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Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality
Immunotherapy has reshaped the field of cancer therapeutics but the population that benefits are small in many tumor types, warranting a companion diagnostic test. While immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) or mismatch repair (MMR) and polymerase chain reaction (PCR) for...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163775/ https://www.ncbi.nlm.nih.gov/pubmed/34050252 http://dx.doi.org/10.1038/s41698-021-00184-1 |
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author | Vathiotis, Ioannis A. Yang, Zhi Reeves, Jason Toki, Maria Aung, Thazin Nwe Wong, Pok Fai Kluger, Harriet Syrigos, Konstantinos N. Warren, Sarah Rimm, David L. |
author_facet | Vathiotis, Ioannis A. Yang, Zhi Reeves, Jason Toki, Maria Aung, Thazin Nwe Wong, Pok Fai Kluger, Harriet Syrigos, Konstantinos N. Warren, Sarah Rimm, David L. |
author_sort | Vathiotis, Ioannis A. |
collection | PubMed |
description | Immunotherapy has reshaped the field of cancer therapeutics but the population that benefits are small in many tumor types, warranting a companion diagnostic test. While immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) or mismatch repair (MMR) and polymerase chain reaction (PCR) for microsatellite instability (MSI) are the only approved companion diagnostics others are under consideration. An optimal companion diagnostic test might combine the spatial information of IHC with the quantitative information from RNA expression profiling. Here, we show proof of concept for combination of spatially resolved protein information acquired by the NanoString GeoMx® Digital Spatial Profiler (DSP) with transcriptomic information from bulk mRNA gene expression acquired using NanoString nCounter® PanCancer IO 360™ panel on the same cohort of immunotherapy treated melanoma patients to create predictive models associated with clinical outcomes. We show that the combination of mRNA and spatially defined protein information can predict clinical outcomes more accurately (AUC 0.97) than either of these factors alone. |
format | Online Article Text |
id | pubmed-8163775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81637752021-06-10 Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality Vathiotis, Ioannis A. Yang, Zhi Reeves, Jason Toki, Maria Aung, Thazin Nwe Wong, Pok Fai Kluger, Harriet Syrigos, Konstantinos N. Warren, Sarah Rimm, David L. NPJ Precis Oncol Brief Communication Immunotherapy has reshaped the field of cancer therapeutics but the population that benefits are small in many tumor types, warranting a companion diagnostic test. While immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) or mismatch repair (MMR) and polymerase chain reaction (PCR) for microsatellite instability (MSI) are the only approved companion diagnostics others are under consideration. An optimal companion diagnostic test might combine the spatial information of IHC with the quantitative information from RNA expression profiling. Here, we show proof of concept for combination of spatially resolved protein information acquired by the NanoString GeoMx® Digital Spatial Profiler (DSP) with transcriptomic information from bulk mRNA gene expression acquired using NanoString nCounter® PanCancer IO 360™ panel on the same cohort of immunotherapy treated melanoma patients to create predictive models associated with clinical outcomes. We show that the combination of mRNA and spatially defined protein information can predict clinical outcomes more accurately (AUC 0.97) than either of these factors alone. Nature Publishing Group UK 2021-05-28 /pmc/articles/PMC8163775/ /pubmed/34050252 http://dx.doi.org/10.1038/s41698-021-00184-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Brief Communication Vathiotis, Ioannis A. Yang, Zhi Reeves, Jason Toki, Maria Aung, Thazin Nwe Wong, Pok Fai Kluger, Harriet Syrigos, Konstantinos N. Warren, Sarah Rimm, David L. Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
title | Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
title_full | Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
title_fullStr | Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
title_full_unstemmed | Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
title_short | Models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
title_sort | models that combine transcriptomic with spatial protein information exceed the predictive value for either single modality |
topic | Brief Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163775/ https://www.ncbi.nlm.nih.gov/pubmed/34050252 http://dx.doi.org/10.1038/s41698-021-00184-1 |
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