Abstract 2996: Sunitinib withdrawal uncovers complementary stromal- and tumor-mediated mechanisms of resistance and rebound growth in metastatic mouse models
Bibliographic record
Abstract
Abstract Background: Despite the clinical approval of VEGF pathway targeted agents in the treatment of late-stage metastatic disease, sustained benefits are not seen in the majority of patients, and eventual relapse occurs. Understanding mechanisms of intrinsic and acquired drug resistance has taken on increasing importance as both host- and tumor-mediated pathways may contribute to treatment failure. However, few studies have aimed to assess resistance in clinically-relevant spontaneous metastatic disease after surgical resection of the primary tumor. Methods: Here we describe the derivation of spontaneous metastatic human kidney, breast, and melanoma cell lines following long-term in vivo sunitinib treatment. Re-exposure of selected tumor and stromal cells to drug in vitro for extended periods allowed evaluation of reversible and irreversible gene expression changes. Cells were implanted orthotopically and then surgically removed to assess primary and metastatic growth potential following treatment cessation. Results: Our results show that metastatic sunitinib-resistant cells retained treatment sensitivity when re-implanted orthotopically regardless of in vitro drug exposure conditions, suggesting a predominant host-mediated role in treatment failure. However, sunitinib treatment withdrawal elicited significant increases in tumor growth and metastatic potential, a finding which was enhanced when non-tumor bearing mice were ‘conditioned’ with drug prior to i.v. tumor cell inoculation. Parallel studies in vitro show increased proliferation and migration following therapy removal. Results from gene and protein expression analysis of cells in different sunitinib treatment conditions will be presented showing that coordinated tumor and host reactions can contribute to changes in metastatic phenotype upon therapy removal. Conclusions: Taken together, clinically relevant models of drug-resistant spontaneous metastatic disease may have the potential to distinguish tumor- and stromal-responses to treatment that can alter in vivo disease progression both on (and off) therapy. Citation Format: Michalis Mastri, Amanda Tracz, Christina R. Lee, Derya Deveci, John M. L. Ebos. Sunitinib withdrawal uncovers complementary stromal- and tumor-mediated mechanisms of resistance and rebound growth in metastatic mouse models. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2996. doi:10.1158/1538-7445.AM2014-2996
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".