Potential role of lipophagy impairment for anticancer effects of glycolysis-suppressed pancreatic ductal adenocarcinoma cells
Bibliographic record
Abstract
Although increased aerobic glycolysis is common in various cancers, pancreatic ductal adenocarcinoma (PDAC) cells can survive a state of glycolysis suppression. We aimed to identify potential therapeutic targets in glycolysis-suppressed PDAC cells. By screening anticancer metabolic compounds, we identified SP-2509, an inhibitor of lysine-specific histone demethylase 1A (LSD1), which dramatically decreased the growth of PDAC PANC-1 cells and showed an anti-tumoral effect in tumor-bearing mice. The growth of glycolysis-suppressed PANC-1 cells was also inhibited by another LSD1 inhibitor, OG-L002. Similarly, the other two PDAC cells (PK-1 and KLM-1) with suppressed glycolysis exhibited anticancer effects against SP-2509. However, the anticancer effects on PDAC cells were unrelated to LSD1. To investigate how PDAC cells survive in a glycolysis-suppressed condition, we conducted proteomic analyses. These results combined with our previous findings suggested that glucose-starvation causes PDAC cells to enhance mitochondrial oxidative phosphorylation. In particular, mitochondrial fatty acid metabolism was identified as a key factor contributing to the survival of PDAC cells under glycolysis suppression. We further demonstrated that SP-2509 and OG-L002 disturbed fatty acid metabolism and induced lipid droplet accumulation through the impairment of lipophagy, but not bulk autophagy. These findings indicate a significant potential association of lipophagy and anticancer effects in glycolysis-suppressed PDAC cells, offering ideas for new therapeutic strategies for PDAC by dual inhibition of glycolysis and fatty acids metabolism.
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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) | 0.001 | 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 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".