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Artificial intelligence, molecular subtyping, biomarkers, and precision oncology
A targeted cancer therapy is only useful if there is a way to accurately identify the tumors that are susceptible to that therapy. Thus rapid expansion in the number of available targeted cancer treatments has been accompanied by a robust effort to subdivide the traditional histological and anatomic...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8786277/ https://www.ncbi.nlm.nih.gov/pubmed/34881776 http://dx.doi.org/10.1042/ETLS20210212 |
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author | Shen, John Paul |
author_facet | Shen, John Paul |
author_sort | Shen, John Paul |
collection | PubMed |
description | A targeted cancer therapy is only useful if there is a way to accurately identify the tumors that are susceptible to that therapy. Thus rapid expansion in the number of available targeted cancer treatments has been accompanied by a robust effort to subdivide the traditional histological and anatomical tumor classifications into molecularly defined subtypes. This review highlights the history of the paired evolution of targeted therapies and biomarkers, reviews currently used methods for subtype identification, and discusses challenges to the implementation of precision oncology as well as possible solutions. |
format | Online Article Text |
id | pubmed-8786277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87862772022-02-01 Artificial intelligence, molecular subtyping, biomarkers, and precision oncology Shen, John Paul Emerg Top Life Sci Review Articles A targeted cancer therapy is only useful if there is a way to accurately identify the tumors that are susceptible to that therapy. Thus rapid expansion in the number of available targeted cancer treatments has been accompanied by a robust effort to subdivide the traditional histological and anatomical tumor classifications into molecularly defined subtypes. This review highlights the history of the paired evolution of targeted therapies and biomarkers, reviews currently used methods for subtype identification, and discusses challenges to the implementation of precision oncology as well as possible solutions. Portland Press Ltd. 2021-12-21 2021-12-09 /pmc/articles/PMC8786277/ /pubmed/34881776 http://dx.doi.org/10.1042/ETLS20210212 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and the Royal Society of Biology and distributed under the Creative Commons Attribution License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Review Articles Shen, John Paul Artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
title | Artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
title_full | Artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
title_fullStr | Artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
title_full_unstemmed | Artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
title_short | Artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
title_sort | artificial intelligence, molecular subtyping, biomarkers, and precision oncology |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8786277/ https://www.ncbi.nlm.nih.gov/pubmed/34881776 http://dx.doi.org/10.1042/ETLS20210212 |
work_keys_str_mv | AT shenjohnpaul artificialintelligencemolecularsubtypingbiomarkersandprecisiononcology |