The role of different GFI1-expressionlevel in the progression of MDS and AML
Bibliographic record
Abstract
The presented data of this doctoral thesis suggest that the transcription factor GFI1/Gfi1 plays an important role in the progression and manifestation of AML. AML patients with low GFI1 expression in their blasts showed an inferior prognosis and a shortend EFS and OS. Furthermore, the KD of GFI1 resulted in a block of differentiation in the bone marrow of mice. The KO and the KD of GFI1/Gfi1 lead to an enhanced AML progression in the MLL-AF9 mouse model. In addition, upregulation of Gfi1 resulted in an increase of differentiation of bone marrow cells and a decrease of monocytosis in a persisting AML. It could be shown that the KO of Gfi1 impeded AML progression whereas the KD of GFI1 accelerated AML progression in the NUP98/HOXD13 mouse model. In cooperation with the the IRCM in Canada it could also be shown that H3K9 acetylation at GFI1 target genes is increased in the bone marrow of GFI1-KD-NUP98/HOXD13 mice. Further analysis of gene expression (Gene Set Enrichement Analysis) showed an upregulation of those genes that belong to "cluster 5" which were defined by Valk et al. as a subgroup of AML patients with poor prognosis. These data suggest, that the GFI1-KD-NUP98/HOXD13 mice recapitulate the situation of AML patients with an inferior prognosis very well. Moreover, the essential role of GFI1/Gfi1 for AML progression and manifestation in AML1-ETO9a- and CBFB-MYH1- mouse models could be demonstrated. Furthermore the here depicted results open up new vistas in treating AML patients with epigenetic drugs. As well as in murine as in human leucemic bone marrow cells it could be shown that cells with low GFI1 expression responded better to the treatment with the HATi CTK7a. This could be also confirmed in first in vivo experiments. Taken together, the presented data suggest that GFI1/Gfi1 plays a level- and dose-dependent role in progression of AML in the here used mouse models and that different GFI1/Gfi1 expression levels could be exploited as new prognostic factor in order to establish a new epigenetic therapy for MDS/AML patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".