Foxp3+IL-17+ T cells promote development of cancer-initiating cells in colorectal cancer
Bibliographic record
Abstract
The pathogenesis of CRC remains to be further understood. This study was designed to elucidate the role of Foxp3+IL-17+ T cells in the pathogenesis of CRC. Surgically removed CRC tissue was collected from 12 patients with CRC. The frequency and cytokine profile of Foxp3+IL-17+ T cells in CRC were examined by flow cytometry. Chemokine CXCL11 was examined in CRC tissue by Western blotting. Treg chemotaxis was examined in a transwell system. The effect of Foxp3+IL-17+ T cells on induction of cancer-initiating cells was examined; the latter's Akt and MAPK activities and colony formation were examined afterward. Abundant Foxp3+IL-17+ T cells were detected in CRC tissue that expresses high levels of TGF-β, CXCR3, CCR6, and RORγt. High levels of CXCL11 were detected in CRC tissue-derived CD68+ cells, which had a strong chemotactic effect on Foxp3+ Tregs. Hypoxia induced the expression of IL-17 in Foxp3+ Tregs; Foxp3+IL-17+ T cells were capable of inducing CRC-associated cell markers in BMMo and drove the cells to be cancer-initiating cells. High levels of phosphorylated Akt and MAPK were detected in the induced cancer-initiation cells; the latter has the capability to form a colony. CRC tissue-derived Foxp3+IL-17+ cells have the capacity to induce cancer-initiating cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".