# DOTA-based pre-targeting of alpha emitters

> **NIH NIH R01** · SLOAN-KETTERING INST CAN RESEARCH · 2020 · $726,157

## Abstract

Project Summary
We have optimized an image-guided, antibody-based method for multi-step targeting (MST) of radiolabeled β-
emitting therapeutics (β-MST) to human tumors that has resulted in tumoricidal radiation doses and
therapeutic indices (TI) of up to 120-fold between tumor and radiosensitive tissues. In preclinical studies, we
have met critical translational landmarks, namely: 1) cure of solid tumors without collateral normal organ
toxicity; and 2) detection of tumors of 10 mg or less, by non-invasive in vivo cross-sectional imaging in living
mice. We now propose a novel extension of MST to effectively target extremely potent short-range high LET α-
emitting isotopes (α-MST) that, if successful, would allow ideal α/β-MST stratification of therapy according to
disease characteristics, such as size, tumor geometry, antigen heterogeneity, blood flow, hypoxia, and genetic
composition—all features known to impact the effectiveness of radiation therapy to human tumors.
In this proposal, we will characterize the efficacy and toxicity of α-MST utilizing a novel carrier for the alpha-
emitting isotope actinium-225, which we call “225Ac-proteus-DOTA.” The proposed experimental studies have
been designed to assay the parameters responsible for tumor uptake of α-particles during α-MST (specific
activity, tumor-antigen density, and antibody-antigen complex internalization), develop an imaging surrogate for
dosimetry, and evaluate therapeutic efficacy and toxicity as a single treatment modality, or in combination with
β-MST. The methods include serial non-invasive positron emission tomographic (PET) imaging of the
individual components of the MST approach, ex vivo radioactivity counting of tissue samples, and
assessments of therapeutic response. A single-photon emission computed tomography (SPECT) imaging
surrogate is also proposed for companion dosimetry and treatment monitoring. The experimental system is
based on three antigen/antibody systems that have been studied extensively in patients: the anti-GPA33
antibody huA33 (colorectal cancer), anti-HER2 antibody trastuzumab (breast, ovarian, gastric), and anti-GD2
antibody hu3F8. Specifically, for α-MST, we will use an MST schema that features novel bi-specific tetravalent
anti-tumor antigen/-[M-DOTA] antibody constructs that react with both antigen (A33 or HER2) and radiometal-
DOTA with high specificity and binding affinity. These two systems were chosen based on their contrasting
membrane antibody-antigen internalization properties; huA33/GPA33 and trastuzumab/HER2 have slow and
fast turnover, respectively, which can have significant dosimetry implications for α-MST. This α-MST approach
will be studied in three different models in nude mice: a human colorectal cancer (SW1222) xenograft model, a
human breast cancer (BT474) xenograft model, and a patient-derived tumor model (GPA33-positive), but
importantly, can serve as a treatment guide for additional cancer types for which anti-tumor antigen/-[M-DOTA]...

## Key facts

- **NIH application ID:** 9834857
- **Project number:** 5R01CA233896-02
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Sarah Marie Cheal
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $726,157
- **Award type:** 5
- **Project period:** 2018-12-10 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9834857

## Citation

> US National Institutes of Health, RePORTER application 9834857, DOTA-based pre-targeting of alpha emitters (5R01CA233896-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9834857. Licensed CC0.

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