Capitalizing on Cancer Specific Replication: Oncolytic Viruses as a Versatile Platform for the Enhancement of Cancer Immunotherapy Strategies
Bibliographic record
Abstract
The past decade has seen considerable excitement in the use of biological therapies in treating neoplastic disease. In particular, cancer immunotherapy and oncolytic virotherapy have emerged as two frontrunners in this regard with the first FDA approvals for agents in both categories being obtained in the last 5 years. It is becoming increasingly apparent that these two approaches are not mutually exclusive and that much of the therapeutic benefit obtained from the use of oncolytic viruses (OVs) is in fact the result of their immunotherapeutic function. Indeed, OVs have been shown to recruit and activate an antitumor immune response and much of the current work in this field centers around increasing this activity through strategies such as engineering genes for immunomodulators into OV backbones. Because of their broad immunostimulatory functions, OVs can also be rationally combined with a variety of other immunotherapeutic approaches including cancer vaccination strategies, adoptive cell transfer and checkpoint blockade. Therefore, while they are important therapeutics in their own right, the true power of OVs may lie in their ability to enhance the effectiveness of a wide range of immunotherapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".