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Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.ORCID iD: 0000-0001-7509-8071
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
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Number of Authors: 82019 (English)In: EBioMedicine, E-ISSN 2352-3964, Vol. 48, p. 212-223Article in journal (Refereed) Published
Abstract [en]

Background: Gene expression analysis of breast cancer largely relies on homogenized tissue samples. Due to the high degree of cellular and molecular heterogeneity of tumor tissues, bulk tissue-based analytical approaches can only provide very limited system-level information about different signaling mechanisms and cellular interactions within the complex tissue context. Methods: We describe an analytical approach using in situ sequencing (ISS), enabling highly multiplexed, spatially and morphologically resolved gene expression profiling. Ninety-one genes including prognostic and predictive marker profiles, as well as genes involved in specific cellular pathways were mapped within whole breast cancer tissue sections, covering luminal A/B-like, HER2-positive and triple negative tumors. Finally, all these features were combined and assembled into a molecular-morphological OncoMap for each tumor tissue. Findings: Our in situ approach spatially revealed intratumoral heterogeneity with regard to tumor subtype as well as to the OncotypeDX recurrence score and even uncovered areas of minor cellular subpopulations. Since ISS-resolved molecular profiles are linked to their histological context, a deeper analysis of the core and periphery of tumor foci enabled identification of specific gene expression patterns associated with these morphologically relevant regions. Interpretation :15S generated OncoMaps represent useful tools to extend our general understanding of the biological processes behind tumor progression and can further support the identification of novel therapeutical targets as well as refine tumor diagnostics.

Place, publisher, year, edition, pages
2019. Vol. 48, p. 212-223
Keywords [en]
Breast cancer, Tumor heterogeneity, Gene expression analysis, Diagnostic, Prognostic
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:su:diva-176757DOI: 10.1016/j.ebiom.2019.09.009ISI: 000493830800028PubMedID: 31526717OAI: oai:DiVA.org:su-176757DiVA, id: diva2:1377164
Available from: 2019-12-11 Created: 2019-12-11 Last updated: 2019-12-12Bibliographically approved

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Strell, CarinaQian, XiaoyanTobin, Nicholas P.Nilsson, Mats
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