Chimeric antigen receptor–engineered T cells as oncolytic virus carriers
Bibliographic record
Abstract
The use of engineered T cells in adoptive transfer therapies has shown significant promise in treating hematological cancers. However, successes treating solid tumors are much less prevalent. Oncolytic viruses (OVs) have the capacity to induce specific lysis of tumor cells and indirectly impact tumor growth via vascular shutdown. These viruses bear natural abilities to associate with lymphocytes upon systemic administration, but therapeutic doses must be very high in order to evade antibodies and other components of the immune system. As T cells readily circulate through the body, using these cells to deliver OVs directly to tumors may provide an ideal combination. Our studies demonstrate that loading chimeric antigen receptor–engineered T cells with low doses of virus does not impact receptor expression or function in either murine or human T cells. Engineered T cells can deposit virus onto a variety of tumor targets, which can enhance the tumoricidal activity of the combination treatment. This concept appears to be broadly applicable, as we observed similar results using murine or human T cells, loaded with either RNA or DNA viruses. Overall, loading of engineered T cells with OVs represents a novel combination therapy that may increase the efficacy of both treatments. The use of engineered T cells in adoptive transfer therapies has shown significant promise in treating hematological cancers. However, successes treating solid tumors are much less prevalent. Oncolytic viruses (OVs) have the capacity to induce specific lysis of tumor cells and indirectly impact tumor growth via vascular shutdown. These viruses bear natural abilities to associate with lymphocytes upon systemic administration, but therapeutic doses must be very high in order to evade antibodies and other components of the immune system. As T cells readily circulate through the body, using these cells to deliver OVs directly to tumors may provide an ideal combination. Our studies demonstrate that loading chimeric antigen receptor–engineered T cells with low doses of virus does not impact receptor expression or function in either murine or human T cells. Engineered T cells can deposit virus onto a variety of tumor targets, which can enhance the tumoricidal activity of the combination treatment. This concept appears to be broadly applicable, as we observed similar results using murine or human T cells, loaded with either RNA or DNA viruses. Overall, loading of engineered T cells with OVs represents a novel combination therapy that may increase the efficacy of both treatments.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".