OncoTherad® (MRB-CFI-1) Nanoimmunotherapy: A Promising Strategy to Treat Bacillus Calmette–Guérin-Unresponsive Non-Muscle-Invasive Bladder Cancer: Crosstalk among T-Cell CX3CR1, Immune Checkpoints, and the Toll-Like Receptor 4 Signaling Pathway
Bibliographic record
Abstract
This study assessed the safety and efficacy of OncoTherad® (MRB-CFI-1) nanoimmunotherapy for non-muscle invasive bladder cancer (NMIBC) patients unresponsive to Bacillus Calmette-Guérin (BCG) and explored its mechanisms of action in a bladder cancer microenvironment. A single-arm phase I/II study was conducted with 44 patients with NMIBC who were unresponsive to BCG treatment. Primary outcomes were pathological complete response (pCR) and relapse-free survival (RFS). Secondary outcomes comprised response duration and therapy safety. Patients’ mean age was 65 years; 59.1% of them were refractory, 31.8% relapsed, and 9.1% were intolerant to BCG. Moreover, the pCR rate after 24 months reached 72.7% (95% CI), whereas the mean RFS reached 21.4 months. Mean response duration in the pCR group was 14.3 months. No patient developed muscle-invasive or metastatic disease during treatment. Treatment-related adverse events occurred in 77.3% of patients, mostly grade 1–2 events. OncoTherad® activated the innate immune system through toll-like receptor 4, leading to increased interferon signaling. This activation played a crucial role in activating CX3CR1+ CD8 T cells, decreasing immune checkpoint molecules, and reversing immunosuppression in the bladder microenvironment. OncoTherad® has proved to be a safe and effective therapeutic option for patients with BCG-unresponsive NMIBC, besides showing likely advantages in tumor relapse prevention processes.
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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".