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Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer

BACKGROUND: Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and...

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Autores principales: Zhai, Xiuming, Yang, Zhaowei, Liu, Xiji, Dong, Zihe, Zhou, Dandan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513746/
https://www.ncbi.nlm.nih.gov/pubmed/33005492
http://dx.doi.org/10.7717/peerj.9975
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author Zhai, Xiuming
Yang, Zhaowei
Liu, Xiji
Dong, Zihe
Zhou, Dandan
author_facet Zhai, Xiuming
Yang, Zhaowei
Liu, Xiji
Dong, Zihe
Zhou, Dandan
author_sort Zhai, Xiuming
collection PubMed
description BACKGROUND: Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and prognosis. MATERIAL/METHODS: Three independent data sets (GSE45827, GSE38959, GSE65194) were downloaded from the Gene Expression Omnibus (GEO). The R software packages were used to integrate the gene profiles and identify differentially expressed genes (DEGs). A variety of bioinformatics tools were used to explore the hub genes, including the DAVID database, STRING database and Cytoscape software. Reverse transcription quantitative PCR (RT-qPCR) was used to verify the hub genes in 14 pairs of TNBC paired tissues. RESULTS: In this study, we screened out 161 DEGs between 222 non-TNBC and 126 TNBC samples, of which 105 genes were up-regulated and 56 were down-regulated. These DEGs were enriched for 27 GO terms and two pathways. GO analysis enriched mainly in “cell division”, “chromosome, centromeric region” and “microtubule motor activity”. KEGG pathway analysis enriched mostly in “Cell cycle” and “Oocyte meiosis”. PPI network was constructed and then 10 top hub genes were screened. According to the analysis results of the Kaplan-Meier survival curve, the expression levels of only NUF2, FAM83D and CENPH were associated with the recurrence-free survival in TNBC samples (P < 0.05). RT-qPCR confirmed that the expression levels of NUF2 and FAM83D in TNBC tissues were indeed up-regulated significantly. CONCLUSIONS: The comprehensive analysis showed that NUF2 and FAM83D could be used as potential biomarkers for diagnosis and prognosis of TNBC.
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spelling pubmed-75137462020-09-30 Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer Zhai, Xiuming Yang, Zhaowei Liu, Xiji Dong, Zihe Zhou, Dandan PeerJ Bioinformatics BACKGROUND: Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and prognosis. MATERIAL/METHODS: Three independent data sets (GSE45827, GSE38959, GSE65194) were downloaded from the Gene Expression Omnibus (GEO). The R software packages were used to integrate the gene profiles and identify differentially expressed genes (DEGs). A variety of bioinformatics tools were used to explore the hub genes, including the DAVID database, STRING database and Cytoscape software. Reverse transcription quantitative PCR (RT-qPCR) was used to verify the hub genes in 14 pairs of TNBC paired tissues. RESULTS: In this study, we screened out 161 DEGs between 222 non-TNBC and 126 TNBC samples, of which 105 genes were up-regulated and 56 were down-regulated. These DEGs were enriched for 27 GO terms and two pathways. GO analysis enriched mainly in “cell division”, “chromosome, centromeric region” and “microtubule motor activity”. KEGG pathway analysis enriched mostly in “Cell cycle” and “Oocyte meiosis”. PPI network was constructed and then 10 top hub genes were screened. According to the analysis results of the Kaplan-Meier survival curve, the expression levels of only NUF2, FAM83D and CENPH were associated with the recurrence-free survival in TNBC samples (P < 0.05). RT-qPCR confirmed that the expression levels of NUF2 and FAM83D in TNBC tissues were indeed up-regulated significantly. CONCLUSIONS: The comprehensive analysis showed that NUF2 and FAM83D could be used as potential biomarkers for diagnosis and prognosis of TNBC. PeerJ Inc. 2020-09-21 /pmc/articles/PMC7513746/ /pubmed/33005492 http://dx.doi.org/10.7717/peerj.9975 Text en ©2020 Zhai et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Zhai, Xiuming
Yang, Zhaowei
Liu, Xiji
Dong, Zihe
Zhou, Dandan
Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer
title Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer
title_full Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer
title_fullStr Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer
title_full_unstemmed Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer
title_short Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer
title_sort identification of nuf2 and fam83d as potential biomarkers in triple-negative breast cancer
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513746/
https://www.ncbi.nlm.nih.gov/pubmed/33005492
http://dx.doi.org/10.7717/peerj.9975
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