Plasma Stromal Cell–Derived Factor-1: Host Derived Marker Predictive of Distant Metastasis in Breast Cancer
Bibliographic record
Abstract
PURPOSE: Homing of breast cancer cells to metastatic sites may be regulated by the production of stromal cell-derived factor (SDF)-1 by specific target organs, which attracts CXCR4-expressing breast cancer cells. We investigated the value of SDF-1 as a predictive blood marker of distant metastasis in breast cancer, together with a common polymorphism of SDF-1, SDF-1-3'A. EXPERIMENTAL DESIGN: Plasma samples were collected prospectively for 270 consecutive primary breast cancer patients with a median follow-up of 3.3 years. Plasma SDF-1 levels were measured using an ELISA, and the polymorphism was identified via PCR-RFLP analysis. RESULTS: Plasma SDF-1 levels were divided into two groups, low and high, based on the median SDF-1 value of 2,661 pg/mL. Patients with low SDF-1 showed an increased risk of developing distant metastasis (relative risk, 1.94; P = 0.02) and poorer breast cancer-specific survival [adjusted hazard ratio (AHR), 3.92; P = 0.007]. Patients with both low plasma SDF-1 levels and the SDF-1-3'A polymorphism showed a poorer breast cancer-specific survival (AHR, 3.98; P = 0.001) and distant disease-free survival (AHR, 2.88; P = 0.003). In a separate cohort of 22 breast cancer patients, we found no significant difference in SDF-1 levels before and posttumor resection. CONCLUSION: We found that low plasma SDF-1 is an independent host-derived predictive marker of distant metastasis in breast cancer. The prognostic value of the combination of a low plasma SDF-1 level and the SDF-1-3'A polymorphism identifies a cohort of patients with an intrinsic susceptibility for poorer survival.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".