Abstract B010: α-Synuclein preformed fibrils suppress cell cycle progression and glycolytic flux in glioblastoma cells
Bibliographic record
Abstract
Abstract Aging-related diseases, including cancer and neurodegenerative disorders, exhibit complex interrelationships. While Parkinson's disease (PD) and glioblastoma (GBM) both affect the central nervous system, they are pathophysiologically distinct, with an inverse correlation in their incidence. However, the mechanisms underlying this inverse relationship remain poorly understood. Here, we investigate the effects of α-synuclein preformed fibrils (PFF) on GBM cells to explore potential link between neurodegenerative diseases and malignancies. α-synuclein PFF are in vitro–assembled fibrils derived from recombinant monomeric α-synuclein, which recapitulate key pathological features of Lewy body inclusions and have been widely used to model synucleinopathies. In this study, we utilized two GBM cell lines to examine the cellular response against proteopathic PFF. PFF exerted anti-tumor activity through cyclin D1 downregulation, leading to G1 cell cycle arrest. Notably, PFF treatment significantly reduced glycolytic flux while sparing mitochondrial oxidative phosphorylation, indicating selective metabolic disruption. Furthermore, PFF inhibited the AKT signaling pathway, resulting in FOXO1 upregulation, which further contributed to its anti-tumor effects. Our findings provide novel insights into the metabolic and molecular implications of α-synuclein aggregation in GBM, suggesting a potential mechanistic link between neurodegenerative disease processes and tumor suppression, as well as therapeutic potential for cancer treatment. Citation Format: Hyo-Jin Song, Hyeon Ji Kim, Bo Kyung Joo, Jin-Seok Byun, Do-Yeon Kim. α-Synuclein preformed fibrils suppress cell cycle progression and glycolytic flux in glioblastoma cells [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 B010.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".