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A comparative study of PCS and PAM50 prostate cancer classification schemes

BACKGROUND: Two prostate cancer (PC) classification methods based on transcriptome profiles, a de novo method referred to as the “Prostate Cancer Classification System” (PCS) and a variation of the established PAM50 breast cancer algorithm, were recently proposed. Both studies concluded that most hu...

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Autores principales: Yoon, Junhee, Kim, Minhyung, Posadas, Edwin M., Freedland, Stephen J., Liu, Yang, Davicioni, Elai, Den, Robert B., Trock, Bruce J., Karnes, R. Jeffrey, Klein, Eric A., Freeman, Michael R., You, Sungyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8326303/
https://www.ncbi.nlm.nih.gov/pubmed/33531653
http://dx.doi.org/10.1038/s41391-021-00325-4
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author Yoon, Junhee
Kim, Minhyung
Posadas, Edwin M.
Freedland, Stephen J.
Liu, Yang
Davicioni, Elai
Den, Robert B.
Trock, Bruce J.
Karnes, R. Jeffrey
Klein, Eric A.
Freeman, Michael R.
You, Sungyong
author_facet Yoon, Junhee
Kim, Minhyung
Posadas, Edwin M.
Freedland, Stephen J.
Liu, Yang
Davicioni, Elai
Den, Robert B.
Trock, Bruce J.
Karnes, R. Jeffrey
Klein, Eric A.
Freeman, Michael R.
You, Sungyong
author_sort Yoon, Junhee
collection PubMed
description BACKGROUND: Two prostate cancer (PC) classification methods based on transcriptome profiles, a de novo method referred to as the “Prostate Cancer Classification System” (PCS) and a variation of the established PAM50 breast cancer algorithm, were recently proposed. Both studies concluded that most human PC can be assigned to one of three tumor subtypes, two categorized as luminal and one as basal, suggesting the two methods reflect consistency in underlying biology. Despite the similarity, differences and commonalities between the two classification methods have not yet been reported. METHODS: Here, we describe a comparison of the PCS and PAM50 classification systems. PCS and PAM50 signatures consisting of 37 (PCS37) and 50 genes, respectively, were used to categorize 9,947 PC patients into PCS and PAM50 classes. Enrichment of hallmark gene sets and luminal and basal marker gene expression were assessed in the same datasets. Finally, survival analysis was performed to compare PCS and PAM50 subtypes in terms of clinical outcomes. RESULTS: PCS and PAM50 subtypes show clear differential expression of PCS37 and PAM50 genes. While only three genes are shared in common between the two systems, there is some consensus between three subtype pairs (PCS1 versus Luminal B, PCS2 versus Luminal A, and PCS3 versus Basal) with respect to gene expression, cellular processes, and clinical outcomes. PCS categories displayed better separation of cellular processes and luminal and basal marker gene expression compared to PAM50. Although both PCS1 and Luminal B tumors exhibited the worst clinical outcomes, outcomes between aggressive and less aggressive subtypes were better defined in the PCS system, based on larger hazard ratios observed. CONCLUSION: The PCS and PAM50 classification systems are similar in terms of molecular profiles and clinical outcomes. However, the PCS system exhibits greater separation in multiple clinical outcomes and provides better separation of prostate luminal and basal characteristics.
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spelling pubmed-83263032021-09-01 A comparative study of PCS and PAM50 prostate cancer classification schemes Yoon, Junhee Kim, Minhyung Posadas, Edwin M. Freedland, Stephen J. Liu, Yang Davicioni, Elai Den, Robert B. Trock, Bruce J. Karnes, R. Jeffrey Klein, Eric A. Freeman, Michael R. You, Sungyong Prostate Cancer Prostatic Dis Article BACKGROUND: Two prostate cancer (PC) classification methods based on transcriptome profiles, a de novo method referred to as the “Prostate Cancer Classification System” (PCS) and a variation of the established PAM50 breast cancer algorithm, were recently proposed. Both studies concluded that most human PC can be assigned to one of three tumor subtypes, two categorized as luminal and one as basal, suggesting the two methods reflect consistency in underlying biology. Despite the similarity, differences and commonalities between the two classification methods have not yet been reported. METHODS: Here, we describe a comparison of the PCS and PAM50 classification systems. PCS and PAM50 signatures consisting of 37 (PCS37) and 50 genes, respectively, were used to categorize 9,947 PC patients into PCS and PAM50 classes. Enrichment of hallmark gene sets and luminal and basal marker gene expression were assessed in the same datasets. Finally, survival analysis was performed to compare PCS and PAM50 subtypes in terms of clinical outcomes. RESULTS: PCS and PAM50 subtypes show clear differential expression of PCS37 and PAM50 genes. While only three genes are shared in common between the two systems, there is some consensus between three subtype pairs (PCS1 versus Luminal B, PCS2 versus Luminal A, and PCS3 versus Basal) with respect to gene expression, cellular processes, and clinical outcomes. PCS categories displayed better separation of cellular processes and luminal and basal marker gene expression compared to PAM50. Although both PCS1 and Luminal B tumors exhibited the worst clinical outcomes, outcomes between aggressive and less aggressive subtypes were better defined in the PCS system, based on larger hazard ratios observed. CONCLUSION: The PCS and PAM50 classification systems are similar in terms of molecular profiles and clinical outcomes. However, the PCS system exhibits greater separation in multiple clinical outcomes and provides better separation of prostate luminal and basal characteristics. Nature Publishing Group UK 2021-02-02 2021 /pmc/articles/PMC8326303/ /pubmed/33531653 http://dx.doi.org/10.1038/s41391-021-00325-4 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 Article
Yoon, Junhee
Kim, Minhyung
Posadas, Edwin M.
Freedland, Stephen J.
Liu, Yang
Davicioni, Elai
Den, Robert B.
Trock, Bruce J.
Karnes, R. Jeffrey
Klein, Eric A.
Freeman, Michael R.
You, Sungyong
A comparative study of PCS and PAM50 prostate cancer classification schemes
title A comparative study of PCS and PAM50 prostate cancer classification schemes
title_full A comparative study of PCS and PAM50 prostate cancer classification schemes
title_fullStr A comparative study of PCS and PAM50 prostate cancer classification schemes
title_full_unstemmed A comparative study of PCS and PAM50 prostate cancer classification schemes
title_short A comparative study of PCS and PAM50 prostate cancer classification schemes
title_sort comparative study of pcs and pam50 prostate cancer classification schemes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8326303/
https://www.ncbi.nlm.nih.gov/pubmed/33531653
http://dx.doi.org/10.1038/s41391-021-00325-4
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