Abstract B88: GPNMB expression modulates the tumor immune microenvironment in mouse models of breast cancer
Bibliographic record
Abstract
Abstract The role of glycoprotein-NMB (GPNMB) in the immune system is varied. GPNMB expression in macrophages and dendritic cells promotes innate immune responses, whereas GPNMB-expressing myeloid-derived suppressor (MDSC) cells suppress adaptive immune responses (T-cell function). While functional roles for GPNMB expressed within cells of the immune system are emerging, the influence of tumor-derived GPNMB expression on the immune landscape within mammary tumors has not been well characterized. To investigate this further, we have generated two GPNMB-deficient breast cancer cell populations (Lung Metastatic-4T1 [LM-4T1] and E0771 cells) to determine the influence of GPNMB on the tumor immune microenvironment (TME). While loss of GPNMB significantly impaired tumor growth of both these breast cancer models in syngeneic mice, this difference was not apparent with LM-4T1 injected in athymic nude mice. These observations suggest GPNMB may promote tumor growth by modulating the T-cell function. We have used traditional immunohistochemical analyses to broadly characterize the T cells present in the TME of E0771 and LM-4T1 breast tumors, which express or lack GPNMB. We have observed a significant increase in both CD8+ and CD4+ immune cells in GPNMB-deficient LM-4T1 and E0771 tumors compared to parental cells at an experimental endpoint of matched tumor volumes. To determine the temporal response of the immune system to LM-4T1 cells, we have isolated early developing lesions and stained for CD8, CD4, Fox3p, and granzyme B positive cells. We observed a significant increase in CD4+ and a trend for elevated granzyme B+ cells at early timepoints in GPNMB-deficient tumors compared to LM-4T1 parental cells. Taken together, these results suggest GPNMB suppresses an early recruitment of CD4+ cells where, in the absence of GPNMB, this would result in elevated CD8+ and CD4+ cells in these tumors. We are currently characterizing the contribution of CD4+ cells in the progression of these tumor models. Citation Format: Matthew G. Annis, April A.N. Rose, Ryuhjin Ahn, Brian E. Hsu, Josie Ursini-Siegel, Peter M. Siegel. GPNMB expression modulates the tumor immune microenvironment in mouse models of breast cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr B88.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".