PAX6 upstream antisense RNA (PAUPAR) inhibits colorectal cancer progression through modulation of the microRNA (miR)-17-5p / zinc finger protein 750 (ZNF750) axis
Bibliographic record
Abstract
Researchers have demonstrated that long non-coding RNAs (lncRNAs) are vital in colorectal cancer (CRC) progression. Here, we aimed to explore the function of lncRNA PAX6 upstream antisense RNA (PAUPAR) in the development of CRC. In the present study, PAUPAR and microRNA (miR)-17-5p expression levels in CRC tissues and cells were examined using quantitative real-time polymerase chain reaction (qRT-PCR). Western blot analysis was adopted to examine ZNF750 expression at the protein level in CRC cells. CRC cell proliferation was examined by colony formation experiment and 5-Bromo-2-deoxyUridine (BrdU) experiment. CRC cell migration and invasion were assessed by Transwell experiments. Apoptosis was measured using the TUNEL experiment. The targeting relationship between PAUPAR and miR-17-5p was confirmed using dual-luciferase reporter gene and RNA immunoprecipitation (RIP) experiments. We demonstrated that PAUPAR was markedly down-modulated in CRC, and its low expression was significantly related to increased T stage and local lymph node metastasis. Knockdown of PAUPAR enhanced CRC cell proliferation, migration and invasion, and restrained apoptosis relative to controls, whereas PAUPAR overexpression caused the opposite effects. Moreover, rescue experiments showed that miR-17-5p inhibitor could reverse the role of PAUPAR knockdown on the malignant phenotypes of CRC cells. Additionally, PAUPAR could positively regulate the expression of ZNF750 via repressing miR-17-5p. Taken together, these findings suggest that PAUPAR/miR-17-5p/ZNF750 axis is a novel mechanism implicated in CRC progression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".