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Nat Commun. 2018 Jun 20;9(1):2419. doi: 10.1038/s41467-018-04724-5.

Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity.

Author information

1
Department of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden.
2
Department of Oncology-Pathology, Karolinska Institutet (KI), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden.
3
Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden.
4
Department of Clinical Pathology, University Uppsala Hospital, Rudbecklaboratoriet, Uppsala, 751 85, Sweden.
5
Department of Computational Biology, School of Computer Science and Communication, Royal Institute of Technology (KTH), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden.
6
Department of Oncology-Pathology, Karolinska Institutet (KI), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden. thomas.helleday@scilifelab.se.
7
Department of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden. joakim.lundeberg@scilifelab.se.

Abstract

Intra-tumor 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.

PMID:
29925878
PMCID:
PMC6010471
DOI:
10.1038/s41467-018-04724-5
[Indexed for MEDLINE]
Free PMC Article

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