scholarly journals Pathway Interactions Based on Drug-Induced Datasets

2019 ◽  
Vol 18 ◽  
pp. 117693511985151 ◽  
Author(s):  
Shinuk Kim
Keyword(s):  
Breast Cancer ◽  
Valproic Acid ◽  
Epithelial Cells ◽  
Sample Size ◽  
Drug Combination ◽  
Trichostatin A ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Drug Induced

In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. We found meaningful pathways using gene set enrichment analysis and identified intradrug and interdrug pathway interactions, which implied the influence of drug combination. Among the top 20 enrichment pathways that were wortmannin induced, there were a total of 37 intradrug pathway interactions via common genes. Thirty-seven pathway interactions were induced by valproic acid, 11 induced by trichostatin A, 20 induced by LY294002, and 59 induced by sirolimus, all via common genes. The number of interdrug-induced pathway interactions ranged from one pair of pathways to 23. The pair of ERBB_SIGNALING and INSULIN_SIGNALING pathways showed the highest score from a pair of 2 individual drugs. The highest number of pathway interactions was observed between the drugs 17-allylamino-geldanamycin and LY294002.

scholarly journals m6A-Mediated Tumor Invasion and Methylation Modification in Breast Cancer Microenvironment

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Fei Liu ◽  
Xiaopeng Yu ◽  
Guijin He
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Genomic Variation ◽  
Gene Set Enrichment Analysis ◽  
Single Sample ◽  
Gene Set Enrichment ◽  
Gene Set

Background. We analyzed the n6-methyladenosine (m6A) modification patterns of immune cells infiltrating the tumor microenvironment of breast cancer (BC) to provide a new perspective for the early diagnosis and treatment of BC. Methods. Based on 23 m6A regulatory factors, we identified m6A-related gene characteristics and m6A modification patterns in BC through unsupervised cluster analysis. To examine the differences in biological processes among various m6A modification modes, we performed genomic variation analysis. We then quantified the relative infiltration levels of different immune cell subpopulations in the tumor microenvironment of BC using the CIBERSORT algorithm and single-sample gene set enrichment analysis. Univariate Cox analysis was used to screen for m6A characteristic genes related to prognosis. Finally, we evaluated the m6A modification pattern of patients with a single BC by constructing the m6Ascore based on principal component analysis. Results. We identified three different m6A modification patterns in 2128 BC samples. A higher abundance of the immune infiltration of the m6Acluster C was indicated by the results of CIBERSORT and the single-sample gene set enrichment analysis. Based on the m6A characteristic genes obtained through screening, the m6Ascore was determined. The BC patients were segregated into m6Ascore groups of low and high categories, which revealed significant survival benefits among patients with low m6Ascores. Additionally, the high-m6Ascore group had a higher mutation frequency and was associated with low PD-L1 expression, and the m6Ascore and tumor mutation burden showed a positive correlation. In addition, treatment effects were better in patients in the high-m6Ascore group. Conclusions. In case of a single patient with BC, the immune cell infiltration characteristics of the tumor microenvironment and the m6A methylation modification pattern could be evaluated using the m6Ascore. Our results provide a foundation for improving personalized immunotherapy of BC.

scholarly journals Overexpression of CENPF correlates with poor prognosis and tumor bone metastasis in breast cancer

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jingbo Sun ◽  
Jingzhan Huang ◽  
Jin Lan ◽  
Kun Zhou ◽  
Yuan Gao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bone Metastasis ◽  
Western Blot ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Free Survival ◽  
Gene Set ◽  
Oncomine Database ◽  
Kaplan Meier

