Microenvironmental interleukin-6 suppresses toll-like receptor signaling in human leukemia cells through miR-17/19A
Bibliographic record
Abstract
The regulation of toll-like receptor (TLR) signaling in a tumor microenvironment is poorly understood despite its importance in cancer biology. To address this problem, TLR7-responses of chronic lymphocytic leukemia (CLL) cells were studied in the presence and absence of a human stromal cell-line derived from a leukemic spleen. CLL cells alone produced high levels of tumor necrosis factor (TNF)-α and proliferated in response to TLR7-agonists. A signal transducer and activator of transcription 3 -activating stromal factor, identified as interleukin (IL)-6, was found to upregulate microRNA (miR)-17 and miR-19a, target TLR7 and TNFA messenger RNA, and induce a state of tolerance to TLR7-agonists in CLL cells. Overexpression of the miR-17-92 cluster tolerized CLL cells directly and miR-17 and miR-19a antagomiRs restored TLR7-signaling. Inhibition of IL-6 signaling with antibodies or small-molecule Janus kinase inhibitors reversed tolerization and increased TLR7-stimulated CLL cell numbers in vitro and in NOD-SCIDγc (null) mice. These results suggest IL-6 can act as tumor suppressor in CLL by inhibiting TLR-signaling.
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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 | 0.001 |
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; 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".