The Effect of Molecular Targeted Agents used in Combination with Chemotherapy to Inhibit the Repopulation of Tumour Cells and Xenografts
Bibliographic record
Abstract
Chemotherapy is often administered once every three weeks to allow repopulation of essential normal tissues such as the bone marrow. Repopulation of surviving tumour cells can also occur between courses of chemotherapy and can decrease the efficacy of anticancer treatment. This thesis aims to characterize repopulation, to study the effect of targeted cytostatic agents to inhibit repopulation, and to determine the optimal scheduling of chemotherapy and molecular targeted treatment.\nThe distribution of proliferating and apoptotic cells in human squamous cell carcinoma (A431) xenografts was studied following chemotherapy using fluorescence immunohistochemistry. There was an initial decrease in cell proliferation and in the total functional blood vessels, and an increase in apoptosis observed following treatment with paclitaxel chemotherapy. A rebound in cell proliferation occurred approximately 12 days following treatment, which corresponded with a rebound in vascular perfusion.\n\tThe effect of gefitinib, an epidermal growth factor receptor (EGFR) inhibitor, to inhibit repopulation between courses of chemotherapy was determined using EGFR-overexpressing A431 cells and xenografts. Furthermore, concurrent and sequential schedules of combined chemotherapy and molecular targeted treatment were compared. Gefitinib inhibited the repopulation of A431 cells in culture when administered sequentially between chemotherapy; sequential treatment was more efficacious than concurrent treatment probably because concomitant scheduling rendered quiescent cells less responsive to chemotherapy. However, in vivo studies using chemotherapy in combination with gefitinib or temsirolimus, a mammalian target of rapamycin (mTOR) inhibitor, showed that concurrent scheduling of combined treatment was more effective at delaying regrowth of xenografts than sequential treatment; this was likely due to dominant effects on the tumour microenvironment.\n\tThe work completed in this thesis has shown that repopulation occurs in A431 xenografts following paclitaxel treatment, and these changes are associated with changes in the tumour vasculature. Repopulation of A431 cells was inhibited by gefitinib administered sequentially with paclitaxel. However, studies in mice showed better inhibitory effects when chemotherapy was given concomitantly with cytostatic agents such as gefitinib or temsirolimus. Our in vivo data highlight the importance of characterizing changes in the tumour microenvironment when determining optimal scheduling of chemotherapy and molecular targeted treatment.
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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) | 0.001 | 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 | 0.001 |
| 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".