Integrative Analysis of the Mutational Landscape of Mouse and Human AML Identifies Functionally Relevant Leukemia Disease Alleles
Bibliographic record
Abstract
Abstract t(8;21) is the most frequent chromosomal abnormality in acute myeloid leukemia (AML), occurring in 4-12% of adult and 12-30% of pediatric patients. This translocation fuses the N-terminus of AML1 to nearly the entire coding region of ETO, resulting in expression of the fusion protein AML1-ETO. Observations that mice expressing AML1-ETO develop AML only if treated with mutagenic agents have suggested that AML1-ETO requires cooperating disease alleles for leukemogenesis. Consistent with this, t(8;21)+ AML patients harbor multiple genetic abnormalities. Recent exome/genome sequencing studies have expanded the number of known mutations in t(8;21)+ AML patients; however, efforts to distinguish driver from passenger mutations have yielded few cooperative events and the requirements for AML1-ETO leukemogenesis remain largely unknown. To better define the genetic landscape in AML and distinguish driver from passenger mutations, we compared the mutational profiles of two specific AML1-ETO driven mouse models of leukemia to the mutational profiles of human AML patients. We found that the mouse models of AML1-ETO driven AML were phenotypically similar in terms of their extensive latency, myeloid progenitor immunophenotype, and the acquired secondary disease alleles. The first model relies upon the expression of AML1-ETO in transplanted p21 null cells, while the second model relies upon the expression of AML1-ETO9a, a splice variant of AML1-ETO, in transplanted wild type cells. p21 is neither disrupted, nor methylated in t(8;21)+ AML. Because loss of p21 prevents the repair of damaged DNA, leukemogenesis may occur in this model once a cooperating disease allele has been naturally acquired in an AML1-ETO positive hematopoietic progenitor. AML1-ETO9a itself deregulates the expression of several DNA repair genes, suggesting that AML1-ETO9a could similarly facilitate the acquisition of a cooperating disease allele. When we compared the mutational landscape of these murine leukemias to AML patients, we found that the murine leukemias enrich for disease alleles present in human AML (hypergeometric p ≤ 4.26x10-20) and that there is a significant tendency for disease alleles mutated in both species to possess mutations in the same protein domain (hypergeometric p ≤ 4.23x10-3). Furthermore, domains mutated in both species were affected by recurrent mutations (Spearman correlation of domain p-values r = 0.53, p ≤ 2.73x10-8). While the frequency with which various protein classes were affected by mutations was significantly different in MLL-AF9 and AML1-ETO/AML1-ETO9a positive murine AML compared to MLL-fusion and t(8;21)+ positive human AML (p = 0.049), the protein classes targeted in AML1-ETO/AML1-ETO9a murine AML vs. human t(8;21)+ AML were not significantly different (p = 0.327). To identify disease alleles capable of cooperating with AML1-ETO, we determined that of the 424 genes mutated in both species, 38 of those genes were significantly mutated in human AML (Genome MuSiC SMG FDR ≤ 30%). These 38 genes represented 45 mouse orthologues, 38 of which were significantly mutated in AML1-ETO driven murine leukemias (FDR ≤ 10%). These 38 orthologues corresponded to 32 human orthologues, 3 of which were annotated in COSMIC as cancer-related genes: TET2, PTPN11, and THRAP3. Using retroviral transduction and transplantation experiments, we demonstrated that the expression of AML1-ETO in transplanted Tet2 null cells or PTPN11 D61Y cells was sufficient for leukemogenesis. At euthanasia, mice exhibited leukocytosis, anemia, thrombocytopenia, splenomegaly, and an expansion in the myeloid progenitor compartment. Our identification of Tet2 loss as a cooperating allele implicates mutations in epigenetic regulators as potential driving events in t(8;21)+ AML, while the discovery of PTPN11 D61Y solidifies the role of constitutive MAPK signaling in t(8;21)+ AML. This integrative genetic profiling approach allowed us to accurately predict cooperating events in t(8;21)+ AML in a robust and unbiased manner, while also revealing functional convergence in mouse and human AML. Collectively, these findings illustrate the power of integrating murine and human genomic profiling to identify functionally relevant disease alleles in AML. Disclosures Levine: CTI BioPharma: Membership on an entity's Board of Directors or advisory committees; Loxo Oncology: Membership on an entity's Board of Directors or advisory committees; Foundation Medicine: Consultancy.
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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 | 0.000 |
| 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".