MicroRNA<i>miR-17-5p</i>is overexpressed in pancreatic cancer, associated with a poor prognosis, and involved in cancer cell proliferation and invasion
Bibliographic record
Abstract
The microRNA-17-92 cluster is an oncogene in human B cell lymphomas and lung cancers. Previous microRNA microarray data revealed that miR-17-5p, a member of the miR-17-92 cluster, is upregulated in pancreatic cancer. However, the involvement of miR-17-5p expression in pancreatic carcinogenesis has not well been studied. In the present study, we measured the miR-17-5p expression levels in pancreatic cancer cell lines, primary cultures of normal human pancreatic ductal cells, formalin-fixed paraffin-embedded (FFPE) tissue samples derived from 80 patients who underwent pancreatectomy for pancreatic cancer and microdissected cells (including normal ductal epithelial, pancreatic intraepithelial neoplasia-1B and invasive ductal carcinoma cells) by qRT-PCR. Furthermore, we investigated the effects of upregulation of miR-17-5p expression on the proliferation and invasion of pancreatic cancer cells. We found that pancreatic cancer cells expressed higher levels of miR-17-5p than primary cultured normal ductal cells. miR-17-5p was also overexpressed in pancreatic cancer in FFPE and microdissected samples. Furthermore, analysis of macrodissected FFPE samples revealed that high miR-17-5p expression was associated with a poor prognosis (p = 0.03). In addition, in vitro experiments revealed that SUIT-2 and KP-2 pancreatic cancer cells transfected with the miR-17-5p precursor showed significantly higher cell growth ratios than the corresponding control cells (p < 0.001 and p = 0.012, respectively), as well as significantly higher numbers of invading cells (p < 0.0001 for both). The present findings suggest that miR-17-5p plays important roles in pancreatic carcinogenesis and cancer progression, and is associated with a poor prognosis in pancreatic 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".