Nuclear Localization of the NuMA-RARα/RXRα Complex Is Necessary for Leukemogenesis in hCG-NuMA-RARα Transgenic Mice.
Bibliographic record
Abstract
Abstract Acute promyelocytic leukemia (APL) is a model system for the role of aberrant transcription in cancer, and differentiation therapy in cancer treatment. APL is characterized by accumulation of abnormal promyelocytes in patient bone marrow, and by reciprocal chromosomal translocations involving retinoic acid receptor alpha (RARα). RARα heterodimerizes with the retinoid X receptor alpha (RXRα) and regulates transcription of genes associated with myeloid differentiation, in response to all trans retinoic acid (ATRA). Though PML-RARα is the most prevalent fusion gene in APL, four variant fusion genes (X-RARα) are currently known. By understanding the role that each fusion gene plays in APL, we may better understand the mechanism of this leukemia, and, by extension, the role of aberrant transcription factors and transcriptional regulation in cancer. Several lines of evidence suggest that X-RARα interact with and delocalize RXRα. We previously characterized the phenotype of the hCG-NuMA-RARα transgenic model (Sukhai et al, Oncogene, 2004). We observed that mice developed a myeloproliferative disease-like myeloid leukemia with promyelocytic features, with a variable onset peripheral blood phenotype (2–17 months). To further elucidate the role of RXRα in APL, we conditionally knocked out RXRα in hCG-NuMA-RARα mice. Phenotype analysis of NuMA-RARα+ mice was consistent with our previous results; animals developed a myeloproliferative disease-like myeloid leukemia within 4 months of birth. Hemizygous and homozygous RXRα conditional knockout mice were phenotypically normal as late as 12 months of age. The leukemic phenotype in NuMA-RARα+ mice was dependent on the presence of functional RXRα, as indicated by a progressive decrease in accumulation of promyelocytes, as well as Gr-1+, CD11b+, CD13+ and CD117+ cells in the bone marrow and peripheral blood of NuMA-RARα+ mice hemizygous and homozygous for the RXRα mutation, as compared to NuMA-RARα+ RXRα+/+ controls. We further observed that downstream target genes (e.g., C/EBPα) of NuMA-RARα were regulated in an RXRα-dependent manner, as these genes exhibited the greatest extent of deregulation in the presence of both alleles of functional RXRα, but had progressively less deregulated expression with loss of one or two functional alleles of RXRα. Furthermore, the NuMA-RARα/RXRα heterodimer was observed to bind to retinoic acid response elements in vitro. Strikingly, these observations mirrored what we observed in single transgenic mice with low vs. high transgene copy number. Mice with low copy number exhibited nuclear localization of the NuMA-RARα/RXRα complex, the greatest extent of deregulation of gene expression, and a rapid-onset phenotype. On the other hand, mice with high transgene copy number exhibited cytoplasmic localization of NuMA-RARα/RXRα, the least extent of gene deregulation, and an ameliorated leukemia similar to that observed in NuMA-RARα mice carrying the conditional mutation in RXRα. We therefore propose that NuMA-RARα cooperates with RXRa in the development of leukemia in hCG-NuMA-RARα transgenic mice, and that the localization of this complex to the nucleus is required for leukemogenesis in transgenic mice.
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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".