Immunotherapy in cancer: novel approaches and future perspectives
Bibliographic record
Abstract
Growing understanding of immune cell regulation and the tumour microenvironment is transforming cancer therapy by enabling the development of tailored immunomodulatory agents, novel combination treatments and new immunotherapy targets. As a result, cancer types and stages once considered incurable or requiring radical surgery can now be managed with effective therapeutic combinations that preserve organs, extend survival and improve patients' quality of life. The themed issue of the British Journal of Pharmacology features four review articles that explore recent advancements in cancer immunotherapy and new approaches to overcome challenges in immunotherapy. Furthermore, the issue includes two research articles that present novel antibodies that remodel the tumour immune landscape and novel approaches to reprogram the tumour microenvironment to increase the efficacy of chimeric antigen receptor T-cell therapy (CAR-T) immunotherapy. LINKED ARTICLES: This article is part of a themed issue Immunotherapy in Cancer. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v183.6/issuetoc.
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 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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".