Abstract Background Centromere Protein F (CENPF) associates with the centromere–kinetochore complex and influences cell proliferation and metastasis in several cancers. The role of CENPF in breast cancer (BC) bone metastasis remains unclear. Methods Using the ONCOMINE database, we compared the expression of CENPF in breast cancer and normal tissues. Findings were confirmed in 60 BC patients through immunohistochemical (IHC) staining. Microarray data from GEO and Kaplan–Meier plots were used analyze the overall survival (OS) and relapse free survival (RFS). Using the GEO databases, we compared the expression of CENPF in primary lesions, lung metastasis lesions and bone metastasis lesions, and validated our findings in BALB/C mouse 4T1 BC models. Based on gene set enrichment analysis (GSEA) and western blot, we predicted the mechanisms by which CENPF regulates BC bone metastasis. Results The ONCOMINE database and immunohistochemical (IHC) showed higher CENPF expression in BC tissue compared to normal tissue. Kaplan–Meier plots also revealed that high CENPF mRNA expression correlated to poor survival and shorter progression-free survival (RFS). From BALB/C mice 4T1 BC models and the GEO database, CENPF was overexpressed in primary lesions, other target organs, and in bone metastasis. Based on gene set enrichment analysis (GSEA) and western blot, we predicted that CENPF regulates the secretion of parathyroid hormone-related peptide (PTHrP) through its ability to activate PI3K–AKT–mTORC1. Conclusion CENPF promotes BC bone metastasis by activating PI3K–AKT–mTORC1 signaling and represents a novel therapeutic target for BC treatment.

Gene expression combined with gene set enrichment analysis to identify markers of vinorelbine efficacy in breast cancer patients.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e21099-e21099
Author(s):  
Robert Audet ◽  
Changyu Shen ◽  
Scooter Willis ◽  
Renata Duchnowska ◽  
Krzysztof Adamowicz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Transcription Factor ◽  
Chromosomal Location ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Molecular Function ◽  
Time To Progression ◽  
Gene Set Enrichment ◽  
Histone Binding

e21099 Background: Vinorelbine (V) induces mitotic arrest and apoptosis but there are limited data on its effect on gene expression in breast cancer clinical setting. Methods: 43 adult female patients with pathologically confirmed breast cancer and locally advanced or metastatic disease were treated with V 25 mg/m2 days 1, 8, 15 of a 28-day cycle. Gene expression was assessed in archival FFPE tissue using the microarray-based DASL assay (cDNA-mediated Annealing, Selection extension and Ligation) and correlated with time-to-progression (TTP). Using a Gene Set Enrichment Analysis (GSEA), groups of genes that share a common molecular function, chromosomal location, or regulation were identified in patients classified as having either a short (S) (n=25) or a long (L) (n=18) time to progression (TTP) divided by the median (72 days). The GSEA software ( http://www.broadinstitute.org/gsea/index.jsp ) was used for the analysis. Results: GSEA focusing on genes grouped according to similar a) molecular function: 16 out of a set of 43 genes involved in histone binding were enriched in group S (p = 0.002), consistent with higher expression in group S of HIST3H2BB and HIST1H3I as well as a nuclear transcription factor promoting their expression. b) transcription factors: 14 out of 47 genes were enriched in group S (p = 0.004) and corresponds to genes with promoter regions that match c-fos serum response element-binding transcription factor that modulates, for example, ABCC1 and ABCB1 (P-gp/MDR1) solute carriers. c) chromosomal location: in group S, genes were enriched on chromosome 11q21 (20 out of 45 genes p = 0.004) and on chromosome 12p12 (14 out of 22 genes p = 0.002). Conclusions: a) the up-regulation of histone binding genes is consonant with recent discovery of high affinity V binding to histones b) the role of P-gp/MDR1 in V transport is well known c) our observations on chromosome 11q21 and12p12 are novel. DASL expression combined with GSEA highlights gene sets that correlate with clinical outcome and may lead to predictive markers of V efficacy. Further confirmatory analysis is needed due to the limitation of small sample size and multiple comparisons.

scholarly journals Identification of a Lipid Metabolism-Associated Gene Signature Predicting Survival in Breast Cancer

2021 ◽  
Author(s):  
Mingkai Gong ◽  
Xiangping Liu ◽  
Wu Yang ◽  
Hongming Song ◽  
Xian Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lipid Metabolism ◽  
High Risk ◽  
Risk Score ◽  
Risk Model ◽  
Risk Group ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Prognostic Analysis

