MAPMET - Mapping metastatic cancer by multi-modal imaging
MAPMET - Mapping metastatic cancer by multi-modal imaging
Disciplines
Biology (20%); Computer Sciences (30%); Medical-Theoretical Sciences, Pharmacy (50%)
Keywords
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Pediatric Cancer,
Neuroblastoma,
Bone Marrow Metastasis,
Imaging Mass Cytometry,
Multi-Modal Imgaging,
Deep Learning
Metastasis to distant organs is the major cause of death in cancer patients. In many types of cancer metastasis occurs in the bone marrow, where normally cells of the immune system develop. Yet, very little is known about how these normal immune cells and tumor cells change when the latter metastasize to the bone marrow. In this study we investigate the cellular composition of bone marrow metastases in the childhood cancer neuroblastoma. To learn more about changes in the tumor cells, we compare the variety of different (heterogeneous) tumor cells in the primary tumor with the bone marrow metastasis and how cells are altered during therapy. On the other hand, we investigate changes in the immune microenvironment in the metastatic bone marrow. To do so, we use a combination of methods that allow us to investigate tumor tissue at very high, i.e. single cell, resolution: automated fluorescence microscopy, imaging mass cytometry and RNA-sequencing. Deep learning algorithms will help to align the microscopy images and detect cells and biomarkers. This multi-disciplinary project will lead to a better understanding of metastasis in childhood cancers and is expected to improve diagnosis of affected patients.
- Florian Halbritter, St. Anna Kinderkrebsforschung GmbH , national collaboration partner
- Bernd Bodenmiller, University of Zurich - Switzerland
Research Output
- 87 Citations
- 4 Publications
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2022
Title The evolutionary dynamics of extrachromosomal DNA in human cancers DOI 10.1038/s41588-022-01177-x Type Journal Article Author Lange J Journal Nature Genetics Pages 1527-1533 Link Publication -
2022
Title A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations DOI 10.1101/2022.11.21.515753 Type Preprint Author Saldana-Guerrero I Pages 2022.11.21.515753 Link Publication -
2024
Title Comparative transcriptomics coupled to developmental grading via transgenic zebrafish reporter strains identifies conserved features in neutrophil maturation DOI 10.1038/s41467-024-45802-1 Type Journal Article Author Kirchberger S Journal Nature Communications Pages 1792 Link Publication -
2024
Title FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection DOI 10.1007/978-3-031-73158-7_3 Type Book Chapter Author Gutwein S Publisher Springer Nature Pages 23-33