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 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 Revealing Biological Pathways Implicated in Lung Cancer from TCGA Gene Expression Data Using Gene Set Enrichment Analysis

2014 ◽  
Vol 13s1 ◽  
pp. CIN.S13882 ◽  
Author(s):  
Binghuang Cai ◽  
Xia Jiang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Gene Expression Data ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Expression Data ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Pathway Gene

Analyzing biological system abnormalities in cancer patients based on measures of biological entities, such as gene expression levels, is an important and challenging problem. This paper applies existing methods, Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis, to pathway abnormality analysis in lung cancer using microarray gene expression data. Gene expression data from studies of Lung Squamous Cell Carcinoma (LUSC) in The Cancer Genome Atlas project, and pathway gene set data from the Kyoto Encyclopedia of Genes and Genomes were used to analyze the relationship between pathways and phenotypes. Results, in the form of pathway rankings, indicate that some pathways may behave abnormally in LUSC. For example, both the cell cycle and viral carcinogenesis pathways ranked very high in LUSC. Furthermore, some pathways that are known to be associated with cancer, such as the p53 and the PI3K-Akt signal transduction pathways, were found to rank high in LUSC. Other pathways, such as bladder cancer and thyroid cancer pathways, were also ranked high in LUSC.

Differential gene expression in prostate tissue according to vasectomy.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 298-298
Author(s):  
Kathryn M Wilson ◽  
Travis Gerke ◽  
Ericka Ebot ◽  
Jennifer A Sinnott ◽  
Jennifer R. Rider ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Cancer Diagnosis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Prostate Tissue ◽  
Gene Set Enrichment ◽  
Normal Prostate ◽  
Gene Sets ◽  
Normal Prostate Tissue

298 Background: We previously found that vasectomy was associated with an increased risk of prostate cancer, and particularly, risk of lethal prostate cancer in the Health Professionals Follow-up Study (HPFS). However, the possible biological basis for this finding is unclear. In this study, we explored possible biological mechanisms by assessing differences in gene expression in the prostate tissue of men with and without a history of vasectomy prostate cancer diagnosis. Methods: Within the HPFS, vasectomy data and gene expression data (20,254 genes) was available from archival tumor tissue from 263 cases, 124 of whom also had data for adjacent normal tissue. To relate expression of individual genes to vasectomy we used linear regression adjusting for age and year at diagnosis. We ran gene set enrichment analysis to identify pathways of genes associated with vasectomy. Results: Among 263 cases, 67 (25%) reported a vasectomy prior to cancer diagnosis. Mean age at diagnosis was 66 years among men without and 65 years among men with vasectomy. Median time between vasectomy and prostate cancer diagnosis was 25 years. Gene expression in tumor tissue was not associated with vasectomy status. In adjacent normal tissue, three individual genes were associated with vasectomy with Bonferroni-corrected p-values of < 0.10: RAPGEF6, OR4C3, and SLC35F4. Gene set enrichment analysis found five pathways upregulated and seven pathways downregulated in men with vasectomy compared to those without in normal prostate tissue with a FDR < 0.05. Upregulated pathways included several immune-related gene sets and G-protein-coupled receptor gene sets. Conclusions: We identified significant differences in gene expression profiles in normal prostate tissue according to vasectomy status among men treated for prostate cancer. The fact that such differences existed several decades after vasectomy provides support for the idea that vasectomy may play a role in the etiology of prostate cancer.

scholarly journals A Comparative Study of Mouse Hepatic and Intestinal Gene Expression Profiles under PPARαKnockout by Gene Set Enrichment Analysis

PPAR Research ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Kan He ◽  
Qishan Wang ◽  
Yumei Yang ◽  
Minghui Wang ◽  
Yuchun Pan
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Gene Set Enrichment Analysis ◽  
Small Cell Lung ◽  
Gene Set Enrichment ◽  
Tissue Specific

Gene expression profiling of PPARαhas been used in several studies, but fewer studies went further to identify the tissue-specific pathways or genes involved in PPARαactivation in genome-wide. Here, we employed and applied gene set enrichment analysis to two microarray datasets both PPARαrelated respectively in mouse liver and intestine. We suggested that the regulatory mechanism of PPARαactivation by WY14643 in mouse small intestine is more complicated than in liver due to more involved pathways. Several pathways were cancer-related such as pancreatic cancer and small cell lung cancer, which indicated that PPARαmay have an important role in prevention of cancer development. 12 PPARαdependent pathways and 4 PPARαindependent pathways were identified highly common in both liver and intestine of mice. Most of them were metabolism related, such as fatty acid metabolism, tryptophan metabolism, pyruvate metabolism with regard to PPARαregulation but gluconeogenesis and propanoate metabolism independent of PPARαregulation. Keratan sulfate biosynthesis, the pathway of regulation of actin cytoskeleton, the pathways associated with prostate cancer and small cell lung cancer were not identified as hepatic PPARαindependent but as WY14643 dependent ones in intestinal study. We also provided some novel hepatic tissue-specific marker genes.

scholarly journals Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum

2020 ◽  
Author(s):  
Priyanka Chakraborty ◽  
Jason T George ◽  
Wendy A Woodward ◽  
Herbert Levine ◽  
Mohit Kumar Jolly
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Inflammatory Breast Cancer ◽  
Predictive Accuracy ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Clinical Samples ◽  
Intratumor Heterogeneity ◽  
Training Algorithms

AbstractInflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.

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.

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