Targeting PTGES/PGE2 axis enhances sensitivity of colorectal cancer cells to 5-fluorouracil
Bibliographic record
Abstract
Insensitivity and resistance to 5-fluorouracil (5FU) remain as major hurdles for effective and durable 5FU-based chemotherapy in colorectal cancer (CRC) patients. In this study, we identified prostaglandin E synthase (PTGES)/prostaglandin E2 (PGE2) axis as an important regulator for 5FU sensitivity in CRC cells. We found that PTGES expression and PGE2 production are elevated in CRC cells in comparison to normal colorectal epithelial cells. Depletion of PTGES significantly enhanced the inhibitory effect of 5FU on CRC cell viability that was fully reverted by exogenous supplement of PGE2. Inhibition of PTGES enzymatic function, by either inducing loss-of-function mutant or treatment with selective inhibitors, phenocopied the PTGES depletion in terms of 5FU sensitization. Mechanistically, PTGES/PGE2 axis modulates glycolysis in CRC cells, thereby regulating the 5FU sensitivity. Importantly, high PTGES expression is correlated with poor prognosis in 5FU-treated CRC patients. Thus, our study defines PTGES/PGE2 axis as a novel therapeutic target for enhancing the efficacy of 5FU-based chemotherapy in CRC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".