Thalidomide Enhances the Anti-Tumor Activity of Standard Chemotherapy in a Human Melanoma Xenotransplatation Model
Bibliographic record
Abstract
It has been demonstrated that thalidomide's anti-angiogenic properties result in clear anti-tumor activity in a number of human malignancies. We studied thalidomide in a human melanoma severe combined immunodeficiency mouse xenotransplantation model. Thalidomide as a single agent showed a significant tumor reduction of 46% compared with the control group. Thalidomide combined with dacarbazine treatment markedly enhanced the anti-tumor effect of chemotherapy and showed a significant tumor reduction relative to the dacarbazine-only group (61%) and even more tumor reduction (74%) compared with the control group. We also measured clearly reduced levels of tumor necrosis factor-alpha in the thalidomide-treated group. A significantly lower microvessel density was encountered in the thalidomide treatment groups (thalidomide alone or combined with DTIC), underscoring the anti-angiogenic effect of thalidomide as a single agent as well as in combination with chemotherapy in this model. In line with these results, we observed a nearly 3-fold increase of apoptosis for the combination of thalidomide and DTIC compared with the rate of apoptotic cells in DTIC-only-treated melanoma xenotransplants. These data underline the rationale for combining dacarbazine--a cytotoxic agent--and thalidomide--an anti-angiogenic cytostatic agent--as a promising strategy for the treatment of melanoma.
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 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".