Relapsed precursor T-cell acute lymphoblastic leukemia is characterized by resistance against chemotherapy and is frequently fatal. We aimed at understanding the molecular mechanisms resulting in relapse of T-cell acute lymphoblastic leukemia and analyzed 13 patients at first diagnosis, remission and relapse by whole exome sequencing, targeted ultra-deep sequencing, multiplex ligation dependent probe amplification and DNA methylation array. Compared to primary T-cell acute lymphoblastic leukemia, in relapse the number of single nucleotide variants and small insertions and deletions approximately doubled from 11.5 to 26. Targeted ultra-deep sequencing sensitively detected subclones that were selected for in relapse. The mutational pattern defined two types of relapses. While both are characterized by selection of subclones and acquisition of novel mutations, 'type 1' relapse derives from the primary leukemia whereas 'type 2' relapse originates from a common pre-leukemic ancestor. Relapse-specific changes included activation of the nucleotidase NT5C2 resulting in resistance to chemotherapy and mutations of epigenetic modulators, exemplified by SUZ12, WHSC1 and SMARCA4. While mutations present in primary leukemia and in relapse were enriched for known drivers of leukemia, relapse-specific changes revealed an association with general cancer-promoting mechanisms. This study thus identifies mechanisms that drive progression of pediatric T-cell acute lymphoblastic leukemia to relapse and may explain the characteristic treatment resistance of this condition. ALL-BFM 86/90, 1989-1998 INS 98 protocol based on ALL-BFM 95 40 , 1998-2003 and ALL Intercontinental (IC) -BFM 200315, 2003-2005 analyzed at the time of primary diagnosis, during remission and at relapse. Pediatric T-cell lymphoblastic leukemia evolves into relapse by clonal selection, acquisition of mutations and promoter hypomethylation ABSTRACT © F e r r a t a S t o r t i F o u n d a t i o n Methods Patients' clinical characteristicsPatients were treated according to ALL-BFM 2000 or related frontline protocols 14 IC 15 ). One patient was aged 18 at diagnosis, all others were children or adolescents. The 13 patients (Table 1) were recruited between 1993 and 2007 from the ALL-REZ BFM 2002 trials (patients T-ALL-H-A61, -E114, -F110, -KI17, -MD40, -T92, -T128) or from Schneider Children's Medical Center of Israel, Petah Tikva, Israel (patients T-ALL-H-S00169, -S00207, -S00285, -S00438, -S00456, -S00472) and selected on the basis of sufficient material being available from the time points of first diagnosis, remission and relapse. Minimal residual disease (MRD) response was assessed as described previously 2,16 (Online Supplementary Table S3).This study was approved by the institutional review boards of the Charité Universitätsmedizin Berlin and the Medical Faculty Heidelberg. Informed consent was obtained in accordance with the Declaration of Helsinki. Exome capture, target capture and Illumina sequencingThe Agilent SureSelect Target Enrichment Kit (Agilent...
Precursor T-cell acute lymphoblastic leukemia (T-ALL) represents one of the major challenges of pediatric oncology, because relapses are frequently refractory to treatment and fatal. The molecular understanding of progression to relapse in T-ALL is limited. We aimed at identifying patterns of clonal evolution and at describing mechanisms of relapse by comparing the genetic and epigenetic alterations in primary and in relapsed pediatric T-ALL. DNA from bone marrow of 13 patients with T-ALL at primary disease, remission and relapse was analyzed by a combination of multiplex ligation- dependent probe amplification (MLPA), Illumina 450k array, whole exome sequencing (WES) and targeted deep sequencing. Targeted deep sequencing was performed after target capture with Agilent HaloPlex. In the target capture design, all loci that showed somatic mutations in WES were included. Deep sequencing was done on all primary disease and relapse samples and on a subset of remission samples. Allele frequencies by HaloPlex were highly reproducible, corresponded well to allele frequencies of loci that were well covered in WES and were consistent after serial dilutions. Analysis of DNA methylation using the Illumina 450k array showed that methylation of relapse samples does not differ significantly from the methylation of the matching primary disease samples, with the variability between different patients being much larger than the variability within samples from the same patient. WES identified on average 10 single nucleotide variants (SNVs) and 1.8 small insertions and deletions (indels) in primary T-ALL and 23.2 SNVs and 2.6 indels in the corresponding relapse samples. Only about 30% of SNVs and indels identified in relapse were already detected in primary disease by WES, while most amplifications and deletions that had been detected by the combination of MLPA and read depth analysis of WES data were conserved from primary disease to relapse. Recurrently, we identified known and novel drivers of T-ALL (NOTCH1, FBXW7, PHF6, WT1, PTEN, NRAS, STAT5B). Targeted resequencing of mutated genes at high depth (median coverage 6233, 90% of targets covered >1000x) identified rare subclonal alleles with a sensitivity in the range of 10-2 to 10-4, depending on the coverage of each individual locus. This allowed us to distinguish de novo mutations that were acquired during treatment from mutations that had already been present at initial diagnosis and were selected for in relapse. Depending on the contribution of clonal selection or de novo mutations, at least two different patterns of relapse could be identified: In a smaller proportion of leukemias, all mutations present at first diagnosis were again detected in relapse, with some additional mutations that were specific for relapse. In most leukemias, the major clone at relapse had arisen from a minor subclone at primary disease and has acquired additional mutations, indicating that clonal selection was the main contributor to the evolution of relapse. In all cases, at least one genetic alteration was detected in samples from both time points. The example of activating mutations in the nucleotidase NT5C2, which have previously been proposed to contribute to resistance against nucleoside analogues, illustrates the genetic plasticity of T-ALL: Activating NT5C2 mutations were identified in 4 out of 13 relapse samples. The only activating NT5C2 mutation that was already detected in a primary disease sample at low allele frequency was not present in the corresponding relapse sample but was replaced by another activating NT5C2 mutation. This indicates that mutations acquired during treatment may outcompete subclonal mutations that were present in the primary leukemia. In at least two relapse samples, subclonal NT5C2 mutations were detected, compatible with the notion that acquisition of resistance towards chemotherapy by mutation of NT5C2 is a late event on the way to relapse. Conclusion: The acquisition of novel genetic alterations and selection of treatment resistant subclones are main contributors to T-ALL relapse. We now aim at identifying molecular signatures that characterize treatment resistant subclones, which may be included in risk stratification algorithms of primary T-ALL. Disclosures No relevant conflicts of interest to declare.
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