Abstract 1583: The tumor immune microenvironment in early breast cancer progression
Bibliographic record
Abstract
Abstract Ductal carcinoma in situ (DCIS), comprising 20% of all breast cancer diagnoses, is a neoplastic proliferation of epithelial cells confined to the luminal compartment of mammary ducts, which precedes invasive ductal carcinoma (IDC) formation. Although not all DCIS progresses to IDC, there remains no reliable method to determine which DCIS lesions are most likely to become invasive. Recent studies on paired HER2+ and triple negative DCIS and IDC, indicate biological modulation of the microenvironment as a possible mechanism of progression. In particular, the immune microenvironment plays a crucial role in modulating cancer cell behavior and invasion potential. The role of the immune microenvironment in luminal (ER/PR+, HER2+/-) DCIS progression to IDC has not been well studied, however it is an area of keen interest given that this subtype accounts for 50-65% of all diagnosed breast cancers. To address this gap in knowledge, we employed imaging mass cytometry (IMC) to evaluate the tumor immune microenvironment of co-existing luminal DCIS and IDC in patient tumor samples. IMC allows for the comprehensive analysis of up to 35 different metal-tagged antibodies simultaneously, by coupling laser ablation of the tissue with mass cytometry, while maintaining spatial integrity. Using a panel of epithelial, immune and signaling markers, we characterized the tumor microenvironment of DCIS and IDC tumor components across multiple patient samples, investigating the differences between IDC, DCIS adjacent to IDC, and distant DCIS that is further away from the IDC component, while also controlling for inter-individual heterogeneity. A segmentation mask for each image was generated using a combination of Ilastik, CellProfiler, and ImageJ open source platforms. Single-cell information was extracted and utilized to categorize cells by phenotypes and reconstruct spatial organization maps. Immune phenotype composition, cell-cell interactions, and tumor infiltrating lymphocytes (TILs) were evaluated, and nearest neighbor analysis was performed. In addition to a significant increase in TILs within IDC tumors, we observe a switch towards an immunosuppressed microenvironment between DCIS (both adjacent and distant) and IDC. This is evidenced by an increase in T regulatory cell (Treg) infiltration and Treg-CD8 T cell interactions, as well as a decrease in the proportion of CD8 T cells observed in IDC tumors. Furthermore, there is an increase in T cell infiltration in adjacent DCIS, when compared to both IDC and distant DCIS. This may indicate a more activated immune microenvironment phenotype in these tumors. Results from this novel study will give insight into how the overall immune landscape is reprogrammed during DCIS progression, and may contribute to efforts to better predict early-stage breast cancer progression. Citation Format: Alyssa Victoria Francis, Luke McCaffrey. The tumor immune microenvironment in early breast cancer progression [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1583.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".