The pseudogene TUSC2P promotes TUSC2 function by binding multiple microRNAs
Bibliographic record
Abstract
Various non-coding regions of the genome, once presumed to be ‘junk’ DNA, have recently been found to be transcriptionally active. In particular, pseudogenes are now known to have important biological roles. Here we report that transcripts of the two tumour suppressor candidate-2 pseudogenes (TUSC2P), found on chromosomes X and Y, are homologous to the 3′-UTR of their corresponding protein coding transcript, TUSC2. TUSC2P and the TUSC2 3′-UTR share many common miRNA-binding sites, including miR-17, miR-93, miR-299-3p, miR-520a, miR-608 and miR-661. We find that ectopic expression of TUSC2P and the TUSC2 3′-UTR inhibits cell proliferation, survival, migration, invasion and colony formation, and increases tumour cell death. By interacting with endogenous miRNAs, TUSC2P and TUSC2 3′-UTR arrest the functions of these miRNAs, resulting in increased translation of TUSC2. The TUSC2P and TUSC2 3′-UTR could thus be used as combinatorial miRNA inhibitors and might have clinical applications. Non-coding RNAs have recently emerged as crucial regulators of gene expression. Here Rutnam et al.identify a pseudogene complementary to the 3′-UTR of the TUSC2 tumour suppressor that regulates TUSC2 levels by acting as a decoy for endogenous microRNAs and thereby inhibits tumorigenesis.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".