Abstract Background: Cancer metabolism and specifically lipid metabolism play an important role in breast cancer (BC) progression and metastasis. However, the role of lipid metabolism-associated genes (LMGs) in the diagnosis of breast cancer remains unknown. Methods: The expression profiles and clinical follow-up information of BC were downloaded from The Cancer Genome Atlas (TCGA), and metabolic genes were downloaded from the Gene Set Enrichment Analysis (GSEA) dataset. Univariate cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed on the differentially expressed metabolism-related genes. Then, the formula of the metabolism-related risk model was composed, and the risk score of each patient was calculated. The breast cancer patients were divided into high-risk and low-risk groups with a cutoff of the median expression value of the risk score, and the prognostic analysis was also used to analyze the survival time between these two groups. Finally, we analyzed the expression, interaction and correlation among the lipid metabolism-associated genes risk model.Results: The results from the prognostic analysis indicated that the survival was significantly poorer in the high-risk group than in the low-risk group in TCGA, single-sample gene set enrichment analysis (ssGSEA) shows it is plausible that lipid metabolism is highly correlated with tumor immunity.Conclusion: Lipid metabolism-associated genes may become a new prognostic indicator predicting the survival of BC patients. The prognostic genes (n=16) may help provide new strategies for tumor therapy.

scholarly journals Screening of DNA Damage Repair Genes Involved in the Prognosis of Triple-Negative Breast Cancer Patients Based on Bioinformatics

2021 ◽  
Vol 12 ◽  
Author(s):  
Nan Wang ◽  
Yuanting Gu ◽  
Jiangrui Chi ◽  
Xinwei Liu ◽  
Youyi Xiong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regulatory Network ◽  
Prognostic Model ◽  
Triple Negative ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Regression Analyses ◽  
Gene Set Enrichment ◽  
Qrt Pcr

Background: Triple-negative breast cancer (TNBC) is a special subtype of breast cancer with poor prognosis. DNA damage response (DDR) is one of the hallmarks of this cancer. However, the association of DDR genes with the prognosis of TNBC is still unclear.Methods: We identified differentially expressed genes (DEGs) between normal and TNBC samples from The Cancer Genome Atlas (TCGA). DDR genes were obtained from the Molecular Signatures Database through six DDR gene sets. After the expression of six differential genes were verified by quantitative real-time polymerase chain reaction (qRT-PCR), we then overlapped the DEGs with DDR genes. Based on univariate and LASSO Cox regression analyses, a prognostic model was constructed to predict overall survival (OS). Kaplan–Meier analysis and receiver operating characteristic curve were used to assess the performance of the prognostic model. Cox regression analysis was applied to identify independent prognostic factors in TNBC. The Human Protein Atlas was used to study the immunohistochemical data of six DEGs. The prognostic model was validated using an independent dataset. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analysis were performed by using gene set enrichment analysis (GSEA). Single-sample gene set enrichment analysis was employed to estimate immune cells related to this prognostic model. Finally, we constructed a transcriptional factor (TF) network and a competing endogenous RNA regulatory network.Results: Twenty-three differentially expressed DDR genes were detected between TNBC and normal samples. The six-gene prognostic model we developed was shown to be related to OS in TNBC using univariate and LASSO Cox regression analyses. All the six DEGs were identified as significantly up-regulated in the tumor samples compared to the normal samples in qRT-PCR. The GSEA analysis indicated that the genes in the high-risk group were mainly correlated with leukocyte migration, cytokine interaction, oxidative phosphorylation, autoimmune diseases, and coagulation cascade. The mutation data revealed the mutated genes were different. The gene-TF regulatory network showed that Replication Factor C subunit 4 occupied the dominant position.Conclusion: We identified six gene markers related to DDR, which can predict prognosis and serve as an independent biomarker for TNBC patients.

scholarly journals Screening of DNA Damage Repair Genes Involved in the Prognosis of Triple-Negative Breast Cancer Patients Based on Bioinformatics

2021 ◽  
Author(s):  
Nan Wang ◽  
Yuanting Gu ◽  
Jiangrui Chi ◽  
Xinwei Liu ◽  
Youyi Xiong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Damage ◽  
Regulatory Network ◽  
Prognostic Model ◽  
Triple Negative ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Regression Analyses ◽  
Gene Set Enrichment

