Oncogenic Potential of the <i>miR-106-363</i> Cluster and Its Implication in Human T-Cell Leukemia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We previously reported the identification of the Kis2 common retrovirus integration site, located on mouse chromosome X, in radiation leukemia virus-induced T-cell leukemias. Tumors with a provirus at the Kis2 locus overexpressed a novel noncoding RNA (ncRNA) with a complex splicing pattern and no polyA tail. Database upgrade revealed the presence of a microRNA (miRNA) cluster, miR-106-363, just downstream of the Kis2 ncRNAs. We found that Kis2 ncRNAs are the pri-miRNA of miR-106-363, and we present evidence that Kis2 ncRNA overexpression in mouse tumors results in miR-106a, miR-19b-2, miR-92-2, and miR-20b accumulation. We show the oncogenic potential of those miRNAs in anchorage independence assay and confirm pri-miR-106-363 overexpression in 46% of human T-cell leukemias tested. This overexpression contributes in rising miR-92 and miR-19 levels, as this is the case for miR-17-92 cluster overexpression. Furthermore, we identified myosin regulatory light chain-interacting protein, retinoblastoma-binding protein 1-like, and possibly homeodomain-interacting protein kinase 3 as target genes of this miRNA cluster, which establishes a link between these genes and T-cell leukemia for the first time.
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.
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 | 0.001 | 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 it