Abstract A75: The role of eosinophils in the lung tumor microenvironment
Bibliographic record
Abstract
Abstract Background: The use of immunotherapy to treat lung cancer is becoming increasingly common, highlighting the importance of the immune system in the lung tumor microenvironment. The lungs are host to a variety of immune cell subsets, including eosinophils (Eo), which are a population of innate immune cells that exert cytotoxic effector functions through the release of secretory granules and participate in tissue homeostasis and immunity. Despite the presence of Eo in solid tumors and their prevalence in the lung, the role of Eo in lung cancer is both controversial and largely unexplored. The Bennewith lab has previously found that mice with elevated lung Eo have decreased tumor growth in a model of breast cancer lung metastasis. We hypothesize that Eo play a protective role in lung cancer progression. Methods: In collaboration with Dr. Kelly McNagny (UBC), we used IL-5Tg transgenic mice that overexpress IL-5 and have a systemic expansion of Eo, ddGATA transgenic mice which are Eo-deficient, and ddGATA/IL-5Tg double-transgenic mice (excess IL-5 but no Eo) to study lung cancer. Lewis Lung carcinoma (LLC) cells were injected intravenously (IV) to seed the lungs. After three weeks, we harvested lungs and used flow cytometry to quantify immune cell subsets in the lungs. Additionally, we used clonogenic assays and histology to quantify lung tumor growth. Results: We confirmed that naive ddGATA and ddGATA/IL-5Tg mice have no lung Eo. In contrast, IL-5Tg mice have a 100-fold expansion of Eo in the lungs, and these Eo express higher levels of the Eo activation marker CD11b compared to wild-type (WT) mice. Naive IL-5Tg and ddGATA/IL-5Tg mice had an increased proportion of lung B-1 B cells, as well as an increase in the expression of the apoptosis-inducing cell surface molecule FasL. The absence of Eo in ddGATA mice did not impact lung colonization of LLC cells. Though there was a substantial expansion of Eo in the lungs of IL-5Tg mice compared to WT mice, there was no change in the number of lung-infiltrating Eo three weeks after IL-5Tg and WT mice were injected IV with LLC cells. IL-5Tg mice injected IV with LLC cells had an increase in the total number of lung-infiltrating Bconv and B-1 B cells compared to naive mice, whereas there was no change in B cell subsets between naive and LLC IV injected WT mice. Conclusions: Though Eo may play an antitumorigenic role in the presence of excess IL-5, the absence of Eo in ddGATA mice did not result in an increase in lung tumor burden. This suggests that Eo need to be activated and expanded to exert an antitumorigenic effect, or that the expansion of B cells in IL-5Tg mice is responsible for the decrease in lung tumor growth in IL-5Tg mice relative to WT mice. Illuminating the specific roles Eo and B cells play in lung cancer progression will allow us to better understand the interplay between host immune cells and malignant cells and could reveal new avenues of cancer immunotherapy development. Citation Format: Rachel A. Cederberg, Alvina So, Elizabeth Franks, Jenna Collier, Brennan J. Wadsworth, Michael R. Hughes, Kelly M. McNagny, Kevin L. Bennewith. The role of eosinophils in the lung tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr A75.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".