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Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype

BACKGROUND AND OBJECTIVES: Transcriptomic landscape of prostate cancer (PCa) shows multidimensional variability, potentially arising from the cell-of-origin, reflected in serum markers, and most importantly related to drug sensitivities. For example, Aggressive Variant Prostate Cancer (AVPC) present...

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Autores principales: Han, Hyunho, Lee, Hyung Ho, Choi, Kwibok, Moon, Young Jun, Heo, Ji Eun, Ham, Won Sik, Jang, Won Sik, Rha, Koon Ho, Cho, Nam Hoon, Giancotti, Filippo G., Choi, Young-Deuk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8616761/
https://www.ncbi.nlm.nih.gov/pubmed/33903734
http://dx.doi.org/10.1038/s41391-021-00364-x
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author Han, Hyunho
Lee, Hyung Ho
Choi, Kwibok
Moon, Young Jun
Heo, Ji Eun
Ham, Won Sik
Jang, Won Sik
Rha, Koon Ho
Cho, Nam Hoon
Giancotti, Filippo G.
Choi, Young-Deuk
author_facet Han, Hyunho
Lee, Hyung Ho
Choi, Kwibok
Moon, Young Jun
Heo, Ji Eun
Ham, Won Sik
Jang, Won Sik
Rha, Koon Ho
Cho, Nam Hoon
Giancotti, Filippo G.
Choi, Young-Deuk
author_sort Han, Hyunho
collection PubMed
description BACKGROUND AND OBJECTIVES: Transcriptomic landscape of prostate cancer (PCa) shows multidimensional variability, potentially arising from the cell-of-origin, reflected in serum markers, and most importantly related to drug sensitivities. For example, Aggressive Variant Prostate Cancer (AVPC) presents low PSA per tumor burden, and characterized by de novo resistance to androgen receptor signaling inhibitors (ARIs). Understanding PCa transcriptomic complexity can provide biological insight and therapeutic guidance. However, unsupervised clustering analysis is hindered by potential confounding factors such as stromal contamination and stress-related material degradation. MATERIALS AND METHODS: To focus on prostate epithelial cell-relevant heterogeneity, we defined 1,629 genes expressed by prostate epithelial cells by analyzing publicly available bulk and single- cell RNA sequencing data. Consensus clustering and CIBERSORT deconvolution were used for class discovery and proportion estimate analysis. The Cancer Genome Atlas Prostate Adenocarcinoma dataset served as a training set. The resulting clusters were analyzed in association with clinical, pathologic, and genomic characteristics and impact on survival. Serum markers PSA and PAP was analyzed to predict response to docetaxel chemotherapy in metastatic setting. RESULTS: We identified two luminal subtypes and two aggressive variant subtypes of PCa: luminal A (Adipogenic/AR-active/PSA-high) (30.0%); luminal S (Secretory/PAP-high) (26.0%); AVPC-I (Immune-infiltrative) (14.7%), AVPC-M (Myc-active) (4.2%), and mixed (25.0%). AVPC-I and AVPC-M subtypes predicted to be resistant to ARI and have low PSA per tumor burden. Luminal A and AVPC-M predicted to be resistant to docetaxel and have high PSA/PAP Ratio. Metastatic PCa patients with high PSA/PAP ratio (>20) had significantly shorter progression-free survival than those with low ratio (≤20) following docetaxel chemotherapy. CONCLUSION: We propose four prostate adenocarcinoma subtypes with distinct transcriptomic, genomic, and pathologic characteristics. PSA/PAP ratio in advanced cancer may aid in determining which patients would benefit from maximized androgen receptor inhibition or early use of antimicrotubule agents.
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spelling pubmed-86167612021-12-10 Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype Han, Hyunho Lee, Hyung Ho Choi, Kwibok Moon, Young Jun Heo, Ji Eun Ham, Won Sik Jang, Won Sik Rha, Koon Ho Cho, Nam Hoon Giancotti, Filippo G. Choi, Young-Deuk Prostate Cancer Prostatic Dis Article BACKGROUND AND OBJECTIVES: Transcriptomic landscape of prostate cancer (PCa) shows multidimensional variability, potentially arising from the cell-of-origin, reflected in serum markers, and most importantly related to drug sensitivities. For example, Aggressive Variant Prostate Cancer (AVPC) presents low PSA per tumor burden, and characterized by de novo resistance to androgen receptor signaling inhibitors (ARIs). Understanding PCa transcriptomic complexity can provide biological insight and therapeutic guidance. However, unsupervised clustering analysis is hindered by potential confounding factors such as stromal contamination and stress-related material degradation. MATERIALS AND METHODS: To focus on prostate epithelial cell-relevant heterogeneity, we defined 1,629 genes expressed by prostate epithelial cells by analyzing publicly available bulk and single- cell RNA sequencing data. Consensus clustering and CIBERSORT deconvolution were used for class discovery and proportion estimate analysis. The Cancer Genome Atlas Prostate Adenocarcinoma dataset served as a training set. The resulting clusters were analyzed in association with clinical, pathologic, and genomic characteristics and impact on survival. Serum markers PSA and PAP was analyzed to predict response to docetaxel chemotherapy in metastatic setting. RESULTS: We identified two luminal subtypes and two aggressive variant subtypes of PCa: luminal A (Adipogenic/AR-active/PSA-high) (30.0%); luminal S (Secretory/PAP-high) (26.0%); AVPC-I (Immune-infiltrative) (14.7%), AVPC-M (Myc-active) (4.2%), and mixed (25.0%). AVPC-I and AVPC-M subtypes predicted to be resistant to ARI and have low PSA per tumor burden. Luminal A and AVPC-M predicted to be resistant to docetaxel and have high PSA/PAP Ratio. Metastatic PCa patients with high PSA/PAP ratio (>20) had significantly shorter progression-free survival than those with low ratio (≤20) following docetaxel chemotherapy. CONCLUSION: We propose four prostate adenocarcinoma subtypes with distinct transcriptomic, genomic, and pathologic characteristics. PSA/PAP ratio in advanced cancer may aid in determining which patients would benefit from maximized androgen receptor inhibition or early use of antimicrotubule agents. Nature Publishing Group UK 2021-04-26 2021 /pmc/articles/PMC8616761/ /pubmed/33903734 http://dx.doi.org/10.1038/s41391-021-00364-x 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
Han, Hyunho
Lee, Hyung Ho
Choi, Kwibok
Moon, Young Jun
Heo, Ji Eun
Ham, Won Sik
Jang, Won Sik
Rha, Koon Ho
Cho, Nam Hoon
Giancotti, Filippo G.
Choi, Young-Deuk
Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
title Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
title_full Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
title_fullStr Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
title_full_unstemmed Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
title_short Prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
title_sort prostate epithelial genes define therapy-relevant prostate cancer molecular subtype
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8616761/
https://www.ncbi.nlm.nih.gov/pubmed/33903734
http://dx.doi.org/10.1038/s41391-021-00364-x
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