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Spatial Transcriptomics on prostate cancer heterogeneity

Intratumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

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
EGAD00001004121 NextSeq 500 14
Publications Citations
Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data.
Genome Biol 24: 2023 120
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