Abstract B014: SYNCRIP drives therapy resistance via ferroptosis suppression and metabolic activation in Glioblastoma
Bibliographic record
Abstract
Abstract Synaptotagmin-binding Cytoplasmic RNA-Interacting Protein (SYNCRIP) is an RNA-binding protein (RBP) implicated in multiple cancers. Here, we report that SYNCRIP is significantly upregulated in glioblastoma (GBM) and correlates with poor prognosis and tumor progression. Mechanistically, SYNCRIP promotes SIRT1 expression at both transcriptional and post-transcriptional levels by stabilizing SIRT1 mRNA. Loss of SYNCRIP decreases SIRT1, increases ROS levels, and induces ferroptosis, which is reversed by SIRT1 restoration. Additionally, SYNCRIP enhances hexokinase 2 (HK2) expression via transcriptional activation and IRES-mediated translation, thereby promoting glycolysis. SYNCRIP depletion impairs mitochondrial function, cell migration, and invasion, partly through the downregulation of EMT-related factors. Collectively, these findings identify SYNCRIP as a key regulator of ferroptosis resistance and metabolic reprogramming in GBM, supporting its potential as a therapeutic target in glioblastoma. Citation Format: Hyeon Ji Kim, Hyo-Jin Song, Bo Kyung Joo, Jun-Nyeong Kim. SYNCRIP drives therapy resistance via ferroptosis suppression and metabolic activation in Glioblastoma [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 B014.
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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".