Abstract P064: Novel engineering of therapeutic <i>Fusobacterium nucleatum</i> phage for colorectal cancer treatment
Bibliographic record
Abstract
Abstract Fusobacterium nucleatum (FN) is enriched in human colorectal tumors [1] and its presence is correlated with poor prognosis [2]. Bacteriophages ("phages") are naturally occurring, self-amplifying viruses that are highly specific for particular bacterial species and strains and are recognized to have a high intrinsic safety. They offer a promising treatment strategy to both target FN associated with colorectal cancer (CRC) and, by phage engineering, to deliver an anti-tumoral immune-stimulating payload that may enhance the effectivity of other anti-cancer therapies such as checkpoint inhibitors in unresponsive colorectal cancer patients. The major challenge in engineering phages that target FN is the optimization of the eukaryotic payloads for high expression in this bacterial host. Since no data is available about codon usage and non-coding genetic sequences in the genome of FN bacteria, two computational approaches were used to optimize the codon usage for elevated payload expression of the first selected payload, murine IL-15. These approaches involved identifying ribosome binding sites and elongation speeds to optimize codon usage. Following design of an IL-15 expression vector, expression of this eukaryotic payload in FN bacteria was tested in vitro. For phage engineering, a plasmid containing the designed payload sequence was used to introduce the selected IL-15 encoding sequences into the phage genome. FN phage was successfully engineered to deliver a payload encoding the sequence of murine cytokine IL-15. Targeting of FN with engineered phage resulted in IL-15 protein expression in phage-infected bacteria in vitro. Given the specificity of FN for CRC tumors and the ability to locally express a eukaryotic protein by using FN targeting phage to deliver a payload, phage therapy may offer novel treatment approaches for patients with CRC. Citation Format: Lihi Ninio-Many, Yael Zigelman, Nufar Buchshtab, Yifat Elharar, Gal Eylon, Eliya Gidron, Dikla Berko-Ashur, Julian Nicenboim, Lior Zelcbuch, Einav Safyon Gartman, Sharon Kredo-Russo, Noga Kowalsman, Ilya Vainberg Slutskin, Iddo Weiner, Inbar Gahali-Sass, Naomi Zak, Sailaja Puttagunta, Merav Bassan. Novel engineering of therapeutic Fusobacterium nucleatum phage for colorectal cancer treatment [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P064.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".