Abstract PD10-08: PD10-08 Immune cell infiltration associated with poor anti-proliferative response to aromatase inhibitors in postmenopausal women with primary ER-positive HER2-negative breast cancer
Bibliographic record
Abstract
Abstract Background: Aromatase inhibitors (AIs) are one of the main treatment strategies for the clinical management of estrogen receptor-positive (ER+) breast cancer (BC). Despite prolonged time to recurrence and initial clinical responses, >20% of patients eventually relapse, and previous studies have shown an association of poor anti-proliferative response to AIs and worse outcome. High immune activity in ER+ tumors may be associated with worse outcome, in contrast to ER-negative BC where immune infiltration is a feature associated with better outcome. Our work focused on understanding the correlations between immune cell infiltration and response to AI. Methods: All patients with ER+ HER2- tumors within the bottom 15% of Ki67 anti-proliferative responders to AIs (poor responders [PRs]; n=177) were selected from the PeriOperative Endocrine Therapy for Individualizing Care (POETIC) trial and matched on baseline Ki67 levels to good responders (GRs) within the 50% showing the best response (n=190). Response to AI was measured by the Ki67 percentage change after 2 weeks of treatment. PRs were further divided into groups expressing high ESR1 (PRs ESR1HIGH; n=119) and low ESR1 (PRs ESR1LOW; n=58) levels to represent PR subgroups that showed partial or no response to AIs. The percentage of stromal tumor-infiltrating lymphocytes (TILs) was assessed. Multiple immunofluorescence was performed for ER, CD3, CD20, CD68, FOXP3, and CD3/FOXP3 in 15 baseline samples from each of the GR, PR ESR1HIGH, and PR ESR1LOW populations and immune cell density in stromal or tumor compartments was estimated. Spearman correlations of TILs with Consensus tumor microenvironment (TME) deconvolution and Molecular Signatures Database hallmark gene sets were conducted. The relationship between the immune markers’ density and genes, hallmark gene sets and Consensus TME was assessed. Results: The percentage of TILs was significantly higher in the PR ESR1HIGH and PR ESR1LOW compared to the GRs (adjusted p< 0.05). As expected, TILs were highly correlated with T cells (particularly T-regulatory cells) and immune hallmark gene sets. There was a tendency for higher density of each of the immune markers in PRs compared to GRs, with significant differences being observed in stromal B-cell marker CD20 density (p< 0.05). Analysis showed a significant correlation between TILs and stromal FOXP3 marker density (FDR< 0.05), and stromal biomarker density was highly correlated to the gene expression of the encoding genes of the same tumors (CD3/CD3D, FOXP3/FOXP3, and CD20/MS4A1) (FDRs< 0.05). There was also a strong and significant correlation between the stromal expression of CD20, CD3, FOXP3, and CD3/FOXP3 with the immune hallmark gene sets (FDRs< 0.05). Finally, the immune phenotyping showed the expected correlations with TME deconvolution, with particularly strong correlations of CD20 and CD3 with B- and T-cell gene signatures, respectively (FDRs< 0.05). Conclusions: Different immune features indicated a broad involvement of several immune cell types in PRs to AIs, suggesting that the immune system might be associated with resistance of ER+ breast tumors to AI treatment. Spatial gene expression profiling is ongoing to characterize these tumors further and investigate potential mechanisms of AI resistance. Citation Format: Anastasia Alataki, Gene Schuster, Lila Zabaglo, Perry Maxwell, Elena López-Knowles, Elizabeth Folkerd, David Evans, Kally Sidhu, Holly Tovey, Nicholas Turner, Stephen Johnston, Maggie Chon U Cheang, John Robertson, Manuel Salto-Tellez, Ian Smith, Judith Bliss, Mitch Dowsett. PD10-08 Immune cell infiltration associated with poor anti-proliferative response to aromatase inhibitors in postmenopausal women with primary ER-positive HER2-negative breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD10-08.
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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 | 0.000 | 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) | 0.002 | 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".