Gemcitabine promotes autophagy and lysosomal function through ERK- and TFEB-dependent mechanisms
Bibliographic record
Abstract
Gemcitabine is a first-line treatment agent for pancreatic ductal adenocarcinoma (PDAC). Contributing to its cytotoxicity, this chemotherapeutic agent is primarily a DNA replication inhibitor that also induces DNA damage. However, its therapeutic effects are limited owing to chemoresistance. Evidence in the literature points to a role for autophagy in restricting the efficacy of gemcitabine. Autophagy is a catabolic process in which intracellular components are delivered to degradative organelles lysosomes. Interfering with this process sensitizes PDAC cells to gemcitabine. It is consequently inferred that autophagy and lysosomal function need to be tightly regulated to maintain homeostasis and provide resistance to environmental stress, such as those imposed by chemotherapeutic drugs. However, the mechanism(s) through which gemcitabine promotes autophagy remains elusive, and the impact of gemcitabine on lysosomal function remains largely unexplored. Therefore, we applied complementary approaches to define the mechanisms triggered by gemcitabine that support autophagy and lysosome function. We found that gemcitabine elicited ERK-dependent autophagy in PDAC cells, but did not stimulate ERK activity or autophagy in non-tumoral human pancreatic epithelial cells. Gemcitabine also promoted transcription factor EB (TFEB)-dependent lysosomal function in PDAC cells. Indeed, treating PDAC cells with gemcitabine caused expansion of the lysosomal network, as revealed by Lysosome associated membrane protein-1 (LAMP1) and LysoTracker staining. More specific approaches have shown that gemcitabine promotes the activity of cathepsin B (CTSB), a cysteine protease playing an active role in lysosomal degradation. We showed that lysosomal function induced by gemcitabine depends on TFEB, the master regulator of autophagy and lysosomal biogenesis. Interfering with TFEB function considerably limited the clonogenic growth of PDAC cells and hindered the capacity of TFEB-depleted PDAC cells to develop orthotopic tumors.
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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".