MétaCan
Menu
Back to cohort
Record W3166933213

PET imaging cancer stem cells using a novel zirconium-89 labelled fully human anti-CD133 antibody

2021· article· en· W3166933213 on OpenAlexaff
Kevin Wyszatko, John F. Valliant, Saman Sadeghi, Sheila K. Singh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiodistributionIn vivoConjugateChemistryAntibodyRadioimmunotherapyPositron emission tomographyCancerCancer researchSpect imagingCancer stem cellStem cellImaging agentMolecular imagingNuclear medicineIn vitroMolecular biologyMonoclonal antibodyMedicineBiochemistryImmunologyBiologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

154 Introduction: Cancer stem cells (CSCs) identified by the CD133 antigen constitute a treatment refractory tumor subpopulation liable to repopulate tumors following therapy. We present [89Zr]Zr-DFO-RW03, a PET imaging probe for CD133 consisting of a novel fully human antibody labelled with long lived positron emitting radioisotope ziconium-89, for use in diagnostic imaging and as a companion diagnostic to cancer stem cell targeted therapy. The stable and highly pure radiolabeled conjugate shows affinity to CD133 in vitro, and in vivo biodistribution and imaging studies demonstrate receptor mediated uptake for tumor delineation in a xenograft mouse model. Methods: We used a robust conjugation strategy to attach 3 molar equivalents of bifunctional chelator DFO-Bn-NCS to RW03 and radiolabeled the DFO-RW03 conjugate with [89Zr]Zr-oxalate to yield [89Zr]Zr-DFO-RW03. The radiolabeled product was incubated, in increasing concentrations, with CD133 expressing HT-29 cells to determine the KD by fitting with a one-site binding curve. In vivo, BALB/c nu/nu mice bearing HT-29 xenografts were injected with 0.185 MBq (2 µg) of [89Zr]Zr-DFO-RW03 and sacrificed after 24, 48, 96 h for organ collection and gamma counting. In a second study, tumor bearing mice were injected with 0.185 MBq (2 µg) of [89Zr]Zr-DFO-RW03 and a 250x mass excess (500 µg) cold antibody block, followed by sacrifice after 96 h and organ counting. For PET imaging, HT-29 bearing mice were injected with 5.5 MBq (35 µg) [89Zr]Zr-DFO-RW03 and imaged over 1 week. ROIs were selected and compared to ex vivo biodistribution, while intratumoral heterogeneity and tumor to muscle ratio was further established using autoradiography. Results: Radiolabeled [89Zr]Zr-DFO-RW03 had high specific activity (>148 MBq/mg) with >99% radiochemical purity, while retaining high affinity for CD133 (KD 15 %ID/g after 96 h with high tumor-to-blood ratio (>5:1) and low bone uptake ( 6:1). Conclusions: Novel CD133 targeted PET imaging probe [89Zr]Zr-DFO-RW03 was syntheized with high specific activty and radiochemical purity and demonstrated CD133 binding both in vitro and in vivo using the model CD133 expressing HT-29 cell line. Tumor uptake was specific for CD133 and heterogenous within the tumor, particularly high in the tumor core, and offering good contrast with background tissue. The probe represents a promising candidate for diagnostic imaging or companion diagnostics in the clinic. Acknowledgements: Support for this work includes OICR, CIHR and OGS funding. We are thankful for STTARR Imaging (UHN) for their help in this work, and for the contributions from all members of McMaster’s Radiochemistry Group and Dr. Sheila Singh’s research team at McMaster University.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.060
GPT teacher head0.397
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicRadiopharmaceutical Chemistry and ApplicationsFrench-language works237,207