Targeting <i>LINC00673</i> expression triggers cellular senescence in lung cancer
Bibliographic record
Abstract
Aberrant expression of noncoding RNAs plays a critical role during tumorigenesis. To uncover novel functions of long non-coding RNA (lncRNA) in lung adenocarcinoma, we used a microarray-based screen identifying LINC00673 with elevated expression in matched tumor versus normal tissue. We report that loss of LINC00673 is sufficient to trigger cellular senescence, a tumor suppressive mechanism associated with permanent cell cycle arrest, both in lung cancer and normal cells in a p53-dependent manner. LINC00673-depleted cells fail to efficiently transit from G1- to S-phase. Using a quantitative proteomics approach, we confirm the modulation of senescence-associated genes as a result of LINC00673 knockdown. In addition, we uncover that depletion of p53 in normal and tumor cells is sufficient to overcome LINC00673-mediated cell cycle arrest and cellular senescence. Furthermore, we report that overexpression of LINC00673 reduces p53 translation and contributes to the bypass of Ras-induced senescence. In summary, our findings highlight LINC00673 as a crucial regulator of proliferation and cellular senescence in lung cancer.
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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".