Creating a tumor-resistant microenvironment: Cell-mediated delivery of TNFα completely prevents breast cancer tumor formation in vivo
Bibliographic record
Abstract
Here, we provide the necessary proof of concept, that it is possible to metabolically create a non-permissive or "hostile" stromal microenvironment, which actively prevents tumor engraftment in vivo. We developed a novel genetically engineered fibroblast cell line that completely prevents tumor formation in mice, with a 100% protection rate. No host side effects were apparent. This could represent a viable cellular strategy for preventing and treating a variety of human cancers. More specifically, we examined the autocrine and paracrine effects of the cellular delivery of TNFα on breast cancer tumor growth and cancer metabolism. For this purpose, we recombinantly overexpressed TNFα in human breast cancer cells (MDA-MB-231) or human immortalized fibroblasts (hTERT-BJ1). Our results directly show that TNFα functions as a potent tumor suppressor. Remarkably, TNFα-expressing breast cancer cells were viable, without any significant increases in their basal apoptotic rate. However, after 4 weeks post-implantation, TNFα-expressing breast cancer cells failed to form any tumors in xenografted mice (0 tumors/10 injections), ultimately conferring 100% protection against tumorigenesis. Similarly, TNFα-overexpressing fibroblasts were also viable, without any increases in apoptosis. Significantly, complete tumor suppression was obtained by co-injecting TNFα expressing stromal fibroblasts with human breast cancer cells, indicating that paracrine cell-mediated delivery of TNFα can also prevent tumor engraftment and growth (0 tumors/10 injections). Mechanistically, TNFα induced autophagy and mitochondrial dysfunction in both epithelial cancer cells and stromal fibroblasts, preventing energy transfer from the tumor microenvironment, likely "starving" the cancer cells to death. In addition, via qRT-PCR analysis of MDA-MB-231 cells, we observed that TNFα mediated the upregulation of gene transcripts associated with inflammation and senescence [IL-1-β, IL-6, IL-8, MCP-1, COX-2, p21(WAF1/CIP1)] and downregulated known tumor-promoting genes (collagen VI and MMP2). Recombinant overexpression of TNFα receptor(s) in MDA-MB-231 cells also significantly reduced tumor growth, but was not as effective as the TNFα ligand itself in preventing tumor growth. Thus, we propose that stromal cell-mediated delivery of TNFα to human tumors [using transfected fibroblasts or mesenchymal stem cells (hMSCs)] may be a novel and effective strategy for the prevention and treatment of human cancers.
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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 | 0.000 | 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 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".