Radiation nanomedicines for cancer treatment: a scientific journey and view of the landscape
Bibliographic record
Abstract
Abstract Background Radiation nanomedicines are nanoparticles labeled with radionuclides that emit α- or β-particles or Auger electrons for cancer treatment. We describe here our 15 years scientific journey studying locally-administered radiation nanomedicines for cancer treatment. We further present a view of the radiation nanomedicine landscape by reviewing research reported by other groups. Main body Gold nanoparticles were studied initially for radiosensitization of breast cancer to X-radiation therapy. These nanoparticles were labeled with 111In to assess their biodistribution after intratumoural vs. intravenous injection. Intravenous injection was limited by high liver and spleen uptake and low tumour uptake, while intratumoural injection provided high tumour uptake but low normal tissue uptake. Further, [111In]In-labeled gold nanoparticles modified with trastuzumab and injected iintratumourally exhibited strong tumour growth inhibition in mice with subcutaneous HER2-positive human breast cancer xenografts. In subsequent studies, strong tumour growth inhibition in mice was achieved without normal tissue toxicity in mice with human breast cancer xenografts injected intratumourally with gold nanoparticles labeled with β-particle emitting 177Lu and modified with panitumumab or trastuzumab to specifically bind EGFR or HER2, respectively. A nanoparticle depot (nanodepot) was designed to incorporate and deliver radiolabeled gold nanoparticles to tumours using brachytherapy needle insertion techniques. Treatment of mice with s.c. 4T1 murine mammary carcinoma tumours with a nanodepot incorporating [90Y]Y-labeled gold nanoparticles inserted into one tumour arrested tumour growth and caused an abscopal growth-inhibitory effect on a distant second tumour. Convection-enhanced delivery of [177Lu]Lu-AuNPs to orthotopic human glioblastoma multiforme (GBM) tumours in mice arrested tumour growth without normal tissue toxicity. Other groups have explored radiation nanomedicines for cancer treatment in preclinical animal tumour xenograft models using gold nanoparticles, liposomes, block copolymer micelles, dendrimers, carbon nanotubes, cellulose nanocrystals or iron oxide nanoparticles. These nanoparticles were labeled with radionuclides emitting Auger electrons (111In, 99mTc, 125I, 103Pd, 193mPt, 195mPt), β-particles (177Lu, 186Re, 188Re, 90Y, 198Au, 131I) or α-particles (225Ac, 213Bi, 212Pb, 211At, 223Ra). These studies employed intravenous or intratumoural injection or convection enhanced delivery. Local administration of these radiation nanomedicines was most effective and minimized normal tissue toxicity. Conclusions Radiation nanomedicines have shown great promise for treating cancer in preclinical studies. Local intratumoural administration avoids sequestration by the liver and spleen and is most effective for treating tumours, while minimizing normal tissue toxicity.
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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".