Imaging mass cytometry dataset of small-cell lung cancer tumors and tumor microenvironments

France Rose ^1,2, Olta Ibruli ^3,4, Luca Lichius ⁵

¹Center for Molecular Medicine Cologne, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany. france.rose@wanadoo.fr.
²Institute for Biomedical Informatics, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany. france.rose@wanadoo.fr.
³Department of Translational Genomics, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
⁴Department I of Internal Medicine, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
⁵Department II of Internal Medicine, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
⁶Center for Molecular Medicine Cologne, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
⁷Mildred Scheel School of Oncology Aachen Bonn Cologne Düsseldorf (MSSO ABCD), Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
⁸Department of Radiation Oncology and Cyberknife Center, Faculty of Medicine, University Hospital of Cologne, University of Cologne, Cologne, Germany.
⁹Department of Radiation Oncology, MVZ Prof. Dr. Uhlenbrock und Partner, Gesundheitscampus Josephs-Hospital, Warendorf, Germany.
¹⁰Institute for Diagnostic and Interventional Radiology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
¹¹Institute of Pathology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
¹²Department of Otorhinolaryngology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, Cologne, Germany.
¹³Department of Hematology and Stem Cell Transplantation, Germany 19 Center for Molecular Biotechnology, University Hospital Essen, Essen, Germany.
¹⁴West German Cancer Center, University Hospital Essen, Essen, Germany.
¹⁵Germany 20 Department of Medical Oncology, Fachklinik Hornheide, Münster, Germany.
¹⁶DKTK Partner Site Essen/Düsseldorf, University Hospital Essen, Essen, Germany.
¹⁷Center for Molecular Biotechnology, University Hospital Essen, Essen, Germany.
¹⁸Institute for Biomedical Informatics, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.

⁰Center for Molecular Medicine Cologne, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany. france.rose@wanadoo.fr.

Bmc Research Notes +

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September 8, 2025

View abstract on PubMed

Summary

This study used imaging mass cytometry to analyze small cell lung cancer (SCLC) mouse models. The data reveal insights into tumor composition and microenvironment interactions for SCLC research.

Area Of Science

Oncology
Immunology
Biotechnology

Background

Small cell lung cancer (SCLC) is an aggressive malignancy comprising 15% of lung tumors, characterized by rapid growth and early metastasis.
Understanding the tumor microenvironment and cellular composition is crucial for developing effective SCLC therapies.

Purpose Of The Study

To investigate the tumor composition, spatial architecture, and microenvironment interactions in two SCLC mouse models with varying tumor mutation burdens (TMB).
To provide a valuable dataset for studying the histological and cellular complexity of SCLC.

Main Methods

Utilized two genetically controlled SCLC mouse models with differing TMB.
Acquired multiplexed images of lung tumors using imaging mass cytometry (IMC) with a 37-marker panel.
Sampled tumor center and border regions, providing tumor masks and metadata for downstream analysis.

Main Results

Generated high-resolution IMC data characterizing major cell types (tumor, immune, structural) and their functional states within SCLC tumors.
Enabled detailed spatial analysis of tumor composition and cellular interactions within the tumor microenvironment.
Facilitated the examination of SCLC heterogeneity across different therapeutic conditions.

Conclusions

The IMC dataset provides a comprehensive resource for dissecting the complex cellular and spatial landscape of SCLC.
This study enhances our understanding of SCLC biology and offers a foundation for future therapeutic target identification.
The data support further research into SCLC progression and treatment response within a controlled experimental setting.

Keywords:

Hyperion IMC MIBI-TOF Mouse models SCLC Tumor microenvironment