Abstract B022: Investigating Biased GPCRs Activation by Nutraceutical Caffeine and Nicotine in Transactivating Glycosylated Receptors to Induce EMT in Cancer Metastasis
Bibliographic record
Abstract
Abstract Chronic inflammation plays a central role in tumor initiation, progression, and metastasis. G protein-coupled receptors (GPCRs) are critical regulators of inflammation and cancer-associated signaling. Previous work from our lab revealed that GPCRs form functional heteromeric complexes with neuraminidase-1 (Neu1) and matrix metalloproteinase-9 (MMP9), which transactivate glycosylated receptor tyrosine kinases (RTKs) and Toll-like receptors (TLRs), promoting NF-κB-mediated epithelial–mesenchymal transition (EMT). This research explores how two widely consumed nutraceutical compounds, caffeine and nicotine, act as biased agonists at GPCRs to modulate this signaling axis in cancer progression. We hypothesize that caffeine and nicotine enhance Neu1–MMP9–GPCR–RTK/TLR interactions, selectively activating pro-inflammatory and oncogenic pathways. To test this, RAW-Blue macrophages and two human cancer cell lines (PANC-1 and MDA-MB-231) were used to assess Neu1 sialidase activity, NF-κB transcriptional activity using a secreted embryonic alkaline phosphatase (SEAP) reporter assay, and co-localization of GPCRs with Neu1 by immunofluorescence microscopy. Additionally, EMT markers, such as E-cadherin and N-cadherin, were evaluated by immunofluorescence staining. Cell migration and metastatic potential were assessed via scratch wound assays and cell tunneling experiments. Our preliminary findings show that nicotine significantly promotes NF-κB activation, EMT marker expression, and cell migration, characterized by increased N-cadherin and decreased E-cadherin. In contrast, caffeine exhibits opposing effects, decreasing NF-κB activation and cell migration, and maintaining epithelial marker expression. These results indicate distinct and opposing roles for these compounds in regulating cancer cell behavior through biased GPCR signaling. In summary, this work highlights novel regulatory mechanisms of Neu1–MMP9–GPCR signaling modulated by common dietary compounds. These findings may support the development of low-cost, accessible therapeutic strategies to mimic or block nutraceutical effects in cancer and inflammation management. Citation Format: Yunfan Li, Myron. R. Szewczuk. Investigating Biased GPCRs Activation by Nutraceutical Caffeine and Nicotine in Transactivating Glycosylated Receptors to Induce EMT in Cancer Metastasis [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 B022.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".