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A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer

A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performe...

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Autores principales: Iwata, Teppei, Sedukhina, Anna S., Kubota, Manabu, Oonuma, Shigeko, Maeda, Ichiro, Yoshiike, Miki, Usuba, Wataru, Minagawa, Kimino, Hames, Eleina, Meguro, Rei, Cho, Sunny, Chien, Stephen H. H., Urabe, Shiro, Pae, Sookhee, Palanisamy, Kishore, Kumai, Toshio, Yudo, Kazuo, Kikuchi, Eiji, Sato, Ko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952695/
https://www.ncbi.nlm.nih.gov/pubmed/33707553
http://dx.doi.org/10.1038/s41598-021-85086-9
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author Iwata, Teppei
Sedukhina, Anna S.
Kubota, Manabu
Oonuma, Shigeko
Maeda, Ichiro
Yoshiike, Miki
Usuba, Wataru
Minagawa, Kimino
Hames, Eleina
Meguro, Rei
Cho, Sunny
Chien, Stephen H. H.
Urabe, Shiro
Pae, Sookhee
Palanisamy, Kishore
Kumai, Toshio
Yudo, Kazuo
Kikuchi, Eiji
Sato, Ko
author_facet Iwata, Teppei
Sedukhina, Anna S.
Kubota, Manabu
Oonuma, Shigeko
Maeda, Ichiro
Yoshiike, Miki
Usuba, Wataru
Minagawa, Kimino
Hames, Eleina
Meguro, Rei
Cho, Sunny
Chien, Stephen H. H.
Urabe, Shiro
Pae, Sookhee
Palanisamy, Kishore
Kumai, Toshio
Yudo, Kazuo
Kikuchi, Eiji
Sato, Ko
author_sort Iwata, Teppei
collection PubMed
description A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ≧8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of factors such as “overexpression” and “shorter survival” is vital, as poor definition may lead to mis-estimations. To eliminate this possibility, we defined an expression cutoff value using an algorithm calculated by a Cox regression model, and the hazard ratio for each gene was set so as to identify genes whose expression levels were associated with shorter survival. Next, genes associated with shorter survival were entered into pathway analysis to identify pathways that were altered in a shorter survival cohort. We identified pathways involving upregulation of GRB2. Overexpression of GRB2 was linked to shorter survival in the TCGA dataset, a finding validated by histological examination of biopsy samples taken from the patients for diagnostic purposes. Thus, GRB2 is a novel biomarker that predicts shorter survival of patients with aggressive prostate cancer (GS ≧8).
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spelling pubmed-79526952021-03-15 A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer Iwata, Teppei Sedukhina, Anna S. Kubota, Manabu Oonuma, Shigeko Maeda, Ichiro Yoshiike, Miki Usuba, Wataru Minagawa, Kimino Hames, Eleina Meguro, Rei Cho, Sunny Chien, Stephen H. H. Urabe, Shiro Pae, Sookhee Palanisamy, Kishore Kumai, Toshio Yudo, Kazuo Kikuchi, Eiji Sato, Ko Sci Rep Article A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ≧8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of factors such as “overexpression” and “shorter survival” is vital, as poor definition may lead to mis-estimations. To eliminate this possibility, we defined an expression cutoff value using an algorithm calculated by a Cox regression model, and the hazard ratio for each gene was set so as to identify genes whose expression levels were associated with shorter survival. Next, genes associated with shorter survival were entered into pathway analysis to identify pathways that were altered in a shorter survival cohort. We identified pathways involving upregulation of GRB2. Overexpression of GRB2 was linked to shorter survival in the TCGA dataset, a finding validated by histological examination of biopsy samples taken from the patients for diagnostic purposes. Thus, GRB2 is a novel biomarker that predicts shorter survival of patients with aggressive prostate cancer (GS ≧8). Nature Publishing Group UK 2021-03-11 /pmc/articles/PMC7952695/ /pubmed/33707553 http://dx.doi.org/10.1038/s41598-021-85086-9 Text en © The Author(s) 2021 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 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/.
spellingShingle Article
Iwata, Teppei
Sedukhina, Anna S.
Kubota, Manabu
Oonuma, Shigeko
Maeda, Ichiro
Yoshiike, Miki
Usuba, Wataru
Minagawa, Kimino
Hames, Eleina
Meguro, Rei
Cho, Sunny
Chien, Stephen H. H.
Urabe, Shiro
Pae, Sookhee
Palanisamy, Kishore
Kumai, Toshio
Yudo, Kazuo
Kikuchi, Eiji
Sato, Ko
A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer
title A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer
title_full A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer
title_fullStr A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer
title_full_unstemmed A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer
title_short A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer
title_sort new bioinformatics approach identifies overexpression of grb2 as a poor prognostic biomarker for prostate cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952695/
https://www.ncbi.nlm.nih.gov/pubmed/33707553
http://dx.doi.org/10.1038/s41598-021-85086-9
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