Abstract Background: Triple-negative breast cancer (TNBC) is a special subtype of breast cancer with poor prognosis. DNA damage response (DDR) is one of the hallmarks of this cancer. However, the association of DDR genes with the prognosis of TNBC is still unclear.Methods: We identified differentially expressed genes (DEGs) between normal and TNBC samples from The Cancer Genome Atlas (TCGA). DDR genes were obtained from the Molecular Signatures Database (MSigDB) through six DDR gene sets. We then overlapped the DEGs with DDR genes. Based on univariate and LASSO Cox regression analyses, a prognostic model was constructed to predict overall survival (OS). Kaplan–Meier (K–M) analysis and receiver operating characteristic (ROC) curve were used to assess the performance of the prognostic model. Cox regression analysis was applied to identify independent prognostic factors in TNBC. The prognostic model was validated using an independent dataset. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by using gene set enrichment analysis (GSEA). Single-sample gene set enrichment analysis (ssGSEA) was employed to estimate immune cells related to this prognostic model. Finally, we constructed a transcriptional factor (TF) network and a competing endogenous RNA (ceRNA) regulatory network.Results: 23 differentially expressed DDR genes were detected between TNBC and normal samples. The six-gene prognostic model we developed was shown to be related to OS in TNBC using univariate and LASSO Cox regression analyses. By drawing ROC curve and KM curve, we determined the effectiveness of the risk model. The prognostic value of the six-gene prognostic model was further validated using the GSE58812 dataset. The GSEA analysis indicated that the genes in the high-risk group were mainly correlated with leukocyte migration, cytokine interaction with cytokine receptors, oxidative phosphorylation, autoimmune diseases, and coagulation cascade. The mutation data revealed that the mutation frequency of the two groups was the same, while the mutated genes were different. The gene-TF regulatory network showed that Replication Factor C subunit 4 (RFC4) occupied the dominant position.Conclusion: We identified six gene markers related to DDR, which can predict prognosis and serve as an independent biomarker for TNBC patients.

scholarly journals Genome-wide association study of asthma exacerbations despite inhaled corticosteroids use

2020 ◽  
pp. 2003388
Author(s):  
Natalia Hernandez-Pacheco ◽  
Susanne J Vijverberg ◽  
Esther Herrera-Luis ◽  
Jiang Li ◽  
Yang Yie Sio ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Inhaled Corticosteroids ◽  
Trichostatin A ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association ◽  
Gene Set Enrichment ◽  
Asthma Exacerbations ◽  
Genome Wide ◽  
European Populations

RationaleSubstantial variability in response to asthma treatment with inhaled corticosteroids (ICS) has been described among individuals and populations, suggesting the contribution of genetic factors. Nonetheless, only a few genes have been identified to date. We aimed to identify genetic variants associated with asthma exacerbations despite ICS use in European children and young adults and to validate the findings in non-Europeans. Moreover, we explored whether a gene-set enrichment analysis could suggest potential novel asthma therapies.MethodsA genome-wide association study (GWAS) of asthma exacerbations was tested in 2681 European-descent children treated with ICS from eight studies. Suggestive association signals were followed up for replication in 538 European asthma patients. Further evaluation was performed in 1773 non-Europeans. Variants revealed by published GWAS were assessed for replication. Additionally, gene-set enrichment analysis focused on drugs was performed.ResultsTen independent variants were associated with asthma exacerbations despite ICS treatment in the discovery phase (p≤5×10−6). Of those, one variant at the CACNA2D3-WNT5A locus was nominally replicated in Europeans (rs67026078, p=0.010), but this was not validated in non-European populations. Five other genes associated with ICS response in previous studies were replicated. Additionally, an enrichment of associations in genes regulated by trichostatin A treatment was found.ConclusionsThe intergenic region of CACNA2D3 and WNT5A was revealed as a novel locus for asthma exacerbations despite ICS treatment in European populations. Genes associated were related to trichostatin A, suggesting that this drug could regulate the molecular mechanisms involved in treatment response.

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