Pancreatic ductal-derived mesenchymal stem cells : their distribution, characterization and cytotoxic effect on pancreatic cancer cells
Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) have attracted significant attention in cancer research as a result of their accessibility, tumor-oriented homing capacity, and the feasibility of auto-transplantation. This study detected the sensitivity of pancreatic cancer cell lines (PCCs) to pancreatic-derived, engineered MSCs under different culture conditions. Pancreatic ductal tissue was extracted from adult human pancreas. MSCs were derived and expanded ex-vivo and verified to fulfil criteria for human MSCs according to the guidelines of the International Society for Cellular Therapy. MSCs were analyzed for distribution and migratory capacity to the site of pancreas and PCCs in in vivo and in vitro models, and found to have homing capacity to the pancreas and towards PCCs (MSCs were attracted to all PCCs compared to normal human A1F8 cells and they displayed significant attraction to the media obtained from cancer cells compared to normal media (p<0.05)). PCCs (BXPC3, ASPC1, Panc-1, TRM6 and HP62) were analyzed by FACS for TNF-α Related Apoptosis Inducing Ligand (TRAIL) receptors. MSCs engineered with non-secreting TRAIL (MSCnsTRAIL) and secreting TRAIL (MSCstTRAIL) and PTEN (MSCPTEN) were used for both direct and indirect co-cultures. TRAIL/PTEN expression was assessed by both ELISA and western blot analysis; higher molecular weight was observed in the MSCnsTRAIL (56kDA) compared with MSCstTRAIL (26kDa). The TRAIL content of supernanatats from MSCstTRAIL was significantly higher than MSCnsTRAIL (p<0.05). PTEN-RFP fusion protein showed a higher molecular weight of 74 kDa in comparison with endogenous PTEN (47 kDa). A real time detection of MSCs cytotoxicity on PCCs displayed proportional cancer cell death to the ratio of conditioned media used from MSCnsTRAIL, MSCstTRAIL, and MSCPTEN. Naive MSCs exhibit intrinsic cytotoxic effect on pancreatic cancer cells and this effect was potentiated by TRAIL/PTEN-engineering. This study provides a practical platform for the development of MSC-based therapy for pancreatic cancer.
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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 | 0.000 |
| 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".