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An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles

Intratumor heterogeneity (ITH) is a biomarker of tumor progression, metastasis, and immune evasion. Previous studies evaluated ITH mostly based on DNA alterations. Here, we developed a new algorithm (DEPTH) for quantifying ITH based on mRNA alterations in the tumor. DEPTH scores displayed significan...

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Autores principales: Li, Mengyuan, Zhang, Zhilan, Li, Lin, Wang, Xiaosheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486929/
https://www.ncbi.nlm.nih.gov/pubmed/32917965
http://dx.doi.org/10.1038/s42003-020-01230-7
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author Li, Mengyuan
Zhang, Zhilan
Li, Lin
Wang, Xiaosheng
author_facet Li, Mengyuan
Zhang, Zhilan
Li, Lin
Wang, Xiaosheng
author_sort Li, Mengyuan
collection PubMed
description Intratumor heterogeneity (ITH) is a biomarker of tumor progression, metastasis, and immune evasion. Previous studies evaluated ITH mostly based on DNA alterations. Here, we developed a new algorithm (DEPTH) for quantifying ITH based on mRNA alterations in the tumor. DEPTH scores displayed significant correlations with ITH-associated features (genomic instability, tumor advancement, unfavorable prognosis, immunosuppression, and drug response). Compared to DNA-based ITH scores (EXPANDS, PhyloWGS, MATH, and ABSOLUTE), DEPTH scores had stronger correlations with antitumor immune signatures, cell proliferation, stemness, tumor advancement, survival prognosis, and drug response. Compared to two other mRNA-based ITH scores (tITH and sITH), DEPTH scores showed stronger and more consistent associations with genomic instability, unfavorable tumor phenotypes and clinical features, and drug response. We further validated the reliability and robustness of DEPTH in 50 other datasets. In conclusion, DEPTH may provide new insights into tumor biology and potential clinical implications for cancer prognosis and treatment.
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spelling pubmed-74869292020-09-24 An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles Li, Mengyuan Zhang, Zhilan Li, Lin Wang, Xiaosheng Commun Biol Article Intratumor heterogeneity (ITH) is a biomarker of tumor progression, metastasis, and immune evasion. Previous studies evaluated ITH mostly based on DNA alterations. Here, we developed a new algorithm (DEPTH) for quantifying ITH based on mRNA alterations in the tumor. DEPTH scores displayed significant correlations with ITH-associated features (genomic instability, tumor advancement, unfavorable prognosis, immunosuppression, and drug response). Compared to DNA-based ITH scores (EXPANDS, PhyloWGS, MATH, and ABSOLUTE), DEPTH scores had stronger correlations with antitumor immune signatures, cell proliferation, stemness, tumor advancement, survival prognosis, and drug response. Compared to two other mRNA-based ITH scores (tITH and sITH), DEPTH scores showed stronger and more consistent associations with genomic instability, unfavorable tumor phenotypes and clinical features, and drug response. We further validated the reliability and robustness of DEPTH in 50 other datasets. In conclusion, DEPTH may provide new insights into tumor biology and potential clinical implications for cancer prognosis and treatment. Nature Publishing Group UK 2020-09-11 /pmc/articles/PMC7486929/ /pubmed/32917965 http://dx.doi.org/10.1038/s42003-020-01230-7 Text en © The Author(s) 2020, corrected publication 2022 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 Article
Li, Mengyuan
Zhang, Zhilan
Li, Lin
Wang, Xiaosheng
An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
title An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
title_full An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
title_fullStr An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
title_full_unstemmed An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
title_short An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
title_sort algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486929/
https://www.ncbi.nlm.nih.gov/pubmed/32917965
http://dx.doi.org/10.1038/s42003-020-01230-7
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