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QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability

RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analys...

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Autores principales: Jamalzadeh, Sanaz, Häkkinen, Antti, Andersson, Noora, Huhtinen, Kaisa, Laury, Anna, Hietanen, Sakari, Hynninen, Johanna, Oikkonen, Jaana, Carpén, Olli, Virtanen, Anni, Hautaniemi, Sampsa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249626/
https://www.ncbi.nlm.nih.gov/pubmed/35169222
http://dx.doi.org/10.1038/s41374-022-00743-5
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author Jamalzadeh, Sanaz
Häkkinen, Antti
Andersson, Noora
Huhtinen, Kaisa
Laury, Anna
Hietanen, Sakari
Hynninen, Johanna
Oikkonen, Jaana
Carpén, Olli
Virtanen, Anni
Hautaniemi, Sampsa
author_facet Jamalzadeh, Sanaz
Häkkinen, Antti
Andersson, Noora
Huhtinen, Kaisa
Laury, Anna
Hietanen, Sakari
Hynninen, Johanna
Oikkonen, Jaana
Carpén, Olli
Virtanen, Anni
Hautaniemi, Sampsa
author_sort Jamalzadeh, Sanaz
collection PubMed
description RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analysis. RNA-ISH experiments produce large amounts of data and there is a need for automated analysis methods. Here we present QuantISH, a comprehensive open-source RNA-ISH image analysis pipeline that quantifies marker expressions in individual carcinoma, immune, and stromal cells on chromogenic or fluorescent in situ hybridization images. QuantISH is designed to be modular and can be adapted to various image and sample types and staining protocols. We show that in chromogenic RNA in situ hybridization images of high-grade serous carcinoma (HGSC) QuantISH cancer cell classification has high precision, and signal expression quantification is in line with visual assessment. We further demonstrate the power of QuantISH by showing that CCNE1 average expression and DDIT3 expression variability, as captured by the variability factor developed herein, act as candidate biomarkers in HGSC. Altogether, our results demonstrate that QuantISH can quantify RNA expression levels and their variability in carcinoma cells, and thus paves the way to utilize RNA-ISH technology.
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spelling pubmed-92496262022-07-03 QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability Jamalzadeh, Sanaz Häkkinen, Antti Andersson, Noora Huhtinen, Kaisa Laury, Anna Hietanen, Sakari Hynninen, Johanna Oikkonen, Jaana Carpén, Olli Virtanen, Anni Hautaniemi, Sampsa Lab Invest Article RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analysis. RNA-ISH experiments produce large amounts of data and there is a need for automated analysis methods. Here we present QuantISH, a comprehensive open-source RNA-ISH image analysis pipeline that quantifies marker expressions in individual carcinoma, immune, and stromal cells on chromogenic or fluorescent in situ hybridization images. QuantISH is designed to be modular and can be adapted to various image and sample types and staining protocols. We show that in chromogenic RNA in situ hybridization images of high-grade serous carcinoma (HGSC) QuantISH cancer cell classification has high precision, and signal expression quantification is in line with visual assessment. We further demonstrate the power of QuantISH by showing that CCNE1 average expression and DDIT3 expression variability, as captured by the variability factor developed herein, act as candidate biomarkers in HGSC. Altogether, our results demonstrate that QuantISH can quantify RNA expression levels and their variability in carcinoma cells, and thus paves the way to utilize RNA-ISH technology. Nature Publishing Group US 2022-02-15 2022 /pmc/articles/PMC9249626/ /pubmed/35169222 http://dx.doi.org/10.1038/s41374-022-00743-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jamalzadeh, Sanaz
Häkkinen, Antti
Andersson, Noora
Huhtinen, Kaisa
Laury, Anna
Hietanen, Sakari
Hynninen, Johanna
Oikkonen, Jaana
Carpén, Olli
Virtanen, Anni
Hautaniemi, Sampsa
QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability
title QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability
title_full QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability
title_fullStr QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability
title_full_unstemmed QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability
title_short QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability
title_sort quantish: rna in situ hybridization image analysis framework for quantifying cell type-specific target rna expression and variability
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249626/
https://www.ncbi.nlm.nih.gov/pubmed/35169222
http://dx.doi.org/10.1038/s41374-022-00743-5
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