the complex dynamic architecture of clonal diversity in childhood ALL.

Table 1.

Subclonal mutations in relapsed childhood ALL patients

patientgenemutation status at relapsemean read depth per sample% variant reads
diagnosis(1st) relapse2nd relapse
1 FMN1 subclonal outgrowth 20,292 8% 34% 
1 NAT8 preserved subclone 4,249 24% 27% 
2 GHR lost 14,530 38% 0% 0% 
2 ARHGEF1 acquired 14,370 0% 0% 44% 
2 PNPLA8 acquired 19,301 0% 0% 44% 
2 IQGAP1 acquired 19,811 0% 0% 46% 
2 RANBP17 subclonal outgrowth 30,260 <0.1% <0.1% 43% 
2 RAG3A subclonal outgrowth 10,935 0.7% 1.0% 49% 
2 PTPN5 subclonal outgrowth 4,228 9% 49% 44% 
patientgenemutation status at relapsemean read depth per sample% variant reads
diagnosis(1st) relapse2nd relapse
1 FMN1 subclonal outgrowth 20,292 8% 34% 
1 NAT8 preserved subclone 4,249 24% 27% 
2 GHR lost 14,530 38% 0% 0% 
2 ARHGEF1 acquired 14,370 0% 0% 44% 
2 PNPLA8 acquired 19,301 0% 0% 44% 
2 IQGAP1 acquired 19,811 0% 0% 46% 
2 RANBP17 subclonal outgrowth 30,260 <0.1% <0.1% 43% 
2 RAG3A subclonal outgrowth 10,935 0.7% 1.0% 49% 
2 PTPN5 subclonal outgrowth 4,228 9% 49% 44% 

Disclosures:

No relevant conflicts of interest to declare.

Author notes

*

Asterisk with author names denotes non-ASH members.