Abstract A013: Fibroblast activation protein (FAP) enhances adoptive NK cell therapy in solid tumors
Bibliographic record
Abstract
Abstract Adoptive cell therapy (ACT) has revolutionized cancer treatment. While chimeric antigen receptor T (CAR-T) cell therapy has shown promise, it faces significant challenges such as tumor heterogeneity, immune evasion, and adverse effects like cytokine release syndrome. In contrast, adoptive natural killer (NK) cell therapy offers a compelling alternative due to the innate immunologic properties and strong cytotoxic affinity of NK cells for tumor cells. However, ACT has shown minimal efficacy in solid tumors such as pancreatic ductal adenocarcinoma (PDAC), which is characterized by a fibroblast-rich stroma that actively hinders NK cell infiltration by expressing extracellular matrix (ECM) components such as collagens. We used imaging mass cytometry for spatial proteomic analysis, and observed that in human PDAC tumors, cytotoxic NK cells—rather than T cells—preferentially co-localize with malignant epithelial cells, particularly in regions with low fibroblast density. This observation warrants investigating strategies to enhance NK cell invasion in fibrous tissue-dense tumors, such as PDAC. To address this, we exploited the capacity of fibroblast activation protein (FAP), a transmembrane serine protease, to improve NK cell motility and intratumoral invasion. FAP is predominantly expressed by activated cancer-associated fibroblasts (CAFs) and plays a key role in extracellular matrix (ECM) remodeling through its collagenase activity. We find that force-overexpressing FAP significantly promotes in vitro NK cell invasion through matrix and into tumor spheroid assays, leading to enhanced tumor cell lysis. In vivo, mice bearing solid PDAC tumors treated with FAP-overexpressing NK cells exhibited greater tumor infiltration and reduced tumor burden compared to those treated with wild-type NK cells. Hence, FAP overexpression by NK cells leads to an enhanced anti-tumor effect in solid tumors by increasing their intrinsic motility properties, while maintaining their innate cytotoxic effects. These results have potential important implications for NK cell-based therapies for solid tumors. Citation Format: Rachael Maynard, Marwa Afifi, Louis Weiner. Fibroblast activation protein (FAP) enhances adoptive NK cell therapy in solid tumors [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 A013.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".