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An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours

Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoredu...

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Autores principales: Ong, Chin-Ann J., Tan, Qiu Xuan, Lim, Hui Jun, Shannon, Nicholas B., Lim, Weng Khong, Hendrikson, Josephine, Ng, Wai Har, Tan, Joey W. S., Koh, Kelvin K. N., Wasudevan, Seettha D., Ng, Cedric C. Y., Rajasegaran, Vikneswari, Lim, Tony Kiat Hon, Ong, Choon Kiat, Kon, Oi Lian, Teh, Bin Tean, Tan, Grace H. C., Chia, Claramae Shulyn, Soo, Khee Chee, Teo, Melissa C. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971024/
https://www.ncbi.nlm.nih.gov/pubmed/31959771
http://dx.doi.org/10.1038/s41598-019-55146-2
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author Ong, Chin-Ann J.
Tan, Qiu Xuan
Lim, Hui Jun
Shannon, Nicholas B.
Lim, Weng Khong
Hendrikson, Josephine
Ng, Wai Har
Tan, Joey W. S.
Koh, Kelvin K. N.
Wasudevan, Seettha D.
Ng, Cedric C. Y.
Rajasegaran, Vikneswari
Lim, Tony Kiat Hon
Ong, Choon Kiat
Kon, Oi Lian
Teh, Bin Tean
Tan, Grace H. C.
Chia, Claramae Shulyn
Soo, Khee Chee
Teo, Melissa C. C.
author_facet Ong, Chin-Ann J.
Tan, Qiu Xuan
Lim, Hui Jun
Shannon, Nicholas B.
Lim, Weng Khong
Hendrikson, Josephine
Ng, Wai Har
Tan, Joey W. S.
Koh, Kelvin K. N.
Wasudevan, Seettha D.
Ng, Cedric C. Y.
Rajasegaran, Vikneswari
Lim, Tony Kiat Hon
Ong, Choon Kiat
Kon, Oi Lian
Teh, Bin Tean
Tan, Grace H. C.
Chia, Claramae Shulyn
Soo, Khee Chee
Teo, Melissa C. C.
author_sort Ong, Chin-Ann J.
collection PubMed
description Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoreductive surgery (CRS), multiple spatially discrete tumour specimens could be systematically harvested for genomic analysis. To facilitate such downstream analyses, laser capture microdissection (LCM) could be utilized to obtain pure cell populations. The aim of this protocol study was to develop a methodology to obtain high-quality expression data from matched primary tumours and metastases by utilizing LCM to isolate pure cellular populations. We demonstrate an optimized LCM protocol which reproducibly delivered intact RNA used for RNA sequencing and quantitative polymerase chain reaction (qPCR). After pathologic annotation of normal epithelial, tumour and stromal components, LCM coupled with cDNA library generation provided for successful RNA sequencing. To illustrate our framework’s potential to identify targets that would otherwise be missed with conventional bulk tumour sequencing, we performed qPCR and immunohistochemical technical validation to show that the genes identified were truly expressed only in certain sub-components. This study suggests that the combination of matched tissue specimens with tissue microdissection and NGS provides a viable platform to unmask hidden biomarkers and provides insight into tumour biology at a higher resolution.
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spelling pubmed-69710242020-01-27 An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours Ong, Chin-Ann J. Tan, Qiu Xuan Lim, Hui Jun Shannon, Nicholas B. Lim, Weng Khong Hendrikson, Josephine Ng, Wai Har Tan, Joey W. S. Koh, Kelvin K. N. Wasudevan, Seettha D. Ng, Cedric C. Y. Rajasegaran, Vikneswari Lim, Tony Kiat Hon Ong, Choon Kiat Kon, Oi Lian Teh, Bin Tean Tan, Grace H. C. Chia, Claramae Shulyn Soo, Khee Chee Teo, Melissa C. C. Sci Rep Article Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoreductive surgery (CRS), multiple spatially discrete tumour specimens could be systematically harvested for genomic analysis. To facilitate such downstream analyses, laser capture microdissection (LCM) could be utilized to obtain pure cell populations. The aim of this protocol study was to develop a methodology to obtain high-quality expression data from matched primary tumours and metastases by utilizing LCM to isolate pure cellular populations. We demonstrate an optimized LCM protocol which reproducibly delivered intact RNA used for RNA sequencing and quantitative polymerase chain reaction (qPCR). After pathologic annotation of normal epithelial, tumour and stromal components, LCM coupled with cDNA library generation provided for successful RNA sequencing. To illustrate our framework’s potential to identify targets that would otherwise be missed with conventional bulk tumour sequencing, we performed qPCR and immunohistochemical technical validation to show that the genes identified were truly expressed only in certain sub-components. This study suggests that the combination of matched tissue specimens with tissue microdissection and NGS provides a viable platform to unmask hidden biomarkers and provides insight into tumour biology at a higher resolution. Nature Publishing Group UK 2020-01-20 /pmc/articles/PMC6971024/ /pubmed/31959771 http://dx.doi.org/10.1038/s41598-019-55146-2 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ong, Chin-Ann J.
Tan, Qiu Xuan
Lim, Hui Jun
Shannon, Nicholas B.
Lim, Weng Khong
Hendrikson, Josephine
Ng, Wai Har
Tan, Joey W. S.
Koh, Kelvin K. N.
Wasudevan, Seettha D.
Ng, Cedric C. Y.
Rajasegaran, Vikneswari
Lim, Tony Kiat Hon
Ong, Choon Kiat
Kon, Oi Lian
Teh, Bin Tean
Tan, Grace H. C.
Chia, Claramae Shulyn
Soo, Khee Chee
Teo, Melissa C. C.
An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours
title An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours
title_full An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours
title_fullStr An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours
title_full_unstemmed An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours
title_short An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours
title_sort optimised protocol harnessing laser capture microdissection for transcriptomic analysis on matched primary and metastatic colorectal tumours
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971024/
https://www.ncbi.nlm.nih.gov/pubmed/31959771
http://dx.doi.org/10.1038/s41598-019-55146-2
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