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A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity

Background and Objectives. The prognostic role of adjacent nontumor tissue in patients with breast cancer (BC) is still unclear. The activity changes in immunologic and hallmark gene sets in normal tissues adjacent to BC may play a crucial role in predicting the prognosis of BC patients. The aim of...

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Autores principales: Luan, Tiankuo, Song, Daqiang, Liu, Jiazhou, Wei, Yuxian, Feng, Rui, Wang, Xiaoyu, Gan, Lin, Wan, Jingyuan, Fang, Huiying, Li, Hongzhong, Gong, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10051894/
https://www.ncbi.nlm.nih.gov/pubmed/36984424
http://dx.doi.org/10.3390/medicina59030424
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author Luan, Tiankuo
Song, Daqiang
Liu, Jiazhou
Wei, Yuxian
Feng, Rui
Wang, Xiaoyu
Gan, Lin
Wan, Jingyuan
Fang, Huiying
Li, Hongzhong
Gong, Xia
author_facet Luan, Tiankuo
Song, Daqiang
Liu, Jiazhou
Wei, Yuxian
Feng, Rui
Wang, Xiaoyu
Gan, Lin
Wan, Jingyuan
Fang, Huiying
Li, Hongzhong
Gong, Xia
author_sort Luan, Tiankuo
collection PubMed
description Background and Objectives. The prognostic role of adjacent nontumor tissue in patients with breast cancer (BC) is still unclear. The activity changes in immunologic and hallmark gene sets in normal tissues adjacent to BC may play a crucial role in predicting the prognosis of BC patients. The aim of this study was to identify BC subtypes and ribosome-associated prognostic genes based on activity changes of immunologic and hallmark gene sets in tumor and adjacent nontumor tissues to improve patient prognosis. Materials and Methods. Gene set variation analysis (GSVA) was applied to assess immunoreactivity changes in the overall sample and three immune-related BC subtypes were identified by non-negative matrix factorization (NMF). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses were after determining the prognostic gene set using the least absolute shrinkage and selection operator (LASSO) method. Ribosome-related genes were identified by PPI (protein-protein interaction) analysis, and finally a prognostic risk model was constructed based on the expression of five ribosomal genes (RPS18, RPL11, PRLP1, RPL27A, and RPL38). Results. A comprehensive analysis of immune and marker genomic activity changes in normal breast tissue and BC tissue identified three immune-related BC subtypes. BC subtype 1 has the best prognosis, and subtype 3 has the worst overall survival rate. We identified a prognostic gene set in nontumor tissue by the least absolute shrinkage and selection operator (LASSO) method. We found that the results of both KEGG and GO analyses were indistinguishable from those of ribosome-associated genes. Finally, we determined that genes associated with ribosomes exhibit potential as a reliable predictor of overall survival in breast cancer patients. Conclusions. Our research provides an important guidance for the treatment of BC. After a mastectomy, the changes in gene set activity of both BC tissues and the nontumor tissues adjacent to it should be thoroughly evaluated, with special attention to changes in ribosome-related genes in the nontumor tissues.
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spelling pubmed-100518942023-03-30 A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity Luan, Tiankuo Song, Daqiang Liu, Jiazhou Wei, Yuxian Feng, Rui Wang, Xiaoyu Gan, Lin Wan, Jingyuan Fang, Huiying Li, Hongzhong Gong, Xia Medicina (Kaunas) Article Background and Objectives. The prognostic role of adjacent nontumor tissue in patients with breast cancer (BC) is still unclear. The activity changes in immunologic and hallmark gene sets in normal tissues adjacent to BC may play a crucial role in predicting the prognosis of BC patients. The aim of this study was to identify BC subtypes and ribosome-associated prognostic genes based on activity changes of immunologic and hallmark gene sets in tumor and adjacent nontumor tissues to improve patient prognosis. Materials and Methods. Gene set variation analysis (GSVA) was applied to assess immunoreactivity changes in the overall sample and three immune-related BC subtypes were identified by non-negative matrix factorization (NMF). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses were after determining the prognostic gene set using the least absolute shrinkage and selection operator (LASSO) method. Ribosome-related genes were identified by PPI (protein-protein interaction) analysis, and finally a prognostic risk model was constructed based on the expression of five ribosomal genes (RPS18, RPL11, PRLP1, RPL27A, and RPL38). Results. A comprehensive analysis of immune and marker genomic activity changes in normal breast tissue and BC tissue identified three immune-related BC subtypes. BC subtype 1 has the best prognosis, and subtype 3 has the worst overall survival rate. We identified a prognostic gene set in nontumor tissue by the least absolute shrinkage and selection operator (LASSO) method. We found that the results of both KEGG and GO analyses were indistinguishable from those of ribosome-associated genes. Finally, we determined that genes associated with ribosomes exhibit potential as a reliable predictor of overall survival in breast cancer patients. Conclusions. Our research provides an important guidance for the treatment of BC. After a mastectomy, the changes in gene set activity of both BC tissues and the nontumor tissues adjacent to it should be thoroughly evaluated, with special attention to changes in ribosome-related genes in the nontumor tissues. MDPI 2023-02-21 /pmc/articles/PMC10051894/ /pubmed/36984424 http://dx.doi.org/10.3390/medicina59030424 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Luan, Tiankuo
Song, Daqiang
Liu, Jiazhou
Wei, Yuxian
Feng, Rui
Wang, Xiaoyu
Gan, Lin
Wan, Jingyuan
Fang, Huiying
Li, Hongzhong
Gong, Xia
A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity
title A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity
title_full A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity
title_fullStr A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity
title_full_unstemmed A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity
title_short A Ribosome-Related Prognostic Signature of Breast Cancer Subtypes Based on Changes in Breast Cancer Patients’ Immunological Activity
title_sort ribosome-related prognostic signature of breast cancer subtypes based on changes in breast cancer patients’ immunological activity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10051894/
https://www.ncbi.nlm.nih.gov/pubmed/36984424
http://dx.doi.org/10.3390/medicina59030424
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