Abstract A005: TAZ-TEAD signaling alters the immune microenvironment of cutaneous melanoma
Bibliographic record
Abstract
Abstract Current standard of care treatment for late-stage cutaneous melanoma is immune checkpoint blockade (ICB); however, about ∼50% of patients progress after treatment and mechanisms underlying resistance are actively being investigated. For example, an invasive, mesenchymal-like cell state, often characterized by low expression of SOX10, is associated with cross resistance to ICB and MAPK targeted therapy (TT). Tumors with low levels of SOX10, a melanocyte lineage specific transcription factor, exhibit enhanced activation of the YAP/TAZ-TEAD signaling pathway. YAP and TAZ are downstream transcriptional co-activators in the Hippo signaling pathway that interact with TEAD transcription factors to promote expression of genes that control cell proliferation, survival and drug resistance. Small molecule TEAD inhibitors (TEADi) have been tested in various clinical trials, but their effect in melanoma has not been evaluated. Melanoma cells with high TEAD activity have upregulated expression of immune checkpoint molecule PD-L1 and depletion of TAZ, not YAP, in these cells significantly upregulates expression of immune-modulatory molecules including galectin 9, galectin 3 and OX40L. Given that TAZ-TEAD signaling has been associated with TT resistance in melanoma, we want to investigate the role of TAZ-TEAD in the melanoma immune microenvironment and evaluate its relevance in the context of ICB resistance. Preliminary in vivo analysis of tumors treated short-term with TEADi (VT103) revealed changes in the immune microenvironment, including upregulation of galectin 9 and MHC-I on tumor cells and enhanced recruitment of CD4+ T cells. Together, these data imply there is TAZ-TEAD dependent regulation of immune-modulatory molecules in the microenvironment, suggesting that targeting TEADs may enhance sensitivity of tumors to ICB. Future directions include in vivo studies to determine if active TAZ is sufficient to mediate ICB resistance and whether TEADi enhances efficacy of ICB. Citation Format: Kristen M. DeRosa, Andrew Aplin, Timothy Purwin, Dan Erkes, Manoela Tiago. TAZ-TEAD signaling alters the immune microenvironment of cutaneous melanoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr A005.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".