Abstract P2-03-08: Deconstructing the molecular characteristics of ER+ HER2+ early breast cancer in the POETIC trial using multiplex immunofluorescence and gene expression profiles
Bibliographic record
Abstract
Abstract Background: POETIC was a phase III clinical trial, with patients randomised 2:1 to 2-week perioperative aromatase inhibitor (POAI) vs control for postmenopausal women with oestrogen receptor positive (ER+) early breast cancer (BC) (Smith et al., Lancet Oncology 2020). Our previous study on POETIC trial patients with ER+ human epidermal growth factor receptor 2 positive (HER2+) BC suggested both HER2 enriched subtype (HER2-E) and immune enrichment pre-POAI (baseline, B) are main drivers of poor early response to POAI (Bergamino et al., 2022). However, some patients with HER2-E or immune enriched BC at B still showed good response to POAI. In this study, we aim to further investigate a sub-cohort of ER+ HER2+ BC from the POETIC trial, including a subset of aforementioned HER2-E tumours, to further explore the multi-modal molecular characteristics of the tumours resistant to POAI. Methods: Proliferation rate was assessed as percentage of cancer cells stained by Ki67. Patient POAI response was determined by Ki67 reduction at 2 weeks of treatment. A sub-cohort of 37 patients were selected based on response and classified as poor responders (PR, reduction < 30%, n=18), good responders (GR, reduction > 90%, n=11) and good responders with HER2-E BC at B (GR, reduction > 65%, n=8). Paired B and post-POAI (surgery, S) samples were taken from each patient of the sub-cohort. Multiplex immunofluorescence (mIF) was performed on these samples, measuring the immune cell densities in stroma and tumour compartments using five biomarkers: CD3 (all T cells), CD20 (B cells), CD68 (Macrophages), FOXP3 (regulatory T cells), and CD3 FOXP3 co-expression. The samples were also profiled using Breast Cancer 360TM (NanoString, BC360), covering the expressions of 758 genes and 46 biological signatures. Wilcoxon test, hierarchical clustering and spearman correlation test were performed to compare the tumour characteristics of GR and PR. Results: In this study, two B and four S samples were not achievable for mIF experiments due to low tumour content. At B (n = 35), among the five mIF biomarker measurements in stroma and tumour, only the stromal CD3 density was significantly different between GR (median = 0.0013) and PR (median = 0.0003, p = 0.041). In GR, HER2-E BC at B were separated into immune-high and immune-low groups with mIF biomarkers at B; the immune-high group was more likely to change into luminal subtypes post-POAI, while the immune-low group remained HER2-E. After POAI, the density changes in five mIF biomarkers in stroma and CD68 in tumour were all significantly higher in PR than GR (Table 1, n of paired samples = 62). The BC360 signatures of BC p53 (p < 0.001), BC proliferation (p < 0.001), LumB (p < 0.001) and HER2-E correlation coefficients (p < 0.001) were significantly downregulated in GR after POAI, while LumA correlation coefficients (p < 0.001) were notably increased. Conclusions: Our results suggest that for this sub-cohort, increased stromal immune response is associated with poor response to 2-week POAI in ER+ HER2+ early BC. HER2-E GR display visible immune heterogeneity at B. Lower-risk BC characteristics were exhibited in GR after the 2-week treatment. Further integrating mIF imaging data and additional digital spatial profiling are ongoing to reveal additional characteristics of ER+ HER2+ BC and tumour microenvironment predicting POAI resistance. Table 1: List of medians of log2 fold changes in mIF biomarker densities between GR and PR among the 62 paired samples, and Wilcoxon test p-values. Citation Format: Xixuan Zhu, Hui Xiao, Elena López-Knowles, Milana A. Bergamino Sirvén, Anastasia Alataki, Perry Maxwell, Holly Tovey, Lucy Kilburn, Chris Holcombe, Anthony Skene, Ian Smith, John Robertson, Katherine A Hoadley, Roberto Salgado, Judith Bliss, Nicholas Turner, Manuel Salto-Tellez, Gene Schuster, Mitch Dowsett, Maggie Chon U Cheang. Deconstructing the molecular characteristics of ER+ HER2+ early breast cancer in the POETIC trial using multiplex immunofluorescence and gene expression profiles [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 P2-03-08.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".