Expression of the Lipogenic Enzyme Fatty Acid Synthase (FAS) in Retinoblastoma and Its Correlation with Tumor Aggressiveness
Bibliographic record
Abstract
PURPOSE: Fatty acid synthase (FAS) performs the anabolic conversion of dietary carbohydrate or protein to fatty acids. Many common human cancers express high levels of FAS, and its differential expression between normal and neoplastic tissues has led to the consideration of FAS as a target for anticancer therapy. To investigate the potential of targeting FAS in the treatment of retinoblastoma, we first determined whether FAS was activated in this human tumor. Moreover, correlation of FAS expression with tumor aggressiveness was determined. METHODS: FAS reactivity was evaluated by immunohistochemistry in 66 retinoblastoma specimens from 65 patients. Degree of tumor differentiation, choroid invasion, optic nerve infiltration, mitotic rate, and necrosis extension were estimated. FAS expression was correlated with all these tumor characteristics by means of parametric and nonparametric statistical analyses. RESULTS: Eighty-two percent of tumors were FAS positive. Stronger FAS expression correlated with more advanced choroid (P < 0.001) and optic nerve (P = 0.016) invasion, high mitotic index (P < 0.001), and less differentiated histology (P = 0.047). Correlation with extension of necrosis was not statistically significant. Unaffected retina was negative. CONCLUSIONS: The data suggest that expression of FAS and fatty acid synthesis support an essential functional aspect of retinoblastoma cells, perhaps cell growth or survival. FAS activation may serve as a novel target for systemic and local antineoplastic therapy and, because it increases with tumor aggressiveness, its inhibition could represent an alternative treatment strategy in advanced and resistant retinoblastomas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".