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Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging

Challenging histopathological diagnostics in cancer include microsatellite instability-high (MSI-H) colorectal cancer (CRC), which occurs in 15% of early-stage CRC and is caused by a deficiency in the mismatch repair system. The diagnosis of MSI-H cannot be reliably achieved by visual inspection of...

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Autores principales: Kallenbach-Thieltges, Angela, Großerueschkamp, Frederik, Jütte, Hendrik, Kuepper, Claus, Reinacher-Schick, Anke, Tannapfel, Andrea, Gerwert, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311536/
https://www.ncbi.nlm.nih.gov/pubmed/32576892
http://dx.doi.org/10.1038/s41598-020-67052-z
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author Kallenbach-Thieltges, Angela
Großerueschkamp, Frederik
Jütte, Hendrik
Kuepper, Claus
Reinacher-Schick, Anke
Tannapfel, Andrea
Gerwert, Klaus
author_facet Kallenbach-Thieltges, Angela
Großerueschkamp, Frederik
Jütte, Hendrik
Kuepper, Claus
Reinacher-Schick, Anke
Tannapfel, Andrea
Gerwert, Klaus
author_sort Kallenbach-Thieltges, Angela
collection PubMed
description Challenging histopathological diagnostics in cancer include microsatellite instability-high (MSI-H) colorectal cancer (CRC), which occurs in 15% of early-stage CRC and is caused by a deficiency in the mismatch repair system. The diagnosis of MSI-H cannot be reliably achieved by visual inspection of a hematoxylin and eosin stained thin section alone, but additionally requires subsequent molecular analysis. Time- and sample-intensive immunohistochemistry with subsequent fragment length analysis is used. The aim of the presented feasibility study is to test the ability of quantum cascade laser (QCL)-based infrared (IR) imaging as an alternative diagnostic tool for MSI-H in CRC. We analyzed samples from 100 patients with sporadic CRC UICC stage II and III. Forty samples were used to develop the random forest classifier and 60 samples to verify the results on an independent blinded dataset. Specifically, 100% sensitivity and 93% specificity were achieved based on the independent 30 MSI-H- and 30 microsatellite stable (MSS)-patient validation cohort. This showed that QCL-based IR imaging is able to distinguish between MSI-H and MSS for sporadic CRC - a question that goes beyond morphological features - based on the use of spatially resolved infrared spectra used as biomolecular fingerprints.
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spelling pubmed-73115362020-06-25 Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging Kallenbach-Thieltges, Angela Großerueschkamp, Frederik Jütte, Hendrik Kuepper, Claus Reinacher-Schick, Anke Tannapfel, Andrea Gerwert, Klaus Sci Rep Article Challenging histopathological diagnostics in cancer include microsatellite instability-high (MSI-H) colorectal cancer (CRC), which occurs in 15% of early-stage CRC and is caused by a deficiency in the mismatch repair system. The diagnosis of MSI-H cannot be reliably achieved by visual inspection of a hematoxylin and eosin stained thin section alone, but additionally requires subsequent molecular analysis. Time- and sample-intensive immunohistochemistry with subsequent fragment length analysis is used. The aim of the presented feasibility study is to test the ability of quantum cascade laser (QCL)-based infrared (IR) imaging as an alternative diagnostic tool for MSI-H in CRC. We analyzed samples from 100 patients with sporadic CRC UICC stage II and III. Forty samples were used to develop the random forest classifier and 60 samples to verify the results on an independent blinded dataset. Specifically, 100% sensitivity and 93% specificity were achieved based on the independent 30 MSI-H- and 30 microsatellite stable (MSS)-patient validation cohort. This showed that QCL-based IR imaging is able to distinguish between MSI-H and MSS for sporadic CRC - a question that goes beyond morphological features - based on the use of spatially resolved infrared spectra used as biomolecular fingerprints. Nature Publishing Group UK 2020-06-23 /pmc/articles/PMC7311536/ /pubmed/32576892 http://dx.doi.org/10.1038/s41598-020-67052-z 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
Kallenbach-Thieltges, Angela
Großerueschkamp, Frederik
Jütte, Hendrik
Kuepper, Claus
Reinacher-Schick, Anke
Tannapfel, Andrea
Gerwert, Klaus
Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
title Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
title_full Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
title_fullStr Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
title_full_unstemmed Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
title_short Label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
title_sort label-free, automated classification of microsatellite status in colorectal cancer by infrared imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311536/
https://www.ncbi.nlm.nih.gov/pubmed/32576892
http://dx.doi.org/10.1038/s41598-020-67052-z
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