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Next-Generation Digital Histopathology of the Tumor Microenvironment
Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068063/ https://www.ncbi.nlm.nih.gov/pubmed/33917241 http://dx.doi.org/10.3390/genes12040538 |
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author | Mungenast, Felicitas Fernando, Achala Nica, Robert Boghiu, Bogdan Lungu, Bianca Batra, Jyotsna Ecker, Rupert C. |
author_facet | Mungenast, Felicitas Fernando, Achala Nica, Robert Boghiu, Bogdan Lungu, Bianca Batra, Jyotsna Ecker, Rupert C. |
author_sort | Mungenast, Felicitas |
collection | PubMed |
description | Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology—which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning. |
format | Online Article Text |
id | pubmed-8068063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80680632021-04-25 Next-Generation Digital Histopathology of the Tumor Microenvironment Mungenast, Felicitas Fernando, Achala Nica, Robert Boghiu, Bogdan Lungu, Bianca Batra, Jyotsna Ecker, Rupert C. Genes (Basel) Review Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology—which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning. MDPI 2021-04-07 /pmc/articles/PMC8068063/ /pubmed/33917241 http://dx.doi.org/10.3390/genes12040538 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Mungenast, Felicitas Fernando, Achala Nica, Robert Boghiu, Bogdan Lungu, Bianca Batra, Jyotsna Ecker, Rupert C. Next-Generation Digital Histopathology of the Tumor Microenvironment |
title | Next-Generation Digital Histopathology of the Tumor Microenvironment |
title_full | Next-Generation Digital Histopathology of the Tumor Microenvironment |
title_fullStr | Next-Generation Digital Histopathology of the Tumor Microenvironment |
title_full_unstemmed | Next-Generation Digital Histopathology of the Tumor Microenvironment |
title_short | Next-Generation Digital Histopathology of the Tumor Microenvironment |
title_sort | next-generation digital histopathology of the tumor microenvironment |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068063/ https://www.ncbi.nlm.nih.gov/pubmed/33917241 http://dx.doi.org/10.3390/genes12040538 |
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