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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

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 signalin...

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Autores principales: Svedlund, Jessica, Strell, Carina, Qian, Xiaoyan, Zilkens, Kilian J.C., Tobin, Nicholas P., Bergh, Jonas, Sieuwerts, Anieta M., Nilsson, Mats
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838368/
https://www.ncbi.nlm.nih.gov/pubmed/31526717
http://dx.doi.org/10.1016/j.ebiom.2019.09.009
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author Svedlund, Jessica
Strell, Carina
Qian, Xiaoyan
Zilkens, Kilian J.C.
Tobin, Nicholas P.
Bergh, Jonas
Sieuwerts, Anieta M.
Nilsson, Mats
author_facet Svedlund, Jessica
Strell, Carina
Qian, Xiaoyan
Zilkens, Kilian J.C.
Tobin, Nicholas P.
Bergh, Jonas
Sieuwerts, Anieta M.
Nilsson, Mats
author_sort Svedlund, Jessica
collection PubMed
description 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: ISS 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. FUND: Swedish Cancerfonden, UCAN, Vetenskapsrådet, Cancer Genomics Netherlands, Iris, Stig och Gerry Castenbäcks Stiftelse, BRECT, PCM Program, King Gustaf V Jubilee Fund, BRO, KI and Stockholm County Council, Alice Wallenberg Foundation.
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spelling pubmed-68383682019-11-12 Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer Svedlund, Jessica Strell, Carina Qian, Xiaoyan Zilkens, Kilian J.C. Tobin, Nicholas P. Bergh, Jonas Sieuwerts, Anieta M. Nilsson, Mats EBioMedicine Research paper 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: ISS 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. FUND: Swedish Cancerfonden, UCAN, Vetenskapsrådet, Cancer Genomics Netherlands, Iris, Stig och Gerry Castenbäcks Stiftelse, BRECT, PCM Program, King Gustaf V Jubilee Fund, BRO, KI and Stockholm County Council, Alice Wallenberg Foundation. Elsevier 2019-09-13 /pmc/articles/PMC6838368/ /pubmed/31526717 http://dx.doi.org/10.1016/j.ebiom.2019.09.009 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Svedlund, Jessica
Strell, Carina
Qian, Xiaoyan
Zilkens, Kilian J.C.
Tobin, Nicholas P.
Bergh, Jonas
Sieuwerts, Anieta M.
Nilsson, Mats
Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
title Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
title_full Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
title_fullStr Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
title_full_unstemmed Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
title_short Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
title_sort generation of in situ sequencing based oncomaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838368/
https://www.ncbi.nlm.nih.gov/pubmed/31526717
http://dx.doi.org/10.1016/j.ebiom.2019.09.009
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