# Combining targeted radionuclide therapy with  a localized in situ vaccine to overcome immune suppression in the tumor microenvironment and augment T cell responses

> **NIH NIH P01** · UNIVERSITY OF WISCONSIN-MADISON · 2024 · $296,214

## Abstract

PROJECT SUMMARY - PROJECT 3: We are developing a combination of immunotherapy (ImmRx) and
radiotherapy (RT) that shows potent synergy in eradicating cancer in mice with multiple sites of immunologically
“cold” tumors, which have few infiltrating T cells and do not respond to immune checkpoint inhibition (ICI).
Virtually all pediatric cancers and most cancers of adults are cold, with few mutations or neoantigens. We are
now taking a systematic approach to enable potent immune-induced eradication of most cold tumors aimed
towards clinical translation. We have eradicated large, cold tumors in mice by combining immunomodulatory (12
Gy) external beam RT (EBRT) with intratumoral (IT) injection of tumor-specific antibody (mAb) + IL2. This
approach induces T-cell infiltration into these tumors, potent T-cell memory, epitope spread, and protection from
tumor re-challenge. However, the presence of an identical but untreated second tumor (2°) on a mouse’s
opposite flank inhibits the effect of this treatment, preventing eradication of the primary (1°) tumor treated with
EBRT + IT mAb-IL2. In this setting, the untreated 2° tumor causes tumor-specific immune unresponsiveness to
EBRT + IT mAb-IL2 at the 1° tumor. We refer to this as concomitant immune tolerance (CIT). We can overcome
CIT and eliminate both tumors by giving IT mAb-IL2 to the 1° tumor and EBRT to both the 1° and 2° tumors.
Delivering as little as 2-5 Gy RT to the 2° tumor can overcome CIT. However, the provision of systemic EBRT to
treat many sites of metastases is problematic, due to systemic immune suppression from EBRT; but this can
effectively be achieved without immune-suppression using molecular targeted radionuclide therapy (TRT).
 131I-MIBG is a common TRT for neuroblastoma (NBL). Our University of Wisconsin P01 team has led
preclinical/clinical testing of a novel TRT using alkyl-phospho-choline (APCh) analogs that selectively deliver
radionuclides to cancers in vivo. These show >10-fold uptake over 131I-MIBG in NBL xenografts, but unlike MIBG,
show similar uptake in NBL and virtually all tumors tested. Our lead-candidate form of TRT, 90Y-NM600 has
many conceptual and clinical advantages over 131I-MIBG, including potential outpatient treatment with no need
for patient isolation. We have demonstrated potent synergy with 90Y-NM600 and ImmRx in our mouse models.
 This project expands the ongoing collaborative progress of the several collaborative projects and cores in
this P01 proposal to systematically develop the potency of combining TRT with our combination ImmRx. We will
pursue this synergy in immunocompetent mouse models of cold NBL and sarcomas. Our in vivo goal is the ability
to use TRT to help eradicate all cancer in mice bearing macroscopic tumors in two separate sites as well as
disseminated micro-metastases. We will carefully analyze tumor and immune parameters at the histological,
cellular, and molecular levels in treated and control mice and in mice that are cured vs. mice that ...

## Key facts

- **NIH application ID:** 10873216
- **Project number:** 5P01CA250972-05
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** PAUL M SONDEL
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $296,214
- **Award type:** 5
- **Project period:** 2020-09-14 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10873216

## Citation

> US National Institutes of Health, RePORTER application 10873216, Combining targeted radionuclide therapy with  a localized in situ vaccine to overcome immune suppression in the tumor microenvironment and augment T cell responses (5P01CA250972-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10873216. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*