Abstract 5333: TH-302 potentiates the antitumor activity of topotecan in neuroblastoma and rhabdomyosarcoma preclinical models
Bibliographic record
Abstract
Abstract Background: There is strong evidence that tumor cells in the hypoxic regions cause drug resistance and tumor relapse. Hypoxia targeting agents may make cytotoxic therapy more effective. In this study, we investigated the efficacy of TH-302, a hypoxia-activated prodrug of bromo-isophosphoramide mustard, both alone and in combination with the cytotoxic agent topotecan, in preclinical models of neuroblastoma (NBL) and rhabdomyosarcoma (RMS). Materials and methods: A panel of four NBL and three RMS cell lines was tested in vitro under normoxic or hypoxic conditions to assess the effect of TH-302 on cell proliferation, both as a single agent and in combination with topotecan. In vivo activity was also evaluated in different xenograft models. TH-302 (50 mg/kg) and topotecan (1 mg/kg) were administered daily for 2 consecutive weeks, as single agents or in combination. Animal survival was studied with an NBL (SK-N-BE(2)) metastatic tumor model. Cleaved caspase-3 and the hypoxia staining agent pimonidazole were used as apoptotic and hypoxic markers in vivo. Results: Under normoxic conditions, all tested lines showed an anti-proliferative response to TH-302 with the IC50s ranging from 4.6 to 52μM. When exposed to hypoxia (1% O2) overnight, a dramatic decrease of IC50 was observed, ranging from 0.07 to 2.4μM. Adding topotecan to the TH-302 treatment significantly increased cytotoxicity in all tested tumor cell lines. In both NBL models (SK-N-BE(2) and CHLA-20), single-agent TH-302 treatment delayed tumor growth. Complete tumor regression was observed in the combined treatment group after a two-week treatment period, but all the regressed tumors relapsed after treatment ended. In the CHLA-20 xenograft model, single-agent topotecan also induced complete tumor regression. However, median time to relapse in the combination group was significantly longer than in the topotecan group (43 days vs. 16 days; p<0.01). In the combination group, all relapsed tumors remained responsive to the drug treatment when re-challenged with the original treatment regimen. In the neuroblastoma metastatic model, all three regimens prolonged animal survival, but the combined treatment group showed better survival than single-agent treatments (p<0.01). In a RMS xenograft model, combined treatment was also more effective than single-agent TH-302 or topotecan. Double immunostaining of apoptotic and hypoxic markers showed that TH-302 mostly targeted tumor cells residing at hypoxic regions while topotecan was more effective on tumor cells outside the hypoxic zones. The combined treatment induced tumor cell apoptosis in both normoxic and hypoxic regions. Conclusions: TH-302 showed antitumor effects in neuroblastoma and rhabdomyosarcoma xenograft models. Compared to single-agent TH-302 or topotecan, the combination treatment significantly improved tumor response, delayed tumor relapse, and enhanced animal survival. Citation Format: Libo Zhang, Bing Wu, Paula Marrano, Paul Thorner, Sylvain Baruchel. TH-302 potentiates the antitumor activity of topotecan in neuroblastoma and rhabdomyosarcoma preclinical models. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5333. doi:10.1158/1538-7445.AM2015-5333
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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) | 0.000 | 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) | 0.003 | 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".