Genomic Landscape of Relapsed Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Abstract Introduction: Despite risk stratification according to presenting clinical and genetic features, 10-25% of children with acute lymphoblastic leukemia (ALL) relapse, which is associated with a poor prognosis. Here, we sought to provide a comprehensive overview of the genetic alterations associated with relapse in ALL. Methods: We studied 93 children (27 female, 43 male) diagnosed with ALL (62 B-progenitor, 25 T-lineage) between 1987 and 2008 and treated on total therapy studies XI-XVI who experienced relapse and/or a second tumor. Age at diagnosis ranged from 3 months to 18 years. Median time to relapse was 3 years (range 3 months to 10 years). Seventy patients had a single relapse, 15 cases had 2 relapses, and 8 cases developed a second tumor of different lineage (B-cell lymphoma, chronic myeloid leukemia (n=1 each) and acute myeloid leukemia (n=6)). Diagnosis, relapse and matched normal samples (n=299) were studied using Affymetrix SNP 6.0 microarrays and whole genome or whole exome sequencing. Results: We found 2692 copy number aberrations (CNAs) with a median of 9 (range 0-109) in the diagnosis samples (n=91) compared to a median of 10 (range 0-112) in the relapse samples (n=89) and 12 (range 0-70) in subsequent samples (n=20). The number of CNAs did not differ significantly between diagnosis, relapse or subsequent samples. We identified a 7286 non-silent single nucleotide variants (SNVs) and small insertions or deletions (indels) in 5002 genes, 1392 of which were recurrent. The median number of variants was 12 (range 0-70) at diagnosis (n=91), 21 (range 0-858) at relapse (n=91; P=0.0029 v. diagnosis) and 60 (range 10-650) in subsequent samples (n=20; P<0.0001 v. diagnosis). A subset of samples revealed very high (variant range 658-1703; 7 cases, 9 samples: all relapse or subsequent samples), or high mutation burden (variant range 104-290; 12 cases, 16 samples: 2 diagnosis, 10 relapse, and 4 subsequent samples). Genes encoding mediators of DNA repair were affected in all cases with very high mutation burden, compared to 7 of the high burden cases and 18 out of 72 other cases (most commonly genes TP53, MSH2, and MUTYH; P<0.0001). The most frequently mutated genes were NOTCH1 (n=33), NRAS (n=24), CREBBP (n=20) and KRAS (n=16). Of the recurrently altered genes, only 87 genes were known to be affected in cancer (Cancer Gene Census, COSMIC database), of which 59 were affected in leukemia and lymphoma tissues, indicating that we have identified 1306 novel recurrently affected genes, most commonly C13orf40 and MKI67. Mutations in epigenetic regulators were particularly frequent, with genes mutated in at least 3 cases altered in over 60% of the cohort (e.g. CREBBP, EP300, MLL2, MLL3, KDM6A/B, CTCF, SETD2, TET2/3, and EZH2). Clonal evolution analyses showed multiple patterns of evolution, with relapses sharing either few or many variants with the diagnosis sample in a frequency that reflects both predominant clones and minor subclones propagating relapse. Variants in NOTCH1, NRAS, and CREBBP were preserved from a major clone at diagnosis in 4, 6, and 5 cases respectively, but acquired at relapse or grown out from a minor subclone at diagnosis in 3, 5, and 8 cases respectively. In contrast, variants in USH2A (n=4), FOXA1 (n=3), and purine/pyrimidine synthesis pathway genes NT5C2 (n=3), PRPS1 (n=3) and NT5C1B (n=1) were exclusively found in relapse samples. Notably, the NT5C2 mutations, which are thought to confer resistance to thiopurines, were subclonal at relapse in the majority of cases. We identified 13 cases (10 B-lineage, 3 T-lineage) in which the diagnosis and relapse were fully discordant for all CNAs and sequence mutations, only 4 of which showed a prolonged remission time (>5 years). This suggests that these patients developed a second primary malignancy and may be predisposed to leukemia development. Indeed, one case revealed focal amplifications on chromosome 1q21.1 encompassing the neuroblastoma breakpoint family genes, which are implicated in cancer development. Comprehensive germline analyses are underway. Conclusion: This study has provided detailed insight into the genetic basis of relapse, implicating multiple new genes and pathways involved in treatment resistance, demonstrating multiple patterns of clonal evolution, and revealing an unexpectedly high frequency of genetically discordant second malignancy in relapse in ALL. Disclosures Evans: Prometheus Labs: Patents & Royalties: Royalties from licensing TPMT genotyping. Mullighan:Amgen: Honoraria, Speakers Bureau; Cancer Science Institute: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Honoraria; Loxo Oncology: Research Funding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".