Glypican3 in genetically modified human monocyte-derived dendritic cells induced specific cytotoxity against glypican3 overexpressing human hepatocellular carcinoma cells in vitro.
Bibliographic record
Abstract
OBJECTIVE: To transduce the new hepatocellular carcinoma (HCC) specific antigen gene glypican3 (GPC3) into dendritic cells (DCs) and to observe the in vitro cytotoxic effect induced by the genetically modified DCs against the hepatocellular carcinoma cell line (HepG2). METHODS: This study was performed in China Medical University Shenyang, China from September 2007-February 2008. The design of the study was to modify DCs with GPC3 and to be used to activate human T cells and elicit a cell-mediated immune response against HepG2 in vitro. The GPC3 gene expression was identified by western blot and immunocytochemistry. The proliferation of responder cells and cytotoxicity against HepG2 were examined by water-soluble tetrazolium salt -1 and lactate dehydrogenase assay respectively. The interferon-y (IFN-y) secreted was detected by ELISA assay. RESULTS: Both Western blot and immunocytochemical analysis assured the validity of GPC3 transfection. Glypican3 modified DCs were potent in inducing responder cells proliferation and IFN-y production. The cytotoxicity in the group of GPC3 transfected DCs were (38.90+/-0.95%) at the ratio of effector cells/target cells E/T:100:1, 30.83+/-1.24% at the ratio of E/T:50:1, and 23.84+/-0.65% at the ratio of E/T:10:1, respectively (which is significant compared with other groups, p<0.001). And the GPC3 modified DCs showed ability to induce high specific cytotoxicity against HepG2 in vitro. CONCLUSION: The effector cells stimulated with DCs that were transfected with pEF-hGPC3 plasmid could effectively lyse GPC3 expressing HepG2 cells, which suggested that those genetically engineered DCs have the potential to serve as novel vaccine for HCC.
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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".