Abstract B022: Tumoral GLI1 controls the resident innate and adaptive tumor immune microenvironment in triple negative breast cancer
Bibliographic record
Abstract
Abstract Background: Triple-negative breast cancer (TNBC) accounts for 15-20% of breast cancer (BC) cases but due to its aggressive nature and the lack of targeted treatment options, represents a disproportionately higher number of BC-related deaths. Compared to other BC subtypes, TNBCs are more inflamed with M2-like tumor-associated macrophages (TAMs) and cytotoxic T-lymphocytes (CTLs) which are associated with poor and good prognosis, respectively. Clinical trials have proven that immunogenic cancers can be effectively treated through immune checkpoint blockade (ICB), a treatment strategy that prevents cancer cells from silencing CTL-mediated attack. However, CTLs can be suppressed by M2-like TAMs which can limit ICB efficacy and support tumor growth. The hedgehog (HH) signaling pathway is highly activated in TNBC and higher expression of GLI1 is associated with worse overall survival. Recent pan-cancer analyses highlight a significant correlation between activated HH signaling and characteristics of immune evasion. We aim to clarify how activated HH signaling regulates resident innate and adaptive immune cells in the tumor microenvironment (TME) in TNBC. Methods: Primary K14-cre; Brca1 fl/fl ; P53 fl/fl (KBP) murine TNBC cells were transfected with CRISPR/Cas9 + sgRNA targeting GLI1. After isolating single cell clones and confirming GLI1 knockout (KO), KBP and KBP-GLI1-KO cells were orthotopically injected into the mammary fat pad of syngeneic immune-competent female mice and allowed to grow for 6-8 weeks. Tumor volume was measured once tumors were palpable, and tumors were harvested once the largest tumor reached ethical endpoint. Tumors were weighed at harvest and fluorescence activated cell sorting (FACS) was performed to determine if there was an effect on the composition of immune populations. Results: At harvest, KBP-GLI1-KO tumors were delayed in growth and significantly smaller than KBP tumors. FACS analysis showed that GLI1-KO tumors had increased CD4+ and CD8+ T cells and a reduced amount of Foxp3+ CD4+ Tregs. Furthermore, GLI1-KO tumors had significantly fewer F4/80+ CD11b+ TAMs within the TME. Amongst TAM populations, there was reduced CD206+ M2-like TAMs and an increase in CD80+ M1-like TAMs upon loss of GLI1. Similar trends were observed when KBP allografts were treated with the GLI1 inhibitor, GANT61. Immunohistochemical and RNAseq analysis are ongoing. Similar experiments with other KBP-GLI1-KO clones are currently being done. Conclusion: Here, we show that tumoral GLI1 not only promotes tumor growth, but also supports an immunosuppressive TME in TNBC. Abolishing GLI1 converted tumors to a pro-inflammatory phenotype marked by an increase in CD4+ and CD8+ T cells and a reduction in CD206+ M2-like TAMs. Future experiments are aimed at revealing the mechanisms by which GLI1 regulates immune cell recruitment to the TME and testing the effect of combination immunotherapy. Overall, these preliminary findings identify GLI1 as a potential therapeutic target to limit tumor growth and promote anti-tumor immunity. Citation Format: Aidan J Gray, Wanda Marini, Kiichi Murakami, Michael Reedijk. Tumoral GLI1 controls the resident innate and adaptive tumor immune microenvironment in triple negative breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr B022.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".