Remolding the tumor microenvironment by bacteria augments adoptive T cell therapy in advanced-stage solid tumors
Why this work is in the frame
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Bibliographic record
Abstract
The intricate tumor microenvironment presents formidable obstacles to the efficacy of adoptive T cell therapy in the management of solid tumors by limiting the infiltration and inducing exhaustion of the transferred T cells. Here, we developed a bacterial-based adjuvant approach that augments the efficacy of adoptive T-cell therapy for solid tumor treatment. Our study reveals that intratumor injection of E. coli MG1655 normalizes tumor vasculatures and reprograms tumor-associated macrophages into M1 phenotype that produce abundant CCL5, together facilitating tumor infiltration of adoptively transferred T cells. The depletion of tumor-associated macrophages or CCL5 neutralization in vivo leads to the significantly decreased solid tumor infiltration of adoptive T cells in the presence of bacteriotherapy. This combinatorial therapy, consisting of E. coli adjuvant and adoptive T-cell therapy, effectively eradicates early-stage melanoma and inhibits the progression of pancreatic tumors. Notably, this dual strategy also strengthened the distal tumor control capabilities of adoptive T-cell therapy through the induction of in situ tumor vaccination. This dual therapeutic approach involving bacterial therapy targeting the interior of solid tumors and adoptive T-cell therapy attacking the tumor periphery exhibits potent therapeutic efficacy in achieving the eradication of advanced-stage tumors, including melanoma and hepatocellular carcinoma, by converging attacks from both inside and outside the tumor tissues.
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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) | 0.000 | 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) | 0.000 | 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