A Single Nucleotide Polymorphism Of Growth Factor Independence 1 (GFI136N) is a Novel Prognostic Marker For The Progression Of Myelodysplastic Syndrome To Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Myelodysplastic syndromes (MDS) are characterized by disturbances in the development of different blood lineages, which can progress to AML. The knowledge about the factors predisposing the development of AML is sparse. Growth factor independence 1 is a transcription factor regulating the differentiation of myeloid cells. Previously a Single Nucleotid Polymorphism (SNP) of Gfi1, denominated Gfi136N, had been described. This variant is characterized by a SNP leading to the replacement of Serine at position 36 to an Asparagine. This SNP is found in 5-7% of all Caucasians and in 10-15% of all AML patients. We sought to investigate whether Gfi136N could be a novel predictive marker for the development of AML in MDS patients. To this end, we characterized 201 patients with regard to presence of the Gfi136N variant. Patients were recruited from different German centers treating MDS patients, i.e. Essen, Düsseldorf and Dresden. Within this cohort, about 10% were heterozygous for Gfi136N. There was no difference between MDS patients heterozygous for Gfi136N or homozygous for Gfi136S with regard to age, sex, cytogenetic or IPSS score. Presence of Gfi136N significantly increased incidence (Odds ratio 2 fold) and shortened latency to AML progression (around 2 years for Gfi136N heterozygous patients compared to around 6 years for Gfi136S homozygous patients (p=0.001). To further investigate the role of Gfi136N in AML development, we generated mice expressing either the wildtype form of human Gfi1 (Gfi136S) or Gfi136N. We mated these mice with mice expressing the Nup98HoxD13 transgene. Mice expressing Nup98HoxD13 develop a MDS like disease and about 20-30% progress to AML. Mice with Nup98HoxD13 and Gfi136N alleles (n=10) developed AML with a higher incidence (60% compared to 20%) and shorter latency (200 days compared to 340 days) than mice with Nup98HoxD13 and Gfi136S alleles. (n=8, p=0.05) To confirm our finding, we used additional murine AML models resembling human AML cells. MLL-AF9 and AML1-ETO9a are recurrent so called oncofusionproteins, which are charateristic for different human AML subtypes. By retroviral transduction of murine Lineage negative (Lin neg) cells, murine leukemia resembling human AML can be generated. We transduced Lin neg cells from Gfi136S and Gfi136N mice with retroviruses expressing the onocfusionporteins MLL-AF9 or AML1-ETO9a. After seeding in semi-solid medium, transduced Gfi136N cells generated more colonies with a higher cell number than transduced Gfi136S cells (2-4 fold more cells or colonies, depending on the oncofusionprotein, p=0.05). In summary, our data suggest that Gfi136N is a novel predictive marker for AML development among MDS patients which can be recapitulated in mice. To investigate the reason behind this observation, we analyzed lineage negative ckit pos blood cells from Gfi136N or Gfi136S homozygous mice. Genome-wide analysis of histone modification showed that mice expressing the 36N variant display globally higher levels of diMeH3K4 and AcH3K9 activation marks with a significant positive correlation between them. We analyzed the genes, which had a higher level of activation marks in Gfi136N cells compared to Gfi136S. We found that pathways involved in cytokine signaling, hematopoietic lineage development and AML genesis were overrepresented among these genes. Thus we show that Gfi136N might play a crucial role in AML development of MDS patients by inducing epigenetic changes, which promote AML development. Disclosures: Germing: Celgene: Honoraria, Research Funding; Jansen-Cilag: Honoraria; Novartis: Research Funding; GSK: Research Funding; Amgen: Research Funding. Platzbecker:Celgene: Honoraria, Research Funding; Novartis: Honoraria, 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 | 0.001 |
| 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".