Antitumor Immune Responses Derived from Transgenic Expression of CD40 Ligand in Myeloma Cells
Bibliographic record
Abstract
Tumor cells engineered to express immunogenes have been used for cancer vaccines to induce the antitumor immunity and study the antitumor immune mechanisms derived from the immunogene expression. In the present study, we engineered a mouse myeloma cell line J558 with a cloned CD40 ligand (CD40L) gene. We demonstrated that (i) the engineered J558/CD40L tumor cells expressing the CD40 ligand molecule lost their tumorigenicity in syngeneic mice, and (ii) the inoculation of J558/CD40L tumor cells further lead to the protective immunity against wild-type J558 tumors. In animal studies using T-cell subset depleted mice, we further showed that the primary rejection of J558/CD40L tumors did not require T cells, but was mainly mediated by NK cells, whereas the effector phase of the protective immunity is mediated by CD8+ T cells. In addition, our data, for the first time, showed that the inoculation of engineered J558/CD40L tumor cells is able to stimulate stronger activation of dendritic cells with enhanced expression of B7-1 and ICAM-1 molecules than the wild-type J558 tumor cells Taken together, we demonstrated the antitumor effect of engineered J558/CD40L tumor cells that is mediated by the activation of the host dendritic cells in vivo. Our data indicate that the introduction of co-stimulatory CD40 ligand molecule will be useful as a new strategy of immunogene therapy against tumors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".