Breast cancer sequencing data

1 Dataset 2 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001011061	The dataset includes spatially-resolved and single-cell antigen receptor, as well as gene expression, data from two different HER2+ breast cancer patients. The tumor piece obtained during surgery from each patient was divided into several regions and tissue sections were used for spatial transcriptomics (Visium, 10x genomics). As indicated, some tissue sections were analyzed by a new method (Spatial VDJ) to spatially resolve antigen receptor sequences (target capture), which was developed in our publication. In parallel, tissue pieces from the same tumor were dissociated for single-cell gene expression analysis (10x genomics GEX, VDJ, and feature barcoding/Hash Tag Oligonucleotide). The deposited data is in the form of fastq files. All processed data, metadata, micrographs of the tissue sections (of those used for spatial transcriptomics), and scripts used for the analysis are publicly available at Zenodo (DOI: 10.5281/zenodo.7961605). Final libraries were sequenced on NextSeq2000 (Illumina) or NovaSeq6000 (Illumina) and analyzed with Cell Ranger, Seurat, Space Ranger, and STutility pipelines.	Illumina NovaSeq 6000 NextSeq 550 Sequel	43

Publications	Citations
Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope. Shafighi S, Geras A, Jurzysta B, Sahaf Naeini A, Filipiuk I, Rączkowska A, Toosi H, Koperski Ł, Thrane K, Engblom C, Mold JE, Chen X, Hartman J, Nowis D, Carbone A, Lagergren J, Szczurek E. Nat Commun 15: 2024 9343	8
Computational pathology annotation enhances the resolution and interpretation of breast cancer spatial transcriptomics data. Li T, Yang Q, Acs B, Sifakis EG, Toosi H, Engblom C, Thrane K, Lin Q, Mold JE, Sun W, Boyaci C, Steen S, Frisén J, Lagergren J, Lundeberg J, Chen X, Hartman J. NPJ Precis Oncol 9: 2025 310	0