Localization and Tumor Growth Inhibition of I-131-Labeled Monoclonal Antibody ERIC1 in a Subcutaneous Xenograft Model of Small Cell Lung Cancer in SCID Mice

This study evaluates the efficacy of [<sup>131</sup>I]I-ERIC1 in targeting and inhibiting the growth of SCLC tumors in mice, focusing on tumor accumulation and regression and potential side effects. NCAM-positive NCI-H69 SCLC cells were implanted in CB 17 SCID mice, and [<sup>131</sup>I]I-ERIC1 biokinetics were measured in organs and tissues at four post-injection time points (24, 72, 96, and 120 h). The experimental series compared tumor growth, survival, and changes in blood counts among three treatment groups (1, 2, or 3 MBq) and a control group, with treatments initiated either two or five days post implantation. [<sup>131</sup>I]I-ERIC1 was synthesized with >95% radiochemical purity and a specific activity of 15 TBq/mmol. Tumor activity peaked at 31.5 ± 6.6% ID/g after four days, demonstrating significant antitumor efficacy, which resulted in sustained remission and extended survival. Hematological toxicity was observed, with the optimal dose identified as 2 MBq per animal administered two days post implantation. [<sup>131</sup>I]I-ERIC1 shows promise as a theranostic agent for personalized cancer treatment by effectively targeting SCLC tumors with manageable side effects. However, further studies are required to optimize dosing strategies and minimize toxicity.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2024-10-02
DOI
https://doi.org/10.3390/ijms251910638
Primary Topic
Lung Cancer Research Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Localization and Tumor Growth Inhibition of I-131-Labeled Monoclonal Antibody ERIC1 in a Subcutaneous Xenograft Model of Small Cell Lung Cancer in SCID Mice

F. Sudbrock, Klaus Schomäcker, Markus Dietlein, Felix Dietlein et al.
International Journal of Molecular Sciences
Lung Cancer Research Studies
article

Localization and Tumor Growth Inhibition of I-131-Labeled Monoclonal Antibody ERIC1 in a Subcutaneous Xenograft Model of Small Cell Lung Cancer in SCID Mice

F. Sudbrock, Klaus Schomäcker, Markus Dietlein, Felix Dietlein, Sergio Muñoz Vázquez, Philipp Krapf, Beate Zimmermanns, Thomas Fischer, Alexander Drzezga, Christopher Dietrich
article en

Abstract

This study evaluates the efficacy of [<sup>131</sup>I]I-ERIC1 in targeting and inhibiting the growth of SCLC tumors in mice, focusing on tumor accumulation and regression and potential side effects. NCAM-positive NCI-H69 SCLC cells were implanted in CB 17 SCID mice, and [<sup>131</sup>I]I-ERIC1 biokinetics were measured in organs and tissues at four post-injection time points (24, 72, 96, and 120 h). The experimental series compared tumor growth, survival, and changes in blood counts among three treatment groups (1, 2, or 3 MBq) and a control group, with treatments initiated either two or five days post implantation. [<sup>131</sup>I]I-ERIC1 was synthesized with >95% radiochemical purity and a specific activity of 15 TBq/mmol. Tumor activity peaked at 31.5 ± 6.6% ID/g after four days, demonstrating significant antitumor efficacy, which resulted in sustained remission and extended survival. Hematological toxicity was observed, with the optimal dose identified as 2 MBq per animal administered two days post implantation. [<sup>131</sup>I]I-ERIC1 shows promise as a theranostic agent for personalized cancer treatment by effectively targeting SCLC tumors with manageable side effects. However, further studies are required to optimize dosing strategies and minimize toxicity.

International Journal of Molecular SciencesVol. 25(19)
Boston Children's Hospital (US), Harvard University (US), Forschungszentrum Jülich (DE), University of Cologne (DE), German Center for Neurodegenerative Diseases (DE), University Hospital Cologne (DE)
Good health and well-being
Openalex Percentile: Top 69%
Lung Cancer Research Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.