The Mixed Lineage Leukemia (MLL) Fusion–Associated Gene <i>AF4</i> Promotes CD133 Transcription
Bibliographic record
Abstract
The AC133 epitope has been used as a marker for both normal and cancer stem cells from multiple tissue lineages. To identify transcription factors that regulate CD133 expression, we conducted parallel large-scale RNA interference screens in Caco-2 cancer cells that endogenously express CD133 and in engineered HEK293 cells that express CD133 from a heterologous promoter. The transcription factor AF4 was identified following a comparative analysis between the two screens. We then showed that AF4 is a promoter of CD133 transcription in multiple cancer cell lines. Knockdown of AF4 resulted in a dramatic reduction in CD133 transcript levels. Importantly, a subset of pediatric acute lymphoblastic leukemias (ALL) harbor a fusion oncogene results from a chromosomal translocation that juxtaposes the mixed-lineage leukemia (MLL) gene and the AF4 gene. An investigation of the functional role of CD133 in the MLL-AF4-dependent ALL cells revealed that CD133 was required for leukemia cell survival. Together, our findings show AF4-dependent regulation of CD133 expression, which is required for the growth of ALL cells. CD133 may therefore represent a therapeutic target in a subset of cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".