MAT1 correlates with molecular subtypes and predicts poor survival in breast cancer

Xu, Hanxiao; Bai, Xia; Yu, Shengnan; Liu, Qian; Pestell, Richard G.; Wu, Zeyu

doi:10.21147/j.issn.1000-9604.2018.03.07

Cited by 3 publications

(4 citation statements)

References 35 publications

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“…Kaplan-Meier Plotter (http://kmplot.com/analysis/), an online tool, was used to assess the effect of 54,675 genes on survival using 10,461 cancer samples (5,143 breast, 1,816 ovarian, 2,437 lung, and 1,065 gastric cancer) and to perform survival analysis on DEGs (19). Recurrence-free survival refers to the recurrence-free survival of BC patients, and the overall survival (OS) is the time from diagnosis to any cause of death.…”

Section: Methodsmentioning

confidence: 99%

Identifying the Antiproliferative Effect of Astragalus Polysaccharides on Breast Cancer: Coupling Network Pharmacology With Targetable Screening From the Cancer Genome Atlas

Liu

Wang

et al. 2019

Front. Oncol.

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Background: Astragalus polysaccharides (APS), natural plant compounds, have recently emerged as a promising strategy for cancer treatment, but little is known concerning their effects on breast cancer (BC) tumorigenesis. Methods: We obtained breast cancer genetic data from The Cancer Genome Atlas (TCGA) database, network pharmacology to further clarify its biological properties. Survival analysis and molecular docking techniques were implemented for the final screening to obtain key target information. Our experiments focused on the detection of intervention effects of APS on BC cells (MCF-7 and MDA-MB-231), and quantitative RT-PCR (qRT-PCR) was used to assess the expression of key targets. Results: A total of 1,439 differentially expressed genes (DEGs) were identified by TCGA and used to build disease networks. Module analysis, gene ontology and pathway analysis revealed characteristic of the DEGs network. Topological properties were used to identify key targets, survival analysis and molecular docking finally found that the targets of APS regulation of BC cells may be CCNB1, CDC6, and p53. Through cell viability, migration and invasion assays, we found that APS interferes with the development of breast cancer in MCF7 and MDA-MB-231 cells in a dose-dependent manner. Furthermore, qRT-PCR verification suggested that the expression of CCNB1 and CDC6 in breast cancer cells was significantly downregulated in response to APS, while expression of the tumor suppressor gene P53 was significantly increased. Conclusion: Results of this study suggest therapeutic potential for APS in BC treatment, possibly through interventions with CCNB1, CDC6, and P53. Furthermore, these findings illustrate the feasibility of using network pharmacology to connect large-scale target data as a way to discover the mechanism of natural products interfering with disease.

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Section: Methodsmentioning

confidence: 99%

Identifying the Antiproliferative Effect of Astragalus Polysaccharides on Breast Cancer: Coupling Network Pharmacology With Targetable Screening From the Cancer Genome Atlas

Liu

Wang

et al. 2019

Front. Oncol.

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“…Human embryonic kidney 293T cells were transfected with the combination of expression vector or control vector with human package plasmids by Lipofectamine™ 2000 (Invitrogen, Carlsbad CA, USA). After transfection, the viral supernatant was harvested and filtered to infect MCF-7 and MDA-MB-231 cells for three times as described previously (39). EYA2 stable cells were selected by green fluorescent protein.…”

Section: Methodsmentioning

confidence: 99%

“…IF staining was performed based on published methods (39, 40). Primary antibodies were used at 1:150 dilution as following: EYA2 (ab95875, Abcam), YBX1 (sc-101198, Santa Cruz), EGFR (sc-03, Santa Cruz) and PCNA (sc-7907, Santa Cruz).…”

Section: Methodsmentioning

confidence: 99%

EYA2 Correlates With Clinico-Pathological Features of Breast Cancer, Promotes Tumor Proliferation, and Predicts Poor Survival

Jiao

et al. 2019

Front. Oncol.

