Abstract PR19: Utilizing novel oncolytic vaccinia virus for selective expression of immunotherapeutic payloads in metastatic tumors
Bibliographic record
Abstract
Abstract The treatment paradigm for patients with metastatic cancer has evolved rapidly with the approval of agents targeting CTLA-4 and the PD-1/L1 immune checkpoint axis. Despite the profound impact these agents have had, they are minimally effective in the majority of cancer patients. Rational combinations of complementary immune-modulating agents have thus far not led to clear patient benefit, and newer technologies that are better able to safely combine multiple modes of action could well prove to be vital. Oncolytic viruses (OVs) have the capacity to be the ideal therapeutic partner for immune checkpoint therapeutics in several ways. First, on their own OVs can “heat up” immunologically “cold” tumors by initiating a proinflammatory infection within the tumor microenvironment (TME). Second, some OVs can be engineered to strategically express one or more immune-modulating molecules. Finally, certain OVs have the capacity to be delivered systemically and thus enhance immune cell recruitment and activation in all metastatic sites. We have selected a novel vaccinia virus as our therapeutic OV platform and are using it to engineer multi-mechanistic cancer therapeutics. Previously it has been demonstrated that oncolytic vaccinia viruses can be delivered systemically and spread within metastatic lesions. These clinical candidates, however, contain multiple potent immune-suppressive genes. Furthermore, in clinical studies some of these therapeutics exhibited off-tumor infections (e.g., pox lesions), which may ultimately limit their ability to be used to deliver potent immune modulators. We used a combination of functional genomics and bio-selection strategies to generate a novel oncolytic vaccinia backbone (termed SKV) containing a large genome deletion that exhibited augmented oncolytic activity and improved tumor selectivity. Our new best-in-class vaccinia robustly stimulates anti-immune responses, rapidly spreads within and between tumors, and has a substantially improved preclinical safety profile when compared to other vaccinia clinical candidates. As predicted, SKV synergizes well with immune checkpoint inhibitor antibodies and potently activates human immune cells. Due to the exquisite tumor selectivity of SKV, we have been able to engineer and express three potent immune modulators that are safest and most effective when expressed within the TME: anti-CTLA4 antibody, membrane tethered IL-12, and the antigen-presenting cell-activating ligand FLT-3L. Tumor-selective transgene expression has been demonstrated in murine tumor models in which therapeutic payload concentrations (e.g., >1 ug/ml IL-12) were achieved within the TME without any detectable transgene product in the systemic circulation (serum). Expression of the therapeutic payloads increased survival versus the SKV backbone control in an immunocompetent, syngeneic tumor model. Ongoing toxicity and efficacy studies are being carried out prior to clinical evaluation of the novel virus construct. This abstract is also being presented as Poster A02. Citation Format: Adrian Pelin, Mike Huh, Matt Tang, Fabrice LeBouef, Brian Keller, Jessie Duong, Katherine Knowles, Julia Petryk, Vicki Jennings, Alan Melcher, Ragunath Singaravelu, Mathieu Crupi, Larissa Pikor, Caroline Breitbach, Steven Bernstein, Michael Burgess, John C. Bell. Utilizing novel oncolytic vaccinia virus for selective expression of immunotherapeutic payloads in metastatic tumors [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr PR19.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".