Investigating the Role of miR-29b2 in the Progression and Chemosensitivity of Acute Myeloid Leukemia
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is a hematological malignancy characterized by the rapid proliferation of abnormal myeloid cells, leading to bone marrow failure. Despite advancements in therapy, AML remains a highly fatal disease with a five-year overall survival rate of less than 30% in adult patients. A critical challenge in treating AML is the high relapse rate, occurring in more than half of patients, even after achieving complete remission. Relapse is often driven by leukemic stem cell-like characteristics of AML cells, highlighting the urgent need to identify genetic and molecular mechanisms that enable these cells to survive therapeutic stress. Understanding these mechanisms will pave the way for developing therapeutic strategies tailored to each patient based on genetic profiling, improving survival rates and treatment outcomes.MicroRNAs (miRNAs) are a class of small noncoding RNAs that target messenger RNA (mRNA) and suppress their translation into proteins. Altered expression of miRNAs in AML has functional relevance in leukemogenesis, with some miRNAs acting as oncogenes or tumour suppressors. Among these, miR29-b2 was previously shown to act in a tumour suppressive manner. Unexpectedly, a CRISPR screen conducted in our lab demonstrated that miR29b2 was essential for the survival of AML cell lines. Furthermore, high miR-29b2 levels in AML patients are associated with poor survival, suggesting that miR-29b2 may promote leukemogenesis. Together, these data suggest that miR-29b2 may have complex and context-dependent functions in AML. In this thesis, I will explore how AML cells respond to alterations in miR-29b2 expression to gain a better understanding of its function. miR-29b2 has been shown to target proteins involved in apoptotic mechanisms, suggesting it may influence AML cell chemosensitivity. Assessing whether miR-29b2 affects AML chemosensitivity will help determine its role in modulating therapeutic outcomes. Such insights may identify strategies to enhance the efficacy of existing therapies, ultimately reducing relapse rates and improving the prognosis for AML patients.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".