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Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer

BACKGROUND: Triple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. However, current therapies have rarely improved the outcome of patients with TNBC. Here we sought to identify novel biomarkers or targets for TNBC. MATERIALS AND METHODS: Patients GSE76275 clinic trai...

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Autores principales: Wang, Ya, Li, Hanning, Ma, Jingjing, Fang, Tian, Li, Xiaoting, Liu, Jiahao, Afewerky, Henok Kessete, Li, Xiong, Gao, Qinglei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792947/
https://www.ncbi.nlm.nih.gov/pubmed/31632087
http://dx.doi.org/10.2147/OTT.S215898
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author Wang, Ya
Li, Hanning
Ma, Jingjing
Fang, Tian
Li, Xiaoting
Liu, Jiahao
Afewerky, Henok Kessete
Li, Xiong
Gao, Qinglei
author_facet Wang, Ya
Li, Hanning
Ma, Jingjing
Fang, Tian
Li, Xiaoting
Liu, Jiahao
Afewerky, Henok Kessete
Li, Xiong
Gao, Qinglei
author_sort Wang, Ya
collection PubMed
description BACKGROUND: Triple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. However, current therapies have rarely improved the outcome of patients with TNBC. Here we sought to identify novel biomarkers or targets for TNBC. MATERIALS AND METHODS: Patients GSE76275 clinic traits and their corresponding mRNA profiles for 198 TNBC and 67 non-TNBC were obtained from the GEO database. Weighted gene co-expression network analysis (WGCNA) of the GSE76275 keyed out hub genes, and the differentially expressed genes (DEGs) were identified with the cut-off of adjusted P (adj. P) <0.01 and |log2 fold-change (FC)| > 1.5. The hub - DEGs overlapping genes, as key genes, were considered for further study using Kaplan-Meier plotter online analysis. Subsequently, Breast Cancer Gene-Expression Miner v4.0 and tissue microarray analysis were applied to determine the transcriptional and translational levels of every key gene. Following plasmid transfection for overexpression, the proliferation of TNBC cells was determined by CCK8 and colony formation assay. Moreover, xenograft tumor models were canvassed to investigate their effect upon in vivo tumor growth. RESULTS: Four genes (SIDT1, ANKRD30A, GPR160, and CA12) were found to be associated with relapse-free survival (RFS) in TNBC through WGCNA and DEGs integrated analysis. Patients with a higher level of SIDT1 had significantly better RFS compared to those with lower levels. The transcriptional and translational levels of SIDT1 were validated as downregulated in patients with triple-negative status, negative estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Furthermore, SIDT1 inhibited proliferation of breast cancer cells (MDA-MB-231 and MDA-MB-468) and xenograft studies demonstrated that SIDT1 can suppress tumor growth in vivo. CONCLUSION: This study suggests that SIDT1 may play a crucial role in TNBC progression and has the potential as a prognostic biomarker of TNBC.
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spelling pubmed-67929472019-10-18 Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer Wang, Ya Li, Hanning Ma, Jingjing Fang, Tian Li, Xiaoting Liu, Jiahao Afewerky, Henok Kessete Li, Xiong Gao, Qinglei Onco Targets Ther Original Research BACKGROUND: Triple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. However, current therapies have rarely improved the outcome of patients with TNBC. Here we sought to identify novel biomarkers or targets for TNBC. MATERIALS AND METHODS: Patients GSE76275 clinic traits and their corresponding mRNA profiles for 198 TNBC and 67 non-TNBC were obtained from the GEO database. Weighted gene co-expression network analysis (WGCNA) of the GSE76275 keyed out hub genes, and the differentially expressed genes (DEGs) were identified with the cut-off of adjusted P (adj. P) <0.01 and |log2 fold-change (FC)| > 1.5. The hub - DEGs overlapping genes, as key genes, were considered for further study using Kaplan-Meier plotter online analysis. Subsequently, Breast Cancer Gene-Expression Miner v4.0 and tissue microarray analysis were applied to determine the transcriptional and translational levels of every key gene. Following plasmid transfection for overexpression, the proliferation of TNBC cells was determined by CCK8 and colony formation assay. Moreover, xenograft tumor models were canvassed to investigate their effect upon in vivo tumor growth. RESULTS: Four genes (SIDT1, ANKRD30A, GPR160, and CA12) were found to be associated with relapse-free survival (RFS) in TNBC through WGCNA and DEGs integrated analysis. Patients with a higher level of SIDT1 had significantly better RFS compared to those with lower levels. The transcriptional and translational levels of SIDT1 were validated as downregulated in patients with triple-negative status, negative estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Furthermore, SIDT1 inhibited proliferation of breast cancer cells (MDA-MB-231 and MDA-MB-468) and xenograft studies demonstrated that SIDT1 can suppress tumor growth in vivo. CONCLUSION: This study suggests that SIDT1 may play a crucial role in TNBC progression and has the potential as a prognostic biomarker of TNBC. Dove 2019-10-11 /pmc/articles/PMC6792947/ /pubmed/31632087 http://dx.doi.org/10.2147/OTT.S215898 Text en © 2019 Wang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wang, Ya
Li, Hanning
Ma, Jingjing
Fang, Tian
Li, Xiaoting
Liu, Jiahao
Afewerky, Henok Kessete
Li, Xiong
Gao, Qinglei
Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer
title Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer
title_full Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer
title_fullStr Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer
title_full_unstemmed Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer
title_short Integrated Bioinformatics Data Analysis Reveals Prognostic Significance Of SIDT1 In Triple-Negative Breast Cancer
title_sort integrated bioinformatics data analysis reveals prognostic significance of sidt1 in triple-negative breast cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792947/
https://www.ncbi.nlm.nih.gov/pubmed/31632087
http://dx.doi.org/10.2147/OTT.S215898
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