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Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types

BACKGROUND: The human proteasome gene family (PSM) consists of 49 genes that play a crucial role in cancer proteostasis. However, little is known about the effect of PSM gene expression and genetic alterations on clinical outcome in different cancer forms. METHODS: Here, we performed a comprehensive...

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Autores principales: Larsson, Peter, Pettersson, Daniella, Engqvist, Hanna, Werner Rönnerman, Elisabeth, Forssell-Aronsson, Eva, Kovács, Anikó, Karlsson, Per, Helou, Khalil, Parris, Toshima Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484138/
https://www.ncbi.nlm.nih.gov/pubmed/36123629
http://dx.doi.org/10.1186/s12885-022-10079-4
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author Larsson, Peter
Pettersson, Daniella
Engqvist, Hanna
Werner Rönnerman, Elisabeth
Forssell-Aronsson, Eva
Kovács, Anikó
Karlsson, Per
Helou, Khalil
Parris, Toshima Z.
author_facet Larsson, Peter
Pettersson, Daniella
Engqvist, Hanna
Werner Rönnerman, Elisabeth
Forssell-Aronsson, Eva
Kovács, Anikó
Karlsson, Per
Helou, Khalil
Parris, Toshima Z.
author_sort Larsson, Peter
collection PubMed
description BACKGROUND: The human proteasome gene family (PSM) consists of 49 genes that play a crucial role in cancer proteostasis. However, little is known about the effect of PSM gene expression and genetic alterations on clinical outcome in different cancer forms. METHODS: Here, we performed a comprehensive pan-cancer analysis of genetic alterations in PSM genes and the subsequent prognostic value of PSM expression using data from The Cancer Genome Atlas (TCGA) containing over 10,000 samples representing up to 33 different cancer types. External validation was performed using a breast cancer cohort and KM plotter with four cancer types. RESULTS: The PSM genetic alteration frequency was high in certain cancer types (e.g. 67%; esophageal adenocarcinoma), with DNA amplification being most common. Compared with normal tissue, most PSM genes were predominantly overexpressed in cancer. Survival analysis also established a relationship with PSM gene expression and adverse clinical outcome, where PSMA1 and PSMD11 expression were linked to more unfavorable prognosis in ≥ 30% of cancer types for both overall survival (OS) and relapse-free interval (PFI). Interestingly, PSMB5 gene expression was associated with OS (36%) and PFI (27%), and OS for PSMD2 (42%), especially when overexpressed. CONCLUSION: These findings indicate that several PSM genes may potentially be prognostic biomarkers and novel therapeutic targets for different cancer forms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10079-4.
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spelling pubmed-94841382022-09-20 Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types Larsson, Peter Pettersson, Daniella Engqvist, Hanna Werner Rönnerman, Elisabeth Forssell-Aronsson, Eva Kovács, Anikó Karlsson, Per Helou, Khalil Parris, Toshima Z. BMC Cancer Research BACKGROUND: The human proteasome gene family (PSM) consists of 49 genes that play a crucial role in cancer proteostasis. However, little is known about the effect of PSM gene expression and genetic alterations on clinical outcome in different cancer forms. METHODS: Here, we performed a comprehensive pan-cancer analysis of genetic alterations in PSM genes and the subsequent prognostic value of PSM expression using data from The Cancer Genome Atlas (TCGA) containing over 10,000 samples representing up to 33 different cancer types. External validation was performed using a breast cancer cohort and KM plotter with four cancer types. RESULTS: The PSM genetic alteration frequency was high in certain cancer types (e.g. 67%; esophageal adenocarcinoma), with DNA amplification being most common. Compared with normal tissue, most PSM genes were predominantly overexpressed in cancer. Survival analysis also established a relationship with PSM gene expression and adverse clinical outcome, where PSMA1 and PSMD11 expression were linked to more unfavorable prognosis in ≥ 30% of cancer types for both overall survival (OS) and relapse-free interval (PFI). Interestingly, PSMB5 gene expression was associated with OS (36%) and PFI (27%), and OS for PSMD2 (42%), especially when overexpressed. CONCLUSION: These findings indicate that several PSM genes may potentially be prognostic biomarkers and novel therapeutic targets for different cancer forms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10079-4. BioMed Central 2022-09-19 /pmc/articles/PMC9484138/ /pubmed/36123629 http://dx.doi.org/10.1186/s12885-022-10079-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Larsson, Peter
Pettersson, Daniella
Engqvist, Hanna
Werner Rönnerman, Elisabeth
Forssell-Aronsson, Eva
Kovács, Anikó
Karlsson, Per
Helou, Khalil
Parris, Toshima Z.
Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
title Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
title_full Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
title_fullStr Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
title_full_unstemmed Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
title_short Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
title_sort pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484138/
https://www.ncbi.nlm.nih.gov/pubmed/36123629
http://dx.doi.org/10.1186/s12885-022-10079-4
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