Abstract B03: Development of retroviral replicating vectors expressing codon-optimized nitroreductase for prodrug activator gene therapy in human glioma models
Bibliographic record
Abstract
Abstract Our studies to date have demonstrated dramatic survival benefit when tumor-selective retroviral replicating vectors (RRV) are employed for gene therapy in a variety of preclinical cancer models. RRV-mediated prodrug activator gene therapy using yeast cytosine deaminase (RRV-CD; “Toca 511”) has been evaluated in multi-center Phase I ascending dose trials in patients with recurrent high grade glioma (http://www. clinicaltrials.gov: NCT01156584, NCT01985256, NCT01470794), and based on highly promising evidence of therapeutic benefit, a registrational Phase IIB/III trial has recently been initiated at multiple sites in the United States and Canada (NCT02414165). Translational development of further RRV-based therapeutic agents is also on-going, and we have now developed an RRV encoding E.coli nitroreductase (NTR), a prodrug activator enzyme which converts CB1954 to a potent bifunctional alkylating agent. We constructed RRV encoding wild-type E.coli NTR genes (RRV-NfsA, RRV-NfsB) as well as NTR variants extensively modified to optimize human codon usage and vector stability (RRV-NAO, RRV-NBO). NTR transgene insertion did not affect vector replication, which resulted in increasing NTR expression over time in U87 human glioma cultures for all vectors, but sequence optimization significantly increased genomic stability of the RRV-NAO and RRV-NBO vectors over serial passage. U87 cells fully transduced with the optimized vectors showed higher levels of NTR protein and increased levels of enzymatic activity compared with cells transduced with wild-type vectors. In vitro cytotoxicity was examined by MTS assay after CB1954 treatment of fully transduced U87 cells. Viability was reduced by >80% within 48 hrs in cells transduced with RRV-NAO, which showed the most potent cell killing efficiency and bystander effect among all vectors tested. Significant reduction in luminescence and inhibition of tumor growth was observed in subcutaneous U87-FLuc2 tumors initiated with 2% RRV-NAO transduction followed by intraperitoneal administration of CB1954. In intracerebral U87-FLuc2 orthotopic tumor models, stereotactic intratumoral injection of RRV-NAO and repeated cycles of prodrug treatment also resulted in significant luminescence reduction, and achieved prolonged survival benefit. These results indicate that we have been successful in developing an improved prodrug activator gene with therapeutic efficacy when delivered by RRV in experimental models of human glioma. Further studies are aimed at translational development of improved RRV-NTR vectors for future clinical use both as a stand-alone therapy and in combination with RRV-CD (Toca 511). Citation Format: Sara Collins, Akihito Inagaki, Mark Tangney, Noriyuki Kasahara. Development of retroviral replicating vectors expressing codon-optimized nitroreductase for prodrug activator gene therapy in human glioma models. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr B03.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".