High Levels of MFG-E8 Confer a Good Prognosis in Prostate and Renal Cancer Patients
Bibliographic record
Abstract
Milk fat globule-epidermal growth factor-8 (MFG-E8) is a glycoprotein secreted by different cell types, including apoptotic cells and activated macrophages. MFG-E8 is highly expressed in a variety of cancers and is classically associated with tumor growth and poor patient prognosis through reprogramming of macrophages into the pro-tumoral/pro-angiogenic M2 phenotype. To date, correlations between levels of MFG-E8 and patient survival in prostate and renal cancers remain unclear. Here, we quantified MFG-E8 and CD68/CD206 expression by immunofluorescence staining in tissue microarrays constructed from renal (n = 190) and prostate (n = 274) cancer patient specimens. Percentages of MFG-E8-positive surface area were assessed in each patient core and Kaplan–Meier analyses were performed accordingly. We found that MFG-E8 was expressed more abundantly in malignant regions of prostate tissue and papillary renal cell carcinoma but was also increased in the normal adjacent regions in clear cell renal carcinoma. In addition, M2 tumor-associated macrophage staining was increased in the normal adjacent tissues compared to the malignant areas in renal cancer patients. Overall, high tissue expression of MFG-E8 was associated with less disease progression and better survival in prostate and renal cancer patients. Our observations provide new insights into tumoral MFG-E8 content and macrophage reprogramming in cancer.
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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 | 0.001 | 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".