Impact of Metronomic UFT/Cyclophosphamide Chemotherapy and Antiangiogenic Drug Assessed in a New Preclinical Model of Locally Advanced Orthotopic Hepatocellular Carcinoma
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is an intrinsically chemotherapy refractory malignancy. Development of effective therapeutic regimens would be facilitated by improved preclinical HCC models. Currently, most models consist of subcutaneous human tumor transplants in immunodeficient mice; however, these do not reproduce the extensive liver disease associated with HCC or metastasize. To address this deficiency, we developed an orthotopic model. Human HCC cells were transfected with the gene encoding secretable beta-subunit human choriogonadotropin (beta-hCG), which was used as a surrogate marker of tumor burden. The HCC cells were implanted into the left liver lobe of severe combined immunodeficient (SCID) mice, after which the efficacy of different therapies was evaluated on established, but liver-confined human Hep3B cell line HCC. Treatments included sorafenib or metronomic chemotherapy using cyclophosphamide (CTX), UFT, an oral 5-fluorouracil prodrug, or doxorubicin either alone or in various combinations, with or without an antiangiogenic agent, DC101, an anti-vascular endothelial growth factor receptor-2 antibody. Sorafenib inhibited tumor growth in a dose-dependent manner but caused severe weight loss in SCID mice, thus necessitating use of DC101 in subsequent experiments. Although less toxicity was observed using either single or doublet metronomic chemotherapy without any added antiangiogenic agent, none, provided survival benefit. In contrast, significantly improved overall survival was observed using various combinations of metronomic chemotherapy regimens such as UFT + CTX with DC101. In conclusion, using this model of liver-confined but advanced HCC suggests that the efficacy of a targeted antiangiogenic drug or metronomic chemotherapy can be mutually enhanced by concurrent combination treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".