Characterization of the immune microenvironment and spatial phenotypes across HER2 subtypes in advanced or metastatic breast cancer.
Bibliographic record
Abstract
1037 Background: Breast cancer is defined by HER2 and hormone receptors (HR) status, which influence the clinical outcomes. HER2-positive has been traditionally defined as HER2 overexpression on immunohistochemistry (IHC score of 3+) or 2+ and ERBB2 amplification on in situ hybridization (ISH). HER2 low (IHC 1+ or 2+ and non-amplified ISH) accounts for nearly half of tumors. There is a paucity of data regarding immune subpopulations and spatial phenotypes in HER2 subtypes. We have investigated the characteristics of tumor immune microenvironment contexture across HER2 groups (HER2 + vs HER2 low vs HER2 - (0 by IHC)) focusing tumor infiltrating lymphocytes (TIL) and on immune cell dynamics, including the distribution and spatial proximity to tumor cells to potentially inform treatment selection. Methods: Formalin-fixed paraffin-embedded (FFPE) samples of patients with metastatic breast cancer who had HER2 IHC/ISH testing according to ASCO-CAP guidelines were stained and analyzed using an 8-plex immunofluorescence (mIF) panel (CD3, CD8, CD69, FOXP3, Ki67, PD-L1, PD1, PanCK). For neighborhood analysis, samples with an area > 2 mm 2 and a phenotypes density with > 2 cells/mm² were considered. A novel spatial analysis method was used to quantify the Euclidian distance between tumor cells and surrounding immune cell populations. The clustering coefficient was used to determine the connectivity of immune cell node neighbors. These findings were analyzed in relation to the clinical characteristics. Results: Tumor and stromal compartment analysis was done on 44 FFPE samples (10 HER2 - , 19 HER2 low , and 15 HER2 + ) with 84% collected from metastatic sites. HER2 status was not significantly associated HR status or overall TIL infiltration into the tumor compartment. The dominant TIL subset identified was non-regulatory CD3+ T cells as defined as CD3 + /FOXP3 - /CD8 - . HER2 - samples were more associated with lack of PD-L1 expression on intratumoral myeloid cells and PD-L1 low expression on tumor cells as compared with HER2 low and HER2 + (p = 0.06). For spatial analysis, 33 samples (6 HER2 - , 16 HER2 low and 11 HER2 + ) were considered. Macrophages and proliferating tumor cells were more abundant in HER2 - samples than HER2 low or HER2 + (p = 0.006 and p-0.027, respectively). Median distances from tumor cells to macrophages and T regs were shorter in HER2 - cases compared to HER2l ow (p < 0.001). Although the clustering coefficient were similar between HER2 groups, HER2 low group clustered mostly around macrophages while HER2 + group preferred cytotoxic T cells (CD8 + ). Conclusions: The spatial organization and density of immune cells in the HER2 low and HER2 + breast cancer microenvironment may provide insight into prognosis and guide therapeutic approaches for combination therapies and HER2-targeted immunotherapies.
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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 | 0.001 | 0.001 |
| 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".