Auger electrons for cancer therapy – a review
Bibliographic record
Abstract
Abstract Background Auger electrons (AEs) are very low energy electrons that are emitted by radionuclides that decay by electron capture (e.g. 111 In, 67 Ga, 99m Tc, 195m Pt, 125 I and 123 I). This energy is deposited over nanometre-micrometre distances, resulting in high linear energy transfer (LET) that is potent for causing lethal damage in cancer cells. Thus, AE-emitting radiotherapeutic agents have great potential for treatment of cancer. In this review, we describe the radiobiological properties of AEs, their radiation dosimetry, radiolabelling methods, and preclinical and clinical studies that have been performed to investigate AEs for cancer treatment. Results AEs are most lethal to cancer cells when emitted near the cell nucleus and especially when incorporated into DNA (e.g. 125 I-IUdR). AEs cause DNA damage both directly and indirectly via water radiolysis. AEs can also kill targeted cancer cells by damaging the cell membrane, and kill non-targeted cells through a cross-dose or bystander effect. The radiation dosimetry of AEs considers both organ doses and cellular doses. The Medical Internal Radiation Dose (MIRD) schema may be applied. Radiolabelling methods for complexing AE-emitters to biomolecules (antibodies and peptides) and nanoparticles include radioiodination ( 125 I and 123 I) or radiometal chelation ( 111 In, 67 Ga, 99m Tc). Cancer cells exposed in vitro to AE-emitting radiotherapeutic agents exhibit decreased clonogenic survival correlated at least in part with unrepaired DNA double-strand breaks (DSBs) detected by immunofluorescence for γH2AX, and chromosomal aberrations. Preclinical studies of AE-emitting radiotherapeutic agents have shown strong tumour growth inhibition in vivo in tumour xenograft mouse models. Minimal normal tissue toxicity was found due to the restricted toxicity of AEs mostly on tumour cells targeted by the radiotherapeutic agents. Clinical studies of AEs for cancer treatment have been limited but some encouraging results were obtained in early studies using 111 In-DTPA-octreotide and 125 I-IUdR, in which tumour remissions were achieved in several patients at administered amounts that caused low normal tissue toxicity, as well as promising improvements in the survival of glioblastoma patients with 125 I-mAb 425, with minimal normal tissue toxicity. Conclusions Proof-of-principle for AE radiotherapy of cancer has been shown preclinically, and clinically in a limited number of studies. The recent introduction of many biologically-targeted therapies for cancer creates new opportunities to design novel AE-emitting agents for cancer treatment. Pierre Auger did not conceive of the application of AEs for targeted cancer treatment, but this is a tremendously exciting future that we and many other scientists in this field envision.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".