Abstract 4069: Selective ablation of solid tumors using a p53-targeted FAST-LNP gene therapy
Bibliographic record
Abstract
Abstract While chemotherapy is a key treatment strategy for many solid tumors, it is rarely curative as patients will eventually become resistant. In this study, we sought to develop an effective suicide gene therapy approach for solid tumors that specifically exploits their unique transcriptional activation state. The tumor suppressor p53 is frequently mutated or dysregulated in cancer, and as a result the upstream signaling pathways activating p53 transcription are strongly upregulated. RNA-seq analysis has demonstrated that p53 transcription is significantly upregulated in almost all forms of cancer. Additionally, HCT116 cells lacking functional p53 display a 6-fold increase in p53 promoter activity when compared to its wild type p53 parent cell line. To exploit this, we have developed a Fusogenix FAST-LNP formulation to deliver a p53-driven inducible suicide gene, iCasp9, to solid tumors and destroy them upon activation with small molecule dimerizer, Rapamycin. To establish a proof-of-concept, plasmid encoding iCasp9 and luciferase under control of the p53 promoter was constructed and evaluated in a panel of cancer cell lines. While LNPs administered without Rapamycin or Rapamycin administered alone had no impact on cell viability, we observed greater than 90% apoptotic cell death when both were employed in a wide range of cancer cell lines with p53 deletions or mutations, as measured using cell viability assays, imaging assays, as well as Annexin V and TUNEL flow cytometry. Induction of iCasp9 protein expression and caspase-mediated apoptosis was confirmed using Western blot. No cell death was observed in cells with intact p53 such as human umbilical vein endothelial cells or the fibroblast cell line IMR-90. Next, we assessed the efficacy of FAST-LNPs containing p53-iCasp9 in xenograft PC-3 and H1299 models of human prostate cancer and lung cancer respectively. In some experiments, tumors were implanted subcutaneously in the flanks of 30 mice and allowed to grow to 500 mm3 before treatment by intravenous doses of 100 µg LNP twice per week during continuous low dosing of Rapamycin. We observed a rapid and dramatic reduction in tumor volume averaging 87% over the following 48 hours, with durable response. Tumors in control mice continued to grow exponentially. Overall survival of mice was extended 250% in the PC-3 cohort and 300% in the H1299 cohort. Optimization of number and concentration of LNP doses should allow for long term control of both localized and systemic disease. In conclusion, we describe a novel LNP gene therapy approach for the treatment of cancer with high selectivity for tumors with dysregulated p53 transcriptional activation. This approach has the potential to provide a highly efficacious alternative to current therapies for localized and advanced solid tumors. Citation Format: Douglas Wilson Brown, Arun Raturi, Prakash Bhandari, Deborah Sosnowski, Liliya Grin, Ping Wee, Hector Vega, Jennifer Gyoba, Maryam Hejazi, Jailal Ablack, Matthew Scholz, John D. Lewis. Selective ablation of solid tumors using a p53-targeted FAST-LNP gene therapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4069.
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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) | 0.000 | 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 | 0.000 |
| 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".