Apigenin Targets MicroRNA-155, Enhances SHIP-1 Expression, and Augments Anti-Tumor Responses in Pancreatic Cancer
Bibliographic record
Abstract
Pancreatic cancer (PC) is a deadly disease with a grim prognosis. Pancreatic tumor derived factors (TDF) contribute to the induction of an immunosuppressive tumor microenvironment (TME) that impedes the effectiveness of immunotherapy. PC-induced microRNA-155 (miRNA-155) represses expression of Src homology 2 (SH2) domain-containing Inositol 5'-phosphatase-1 (SHIP-1), a regulator of myeloid cell development and function, thus impacting anti-tumor immunity. We recently reported that the bioflavonoid apigenin (API) increased SHIP-1 expression which correlated with the expansion of tumoricidal macrophages (TAM) and improved anti-tumor immune responses in the TME of mice with PC. We now show that API transcriptionally regulates SHIP-1 expression via the suppression of miRNA-155, impacting anti-tumor immune responses in the bone marrow (BM) and TME of mice with PC. We discovered that API reduced miRNA-155 in the PC milieu, which induced SHIP-1 expression. This promoted the restoration of myelopoiesis and increased anti-tumor immune responses in the TME of heterotopic, orthotopic and transgenic SHIP-1 knockout preclinical mouse models of PC. Our results suggest that manipulating SHIP-1 through miR-155 may assist in augmenting anti-tumor immune responses and aid in the therapeutic intervention of PC.
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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".