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Eyes absent homolog 2 (EYA2), a transcriptional activator, is pivotal for organ development, but aberrant regulation of EYA2 has been reported in multiple human tumors. However, the role of EYA2 in breast cancer is still lack of full understanding. To explore the biological significance of EYA2 in breast cancer, we conducted data analysis on public breast cancer datasets, and performed immunohistochemistry (IHC) analysis, colony-forming unit assays, EdU assay, western blotting, and immunofluorescence (IF). Meta-analysis showed that EYA2 mRNA expression was correlated with tumor grade, the status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). IHC analysis displayed that EYA2 protein abundance was inversely associated with the status of ER and PR, and enriched in triple-negative breast cancer in comparison with luminal-type tumors. Additionally, correlation analysis reflected that EYA2 mRNA was negatively correlated with luminal markers, and positively associated with markers of basal cells, epithelial-mesenchymal transition and cancer stem cells. Clone-forming assay and EdU experiment showed that EYA2 overexpression enhanced proliferation of breast cancer cells. Results from western blotting and IF displayed that overexpression of EYA2 up-regulated the protein abundance of proliferation markers. Importantly, survival analysis indicated that higher EYA2 mRNA level predicted worse overall survival, relapse-free survival and metastasis-free survival among whole enrolled breast cancer patients. Collectively, EYA2 was closely correlated with clinico-pathological characteristics, and served as a proliferation stimulator for breast cancer cells and an unfavorable prognostic element for breast cancer patients, suggesting that EYA2 is involved in the progression of breast carcinoma.

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“…Survival Analysis of PPI Genes. Kaplan-Meier Plotter (http://kmplot.com/analysis/) is an online tool that was used to perform survival analysis of the top eight PPI genes in GACA patients [43]. Recurrence-free survival (RFS) refers to the recurrence-free period of GACA patients, and overall survival (OS) is the time from diagnosis to death.…”

Section: Enrichment Analysis Of Gene Ontology Functionalmentioning

confidence: 99%

Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses

Zhou

Zhang

et al. 2022

Computational and Mathematical Methods in Medicine

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Objective. This study is aimed at screening out effective active compounds of Qizhen capsule (QZC) and exploring the underlying mechanisms against gastric cancer (GACA) by combining both bioinformatic analysis and experimental approaches. Weighted gene coexpression network analysis (WGCNA), network pharmacology, molecular docking simulation, survival analysis, and data-based differential gene and protein expression analysis were employed to predict QZC’s potential targets and explore the underlying mechanisms. Subsequently, multiple experiments, including cell viability, apoptosis, and protein expression analyses, were conducted to validate the bioinformatics-predicted therapeutic targets. The results indicated that luteolin, rutin, quercetin, and kaempferol were vital active compounds, and TP53, MAPK1, and AKT1 were key targets. Molecular docking simulation showed that the four abovementioned active compounds had high binding affinities to the three main targets. Enrichment analysis showed that vital active compounds exerted therapeutic effects on GACA through regulating the TP53 pathway, MAPK pathway, and PI3K/AKT pathway. Furthermore, data-based gene expression analysis revealed that TP53 and JUN genes were not only differentially expressed between normal and GACA tissues but also correlated with clinical stages. In parallel, in vitro experimental results suggested that QZC exerted therapeutic effects on GACA by decreasing IC50 values, downregulating AKT expression, upregulating TP53 and MAPK expression, and increasing apoptosis of SGC-7901 cells. This study highlights the potential candidate biomarkers, therapeutic targets, and basic mechanisms of QZC in treating GACA, providing a foundation for new drug development, target mining, and related animal studies in GACA.

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MAT1 correlates with molecular subtypes and predicts poor survival in breast cancer

Abstract: MAT1 is correlated with molecular subtypes and is associated with unfavorable prognosis for breast cancer patients.

Cited by 3 publications

References 35 publications

Identifying the Antiproliferative Effect of Astragalus Polysaccharides on Breast Cancer: Coupling Network Pharmacology With Targetable Screening From the Cancer Genome Atlas

Identifying the Antiproliferative Effect of Astragalus Polysaccharides on Breast Cancer: Coupling Network Pharmacology With Targetable Screening From the Cancer Genome Atlas

EYA2 Correlates With Clinico-Pathological Features of Breast Cancer, Promotes Tumor Proliferation, and Predicts Poor Survival

Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses

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