Dendritic Cell Infiltration and Prognosis of Early Stage Breast Cancer
Bibliographic record
Abstract
PURPOSE: Although dendritic cells (DC) and T cells can infiltrate primary breast carcinoma, it remains unclear whether the immune response influences the clinical outcome. EXPERIMENTAL DESIGN: T lymphocytes and DC infiltration within primary tumors was investigated in 152 patients with invasive nonmetastatic breast cancer. CD1a, CD3, CD68, CD123, CD207/Langerin, and CD208/DC-LAMP expression was assessed with semiquantitative immunohistochemical analysis. Expression of chemokines involved in DC migration (MIP-3a/CCL20, MIP-3b/CCL19, and 6Ckine/CCL21) was also examined. The correlation between these markers and the characteristics of the tumors, as well as relapse-free and overall survival was analyzed. Significant prognostic parameters were then tested in a validation series. RESULTS: Infiltration by immature CD207/Langerin+ DC was found in a third of the cancers and did not correlate with clinicopathological data. Presence of mature CD208/DC-LAMP+ DC (56%) and CD3+ T cells (82%) strongly correlated with lymph node involvement and tumor grade. Among the chemokines analyzed, only the presence of MIP-3b/CCL19 in 57% of the tumors correlated with prolonged overall survival. CD123+ plasmacytoid DC (pDC) infiltrated 13% of the primary tumors. Their presence was strongly associated with shorter overall survival (93% versus 58% at 60 months) and relapse-free survival (90% versus 37% at 60 months) and was found to be an independent prognostic factor for overall survival and relapse-free survival and confirmed in an independent validation series of 103 patients. CONCLUSIONS: Infiltration by pDC of primary localized breast tumor correlates with an adverse outcome, suggesting their contribution in the progression of breast 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 | 0.001 |
| 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) | 0.001 | 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".