Fundamentals and Applications of Focused Ultrasound-Assisted Cancer Immune Checkpoint Inhibition for Solid Tumors
Bibliographic record
Abstract
Despite spectacular clinical successes across several cancer types, immune checkpoint inhibition is effective only in subgroups of patients and suffers from significant systemic toxicities, highlighting the need to understand and locally overcome the mechanisms of therapeutic resistance. Similarly to other therapeutics, immunotherapies face delivery challenges (for example, antibodies need to reach their targets) and immunological barriers that are unique to solid tumors and their microenvironment. Interestingly, focused ultrasound (FUS), with or without microbubbles, which has been shown to enhance gene and drug delivery, notably in oncology, has been recently found to trigger immunological responses. In recent years, there has been a strong emphasis on understanding the biological and immunological effects of FUS for cancer therapy, and FUS is now emerging as an approach that can improve cancer immunotherapy. We herein review: (1) the immunological barriers implicated in ICI resistance; (2) the fundamentals of FUS +/- MB and the current knowledge on leveraging FUS +/- MB bioeffects for improving ICI therapy efficacy; (3) the immune profile of tumor models that have been successfully treated with FUS and ICI; and finally, (4) we discuss the challenges ahead for translating FUS and MB treatments to the clinic, highlighting the exciting perspectives for this new research area.
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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 | 0.000 | 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) | 0.000 | 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".