Far upstream element‐binding protein 1 confers lobaplatin resistance by transcriptionally activating PTGES and facilitating the arachidonic acid metabolic pathway in osteosarcoma
Bibliographic record
Abstract
Drug resistance is a major obstacle in cancer treatment and recurrence prevention and leads to poor outcomes in patients suffering from osteosarcoma. Clarification of the mechanism of drug resistance and exploration of effective strategies to overcome this obstacle could lead to clinical benefits for these patients. The expression of far upstream element-binding protein 1 (FUBP1) was found to be markedly elevated in osteosarcoma cell lines and clinical specimens compared with osteoblast cells and normal bone specimens. High expression of FUBP1 was correlated with a more aggressive phenotype and a poor prognosis in osteosarcoma patients. We found that overexpression of FUBP1 confers lobaplatin resistance, whereas the inhibition of FUBP1 sensitizes osteosarcoma cells to lobaplatin-induced cytotoxicity both in vivo and in vitro. Chromatin immunoprecipitation-seq and RNA-seq were performed to explore the potential mechanism. It was revealed that FUBP1 could regulate the transcription of prostaglandin E synthase (PTGES) and subsequently activate the arachidonic acid (AA) metabolic pathway, which leads to resistance to lobaplatin. Our investigation provides evidence that FUBP1 is a potential therapeutic target for osteosarcoma patients. Targeting FUBP1, its downstream target PTGES and the AA metabolic pathway may be promising strategies for sensitizing chemoresistant osteosarcoma cells to lobaplatin.
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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) | 0.002 | 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".