Abstract B034: The immune checkpoint molecule B7-H3 is a driver of tumor immune exclusion by mediating TGF-β activation
Bibliographic record
Abstract
Abstract Addressing the limited responsiveness to immune checkpoint blockade (ICB) in human cancers remains a critical challenge. Efforts over the past two decades have primarily focused on enhancing CD8 T cell function and preventing their exhaustion. However, less attention has been given to understanding the molecular mechanisms that contribute to the immunosuppressive tumor microenvironment (TME), which impedes CD8 T cell infiltration and fosters ICB resistance. The TME in ICB-resistant tumors is characterized by Transforming Growth Factor beta (TGF-β) cytokine signaling, leading to a fibrotic extracellular matrix (ECM) and the accumulation of immunosuppressive fibroblasts and myeloid cells. These features hinder CD8 T cell penetration, thereby promoting immune escape. The immune checkpoint molecule B7-H3, overexpressed in ICB-resistant cancers, has been linked to impaired CD8 T cell infiltration and poor prognosis. However, the molecular mechanisms governing B7-H3 function remain poorly understood. We investigated the relationship between B7-H3 gene expression and ICB response using transcriptomic data from two randomized phase 3 trials (IMvigor010 and IMvigor210). Bulk RNAseq data, tissue staining, and spectral flow cytometry were used to characterize the TME composition of B7-H3 high and low tumors. Multi-omic profiling of tumor cell lines with manipulated B7-H3 expression was performed to identify downstream targets of B7-H3. Syngeneic mouse tumor models were used to assess the impact of B7-H3 on tumor growth and antitumor immunity. High B7-H3 expression was associated with shorter overall survival in both IMvigor010 (HR=0.48, 95% CI: 0.33-0.70, p<0.0001) and IMvigor210 trials (HR=0.68, 95% CI: 0.51-0.92, p=0.01). In ICB-refractory cancers, B7-H3 expression correlated with high levels of fibroblasts, collagen deposits, and M2 macrophages. Gene set enrichment analysis revealed a positive association between B7-H3 and TGF-β signaling. Genetic deletion of B7-H3 in tumor cells reduced the surface expression of MMP14, a metalloprotease that activates TGF-β. Pan-cancer analysis identified MMP14 as the gene most correlated with B7-H3 (Pearson r=0.69, p<0.0001). TGF-β activation was reduced by 70% in B7-H3 knockout cells compared to wild-type. Loss of B7-H3 led to MMP14 accumulation in lysosomes, resulting in its degradation. We generated a B7-H3 inhibitor, 5D10, which promotes MMP14 degradation and inhibits TGF-β activation. In humanized B7-H3 mouse models, 5D10 significantly reduced TGF-β activation, enhancing CD8 T cell infiltration and impairing tumor growth. Our research identifies B7-H3 as a driver of immune exclusion and ICB resistance. We describe a novel, receptor-independent mechanism where B7-H3 promotes TGF-β activation via stabilization of MMP14. Targeting B7-H3 represents a strategy to modulate the TME, transforming immune-excluded tumors into immune-inflamed states that may respond better to ICB. Citation Format: Fabrice Lucien, Roxane Lavoie, Jack Korleski, Yohan Kim, Bharath Wootla, Liguo Wang, Ava Farrell, Kelly Harper, Martine Charbonneau, Claire Dubois, Igor Frank, Sounak Gupta, John Cheville, Jacob Orme, Stephen Boorjian, Parash Shah, Eugene Kwon, Sean Park, Haidong Dong. The immune checkpoint molecule B7-H3 is a driver of tumor immune exclusion by mediating TGF-β activation [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr B034.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".