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Record W4396644643 · doi:10.1186/s41181-024-00266-y

Radiation nanomedicines for cancer treatment: a scientific journey and view of the landscape

2024· article· en· W4396644643 on OpenAlexafffund
Raymond M. Reilly, Constantine J. Georgiou, Madeline K. Brown, Zhongli Cai

Bibliographic record

VenueEJNMMI Radiopharmacy and Chemistry · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersTerry Fox FoundationNatural Sciences and Engineering Research Council of CanadaBrain Tumour Foundation of CanadaUniversity of TorontoCanadian Cancer Society
KeywordsBiodistributionBreast cancerCancer researchNanomedicineColloidal goldCancerBrachytherapyMedicineRadiation therapyAbscopal effectNuclear medicineChemistryPathologyNanoparticleInternal medicineNanotechnologyMaterials scienceImmunotherapyIn vitroBiochemistry

Abstract

fetched live from OpenAlex

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 111 In 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, [ 111 In]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 177 Lu 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 [ 90 Y]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 [ 177 Lu]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 ( 111 In, 99m Tc, 125 I, 103 Pd, 193m Pt, 195m Pt), β-particles ( 177 Lu, 186 Re, 188 Re, 90 Y, 198 Au, 131 I) or α-particles ( 225 Ac, 213 Bi, 212 Pb, 211 At, 223 Ra). 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.321
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2024
Admission routes2
Has abstractyes

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