Contemporaneous Inflammatory, Angiogenic, Fibrogenic, and Angiostatic Cytokine Profiles of the Time-to-Tumor Development by Cancer Cells to Orchestrate Tumor Neovascularization, Progression, and Metastasis
Bibliographic record
Abstract
Cytokines can promote various cancer processes, such as angiogenesis, epithelial to mesenchymal transition (EMT), invasion, and tumor progression, and maintain cancer stem-cell-like (CSCs) cells. The mechanism(s) that continuously promote(s) tumors to progress in the TME still need(s) to be investigated. The data in the present study analyzed the inflammatory, angiogenic, fibrogenic, and angiostatic cytokine profiles in the host serum during tumor development in a mouse model of human pancreatic cancer. Pancreatic MiaPaCa-2-eGFP cancer cells were subcutaneously implanted in RAG2xCγ double mutant mice. Blood samples were collected before cancer cell implantation and every week until the end point of the study. The extracted serum from the blood of each mouse at different time points during tumor development was analyzed using a Bio-Plex microarray analysis and a Bio-Plex 200 system for proinflammatory (IL-1β, IL-10, IFN-γ, and TNF-α) and angiogenic and fibrogenic (IL-15, IL-18, basic FGF, LIF, M-CSF, MIG, MIP-2, PDGF-BB, and VEGF) cytokines. Here, we find that during cancer cell colonization for tumor development, host angiogenic, fibrogenic, and proinflammatory cytokine profiling in the tumor-bearing mice has been shown to significantly reduce host angiostatic and proinflammatory cytokines that restrain tumor development and increase those for tumor growth. The proinflammatory cytokines IL-15, IL-18, and IL-1β profiles reveal a significant host serum increase after day 35 when the tumor began to progress in growth. In contrast, the angiostatic cytokine profiles of TNFα, MIG, M-CSF, IL-10, and IFNγ in the host serum revealed a dramatic and significant decrease after day 5 post-implantation of cancer cells. OP treatment of tumor-bearing mice on day 35 maintained high levels of angiostatic and fibrogenic cytokines. The data suggest an entirely new regulation by cancer cells for tumor development. The findings identify for the first time how pancreatic cancer cells use host cytokine profiling to orchestrate the initiation of tumor development.
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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".