<i>let-7</i> MicroRNA Transfer in Pancreatic Cancer-Derived Cells Inhibits <i>In Vitro</i> Cell Proliferation but Fails to Alter Tumor Progression
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Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is still the fourth leading cause of cancer-related deaths in Western countries, with increasing incidence. Neither effective prognostic markers nor therapies exist for this cancer. MicroRNAs are potent inhibitors of protein translation, and aberrantly expressed in many cancers. Because let-7 microRNA targets the K-ras oncogene, we aimed to characterize let-7 expression and function in PDAC in vitro and in vivo. Let-7 expression was quantified by real-time RT-PCR from resected tumors and matching adjacent tissue, and in endoscopic ultrasound-guided fine needle aspiration material from patients with PDAC. Let-7 is detected by reverse transcription in situ PCR in a PDAC tissue microarray. PDAC-derived cells were transfected with plasmid-based synthetic microRNAs or by lentiviral transduction, in vitro and in vivo. Let-7 microRNA expression is strongly reduced in PDAC samples, as compared with adjacent tissue. Let-7 is present in normal acinar pancreatic cells, and lost in poorly differentiated cancer samples. In addition, let-7 expression was repressed in patients with PDAC not eligible for surgery. Restoring let-7 levels in cancer-derived cell lines strongly inhibits cell proliferation, K-ras expression, and mitogen-activated protein kinase activation, but fails to impede tumor growth progression after intratumoral gene transfer or after implantation of Capan-1 cells stably overexpressing let-7 microRNA. We describe here for the first time the extensive loss of expression of let-7 in PDAC. In addition, this study provides the initial steps for a microRNA replacement therapy for this cancer.
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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 it