<p>The Immunostimulative Effect and Mechanisms of a Novel Mouse Anti-Human PD-1 Monoclonal Antibody on Jurkat Lymphocytic Cells Cocultured with Hepatoma Cells</p>
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Bibliographic record
Abstract
BACKGROUND: Monoclonal antibodies (mAbs) that target the programmed cell death-1 (PD-1)/programmed death-ligand 1 (PD-L1) immune checkpoint have demonstrated substantial clinical benefit for a variety of solid tumors. However, their applications in patients with hepatocellular carcinoma (HCC) are reported with unclear molecular mechanisms. Here, we report a novel mouse anti-human PD-1 mAb that can reverse the immunosuppressive effect of HePG2 cells on Jurkat cells. MATERIALS AND METHODS: HepG2 liver cancer cells, which were induced to overexpress PD-L1 by IFN-γ, were co-cultured with PHA-activated Jurkat lymphocytic cells to investigate the immunostimulative effect and mechanisms of the 14 newly generated PD-1 mAbs. Multiple cellular and molecular biology experiments were performed in this study, such as CCK-8, ELISA, flow cytometry, immunofluorescence and Western blot. RESULTS: We found that mAb B1C4 significantly enhanced the tumor-killing cytokine secretion level by Jurkat cells in the co-culture system and increased the killing ability of Jurkat cells on HepG2 cells. Co-culture with HePG2 cells led to Jurkat cell cycle delay in S phase, and B1C4 promoted cell cycle progression from S to G2/M. Co-culture with HePG2 cells also caused apoptosis in Jurkat cells, which was inhibited by B1C4. B1C4 reversed the immunosuppression of Jurkat cells resulted from co-cultured with HePG2 cells through inhibiting PTEN and activating PI3K/AKT/mTOR signaling pathways. CONCLUSION: Our study demonstrated that anti-PD-1 mAb B1C4 could inhibit the apoptosis of Jurkat cells induced by HePG2 hepatoma cells and reverse the immunosuppressive effect of HePG2 cells on Jurkat cells. The study provides a vital basis for applying PD-1 monoclonal antibodies in the treatment of HCC and provides antibody selection for the development of novel PD-1 mAb with blocking activity.
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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) | 0.001 | 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