STAT3 Establishes an Immunosuppressive Microenvironment during the Early Stages of Breast Carcinogenesis to Promote Tumor Growth and Metastasis
Why this work is in the frame
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Bibliographic record
Abstract
Immunosurveillance constitutes the first step of cancer immunoediting in which developing malignant lesions are eliminated by antitumorigenic immune cells. However, the mechanisms by which neoplastic cells induce an immunosuppressive state to evade the immune response are still unclear. The transcription factor STAT3 has been implicated in breast carcinogenesis and tumor immunosuppression in advanced disease, but its involvement in early disease development has not been established. Here, we genetically ablated Stat3 in the tumor epithelia of the inducible PyVmT mammary tumor model and found that Stat3-deficient mice recapitulated the three phases of immunoediting: elimination, equilibrium, and escape. Pathologic analyses revealed that Stat3-deficient mice initially formed hyperplastic and early adenoma-like lesions that later completely regressed, thereby preventing the emergence of mammary tumors in the majority of animals. Furthermore, tumor regression was correlated with massive immune infiltration into the Stat3-deficient lesions, leading to their elimination. In a minority of animals, focal, nonmetastatic Stat3-deficient mammary tumors escaped immune surveillance after a long latency or equilibrium period. Taken together, our findings suggest that tumor epithelial expression of Stat3 plays a critical role in promoting an immunosuppressive tumor microenvironment during breast tumor initiation and progression, and prompt further investigation of Stat3-inhibitory strategies that may reactivate the immunosurveillance program.
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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 it