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Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes
Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529539/ https://www.ncbi.nlm.nih.gov/pubmed/31113981 http://dx.doi.org/10.1038/s41598-019-43492-0 |
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author | Ragulan, Chanthirika Eason, Katherine Fontana, Elisa Nyamundanda, Gift Tarazona, Noelia Patil, Yatish Poudel, Pawan Lawlor, Rita T. Del Rio, Maguy Koo, Si-Lin Tan, Wah-Siew Sclafani, Francesco Begum, Ruwaida Teixeira Mendes, Larissa S. Martineau, Pierre Scarpa, Aldo Cervantes, Andrés Tan, Iain Beehuat Cunningham, David Sadanandam, Anguraj |
author_facet | Ragulan, Chanthirika Eason, Katherine Fontana, Elisa Nyamundanda, Gift Tarazona, Noelia Patil, Yatish Poudel, Pawan Lawlor, Rita T. Del Rio, Maguy Koo, Si-Lin Tan, Wah-Siew Sclafani, Francesco Begum, Ruwaida Teixeira Mendes, Larissa S. Martineau, Pierre Scarpa, Aldo Cervantes, Andrés Tan, Iain Beehuat Cunningham, David Sadanandam, Anguraj |
author_sort | Ragulan, Chanthirika |
collection | PubMed |
description | Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n = 237), a subset had matched microarray/RNAseq profiles (n = 47) or formalin-fixed paraffin-embedded (FFPE) samples (n = 58). We also analyzed a further 118 FFPE samples. We compared the assay results with the CMS classifier, different platforms (microarrays/RNAseq) and gene-set classifiers (38 and the original 786 genes). The standard and modified protocols showed high correlation (> 0.88) for gene expression. Technical replicates were highly correlated (> 0.96). NanoCRCA classified fresh frozen and FFPE samples into all five CRCA subtypes with consistent classification of selected matched fresh frozen/FFPE samples. We demonstrate high and significant subtype concordance across protocols (100%), gene sets (95%), platforms (87%) and with CMS subtypes (75%) when evaluated across multiple datasets. Overall, our NanoCRCA assay with further validation may facilitate prospective validation of CRC subtypes in clinical trials and beyond. |
format | Online Article Text |
id | pubmed-6529539 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65295392019-05-30 Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes Ragulan, Chanthirika Eason, Katherine Fontana, Elisa Nyamundanda, Gift Tarazona, Noelia Patil, Yatish Poudel, Pawan Lawlor, Rita T. Del Rio, Maguy Koo, Si-Lin Tan, Wah-Siew Sclafani, Francesco Begum, Ruwaida Teixeira Mendes, Larissa S. Martineau, Pierre Scarpa, Aldo Cervantes, Andrés Tan, Iain Beehuat Cunningham, David Sadanandam, Anguraj Sci Rep Article Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n = 237), a subset had matched microarray/RNAseq profiles (n = 47) or formalin-fixed paraffin-embedded (FFPE) samples (n = 58). We also analyzed a further 118 FFPE samples. We compared the assay results with the CMS classifier, different platforms (microarrays/RNAseq) and gene-set classifiers (38 and the original 786 genes). The standard and modified protocols showed high correlation (> 0.88) for gene expression. Technical replicates were highly correlated (> 0.96). NanoCRCA classified fresh frozen and FFPE samples into all five CRCA subtypes with consistent classification of selected matched fresh frozen/FFPE samples. We demonstrate high and significant subtype concordance across protocols (100%), gene sets (95%), platforms (87%) and with CMS subtypes (75%) when evaluated across multiple datasets. Overall, our NanoCRCA assay with further validation may facilitate prospective validation of CRC subtypes in clinical trials and beyond. Nature Publishing Group UK 2019-05-21 /pmc/articles/PMC6529539/ /pubmed/31113981 http://dx.doi.org/10.1038/s41598-019-43492-0 Text en © The Author(s) 2019 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 Ragulan, Chanthirika Eason, Katherine Fontana, Elisa Nyamundanda, Gift Tarazona, Noelia Patil, Yatish Poudel, Pawan Lawlor, Rita T. Del Rio, Maguy Koo, Si-Lin Tan, Wah-Siew Sclafani, Francesco Begum, Ruwaida Teixeira Mendes, Larissa S. Martineau, Pierre Scarpa, Aldo Cervantes, Andrés Tan, Iain Beehuat Cunningham, David Sadanandam, Anguraj Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes |
title | Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes |
title_full | Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes |
title_fullStr | Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes |
title_full_unstemmed | Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes |
title_short | Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes |
title_sort | analytical validation of multiplex biomarker assay to stratify colorectal cancer into molecular subtypes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529539/ https://www.ncbi.nlm.nih.gov/pubmed/31113981 http://dx.doi.org/10.1038/s41598-019-43492-0 |
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