Spatial Structure of Tumor and Immune Cells Shape Outcomes in ER⁺HER2⁻ and Triple-Negative Breast Cancer
Bibliographic record
Abstract
Abstract Immune infiltration is prognostic in triple-negative breast cancer (TNBC), but its role in ER⁺/HER2⁻ disease remains unclear, and conventional scoring may overlook spatial context. We analyzed tumors from 1,037 women ≤50 years in the Young Boost Trial ( NCT00212121 ), integrating centralized pathology review, deep learning–based spatial profiling of whole-slide H&E, and multiplex immunophenotyping. In TNBC, stromal tumor-infiltrating lymphocytes (sTILs) were robustly prognostic, independent of clinicopathologic features, confirming immune burden as the dominant signal. By contrast, in ER⁺/HER2⁻ cancers, sTILs were protective only in low-grade tumors and lost significance when architectural features were considered. Instead, grade, lymphovascular invasion, central sclerosis, and spatial separation of lymphocytes and tumor cells carried stronger independent prognostic value. These findings highlight subtype-specific prognostic biology: in TNBC, immune density alone captures outcome, whereas in ER⁺/HER2⁻ disease, the interplay between immune infiltrates and tumor architecture governs prognostic associations.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".