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Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer
The aim of this study is to investigate the prognostic immune-related factors in breast cancer (BC) metastasis. The gene expression chip GSE159956 was downloaded from the gene expression omnibus database. Differentially expressed genes (DEGs) were selected using GEO2R online tools based on lymph nod...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238809/ https://www.ncbi.nlm.nih.gov/pubmed/37273920 http://dx.doi.org/10.1515/med-2023-0732 |
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author | Chen, Gang Zhang, Kun Liang, Zhi Zhang, Song Dai, Yuanping Cong, Yizi Qiao, Guangdong |
author_facet | Chen, Gang Zhang, Kun Liang, Zhi Zhang, Song Dai, Yuanping Cong, Yizi Qiao, Guangdong |
author_sort | Chen, Gang |
collection | PubMed |
description | The aim of this study is to investigate the prognostic immune-related factors in breast cancer (BC) metastasis. The gene expression chip GSE159956 was downloaded from the gene expression omnibus database. Differentially expressed genes (DEGs) were selected using GEO2R online tools based on lymph node and metastasis status. The intersected survival-associated DEGs were screened from the Kaplan–Meier curve. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) annotation analyses were performed to determine the survival-associated DEGs. Immune-related prognostic factors were screened based on immune infiltration. The screened prognostic factors were verified by the Cancer Genome Atlas (TCGA) database and single-sample gene set enrichment analysis (ssGSEA). As a result, twenty-eight upregulated and three downregulated genes were generated by the survival analysis. The enriched GO and KEGG pathways were mostly correlated with “regulation of cellular amino acid metabolic process,” “proteasome complex,” “endopeptidase activity,” and “proteasome.” Six of 19 (17 upregulated and 2 downregulated) immune-related prognostic factors were verified by the TCGA database. Four immune-related factors were obtained after ssGSEA, and three significant immune-related factors were selected after univariate and multivariate analyses. Based on the risk score receiver operating characteristic, the three immune-related prognosis factors could be potential biomarkers of BC metastasis. In conclusion, APPL1, RPS6KB2, and GALK1 may play a pivotal role as potential biomarkers for prediction of BC metastasis. |
format | Online Article Text |
id | pubmed-10238809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-102388092023-06-04 Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer Chen, Gang Zhang, Kun Liang, Zhi Zhang, Song Dai, Yuanping Cong, Yizi Qiao, Guangdong Open Med (Wars) Research Article The aim of this study is to investigate the prognostic immune-related factors in breast cancer (BC) metastasis. The gene expression chip GSE159956 was downloaded from the gene expression omnibus database. Differentially expressed genes (DEGs) were selected using GEO2R online tools based on lymph node and metastasis status. The intersected survival-associated DEGs were screened from the Kaplan–Meier curve. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) annotation analyses were performed to determine the survival-associated DEGs. Immune-related prognostic factors were screened based on immune infiltration. The screened prognostic factors were verified by the Cancer Genome Atlas (TCGA) database and single-sample gene set enrichment analysis (ssGSEA). As a result, twenty-eight upregulated and three downregulated genes were generated by the survival analysis. The enriched GO and KEGG pathways were mostly correlated with “regulation of cellular amino acid metabolic process,” “proteasome complex,” “endopeptidase activity,” and “proteasome.” Six of 19 (17 upregulated and 2 downregulated) immune-related prognostic factors were verified by the TCGA database. Four immune-related factors were obtained after ssGSEA, and three significant immune-related factors were selected after univariate and multivariate analyses. Based on the risk score receiver operating characteristic, the three immune-related prognosis factors could be potential biomarkers of BC metastasis. In conclusion, APPL1, RPS6KB2, and GALK1 may play a pivotal role as potential biomarkers for prediction of BC metastasis. De Gruyter 2023-06-01 /pmc/articles/PMC10238809/ /pubmed/37273920 http://dx.doi.org/10.1515/med-2023-0732 Text en © 2023 the author(s), published by De Gruyter https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License. |
spellingShingle | Research Article Chen, Gang Zhang, Kun Liang, Zhi Zhang, Song Dai, Yuanping Cong, Yizi Qiao, Guangdong Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer |
title | Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer |
title_full | Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer |
title_fullStr | Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer |
title_full_unstemmed | Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer |
title_short | Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer |
title_sort | integrated transcriptome analysis identifies appl1/rps6kb2/galk1 as immune-related metastasis factors in breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238809/ https://www.ncbi.nlm.nih.gov/pubmed/37273920 http://dx.doi.org/10.1515/med-2023-0732 |
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