TIM-3 expression in breast cancer
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Bibliographic record
Abstract
Tumor-infiltrating lymphocytes (TILs) are predominantly present in breast cancer patients with estrogen receptor negative tumors, among whom increasing levels correlate with favorable outcomes. Nevertheless, currently available immune checkpoint inhibitors appear to benefit only a small number of women with breast cancer. Upregulation of additional immune checkpoint markers is one mechanism of resistance to current inhibitors that might be amenable to targeting with newer agents. T-cell Immunoglobulin and Mucin domain-containing molecule 3 (TIM-3) is an immune checkpoint receptor that is an emerging target for cancer immunotherapy. We investigated TIM-3 immunohistochemical expression in 3,992 breast cancer specimens assembled into tissue microarrays, linked to detailed outcome, clinico-pathological parameters and biomarkers including CD8, PD-1, PD-L1 and LAG-3. We scored and reported absolute counts for TIM-3+ intra-epithelial and stromal TILs (iTILs and sTILs), and find that breast cancer patients with TIM-3+ iTILs (≥ 1) represent a minority of cases (11%), with a predilection for basal-like breast cancers (among which 28% had TIM-3+ iTILs). TIM-3+ sTILs (≥ 2) represented 20% of cases and included more non-basal cases. The presence of TIM-3+ iTILs highly correlates with hematoxylin and eosin-stained stromal TILs and with other immune checkpoint markers (PD-1+ iTILs, LAG-3+ iTILs and PD-L1+ tumors). In prognostic analyses, early breast cancer patients with TIM-3+ iTILs have significantly improved breast cancer-specific survival whereas TIM-3+ sTILs did not reach statistical significance. In multivariate analyses, the presence of TIM-3+ iTILs is an independent favorable prognostic factor in the whole cohort as well as among ER negative patients. Our study supports TIM-3 as a target for breast cancer immunotherapy.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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