Abstract 2593: A double dose of DNA damage: Overcoming drug resistance using targeted oncolytic viruses
Bibliographic record
Abstract
Abstract Background: Hereditary breast and ovarian cancers make up 5-10% of breast cancer and 10-15% of ovarian cancer cases. These cancers tend to be difficult to treat and progress in an aggressive manner. Poly(ADP-ribose) polymerase inhibitors (PARPi) are a type of drug that targets the DNA repair pathway; many of these drugs are undergoing clinical trials and some are presently in use for cancers harbouring mutations in their DNA repair machinery, such as hereditary breast and ovarian cancers. Unfortunately, numerous patients become resistant to PARPi, leaving limited options for further treatment. Oncolytic or “cancer-killing” viruses are an innovative approach for treating even the most complex cancers. Oncolytic viruses target and destroy cancer cells, leaving normal cells unharmed, all while activating a patient’s own immune system to fight the cancer. Our group has demonstrated that oncolytic rhabdoviruses may be used to deliver therapeutic payloads by encoding targeting sequences to act on genes via RNA interference (such as shRNA). Objective: The aim of this project is to overcome PARPi resistance by engineering cancer specific viruses that will target genes relevant to the DNA repair pathway, sensitizing them to PARPi treatment in a synthetically lethal manner. Methods: shRNA sequences targeting components of the DNA repair pathway have been cloned into the genome of an oncolytic rhabdovirus (a non-targeting control sequence has been inserted into the same virus as well). Prior to encoding shRNA sequences into the virus, validation of these targets was performed using siRNA transfection. Downregulation of targeted genes are being assessed via qPCR and Western Blot analysis following transfection and infection. Cell viability following treatment with PARPi +/- viruses will be assessed by Alamar Blue and Crystal Violet assays. Results: Downregulation of siRNA targeted genes has been validated at the mRNA level via qPCR analysis (Western Blot analysis is currently ongoing). Validation of the newly engineered viruses to show downregulation of their specific gene targets is currently underway. Changes in cell viability for seven unique human/mouse cell lines following treatment with varying concentrations of two different PARPi to establish a dosing scheme for combination therapy with viral infection has been completed. Conclusions and project impact: This project is currently in the early stages of development; however, preliminary experiments testing the combination of siRNA knockdown with PARPi have revealed a significant decrease in cell viability compared to siRNA knockdown or PARPi alone in MCF-7 breast cancer cells. By engineering OVs that specifically replicate in and kill cancer cells while delivering PARPi sensitizing sequences, this combination approach may enhance and expand the utility of oral PARPi therapeutics in numerous cancers with alterations in DNA repair genes. Citation Format: Taylor R. Jamieson, Carolina S. Ilkow. A double dose of DNA damage: Overcoming drug resistance using targeted oncolytic viruses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2593.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".