Identification of Hub Genes Related to Liver Metastasis of Colorectal Cancer by Integrative Analysis

Liver metastasis of colorectal cancer (LMCRC) severely damages patient health, causing poor prognosis and tumor relapse. Marker genes associated with LMCRC identified by previous study did not meet therapeutic demand. Therefore, it is necessary to identify new biomarkers regulating the metastasis network and screen potential drugs for future treatment. Here, we identified that cell adhesion molecules and peroxisome proliferator-activated receptor (PPAR) signaling pathway were significantly enriched by analyzing the integrated-multiple expression profiles. Moreover, analysis with robust rank aggregation approach revealed a total of 138 differentially expressed genes (DEGs), including 108 upexpressed and 30 downexpressed genes. With establishing protein–protein interaction network, we also identified the subnetwork significantly enriching the metastasis-associated hub genes including ALB, APOE, CDH2, and ORM1. ESR2, FOXO3, and SRY were determined as key transcription factors regulating hub genes. In addition, ADH-1, epigallocatechin, CHEMBL1945287, and cochinchinenin C were predicted as potential therapeutic drugs. Moreover, the antimigration capacity of ADH-1 and epigallocatechin were confirmed in CRC cell lines. In conclusion, our findings not only offer opportunities to understand metastasis mechanism but also identify potential therapeutic targets for CRC.

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Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

Experimental Biology and Medicine ◽

10.1177/15353702211048757 ◽

2021 ◽

pp. 153537022110487

Author(s):

Zirui Zhu ◽

Rui Huang ◽

Baojun Huang

Keyword(s):

Messenger Rna ◽

Expression Profiles ◽

Clinical Stage ◽

Interaction Network ◽

Enrichment Analysis ◽

Rank Aggregation ◽

Circular Rnas ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

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Identification of Candidate Genes and Pathways in Nonsegmental Vitiligo Using Integrated Bioinformatics Methods

Dermatology ◽

10.1159/000511893 ◽

2020 ◽

pp. 1-9

Author(s):

Baoyi Liu ◽

Yongyi Xie ◽

Zhouwei Wu

Keyword(s):

Gene Expression ◽

Interaction Network ◽

Unknown Origin ◽

Cell Receptor ◽

R Package ◽

Peroxisome Proliferator ◽

Hub Genes ◽

Peroxisome Proliferator Activated Receptor ◽

Lesional Skin ◽

Functional Changes

Background: Nonsegmental vitiligo (NSV) is an acquired depigmentation disorder of unknown origin. Enormous interests focus on finding novel biomarkers and pathways responsible for NSV. Methods: The gene expression level was obtained by integrating microarray datasets (GSE65127 and GSE75819) from the Gene Expression Omnibus database using the sva R package. Differentially expressed genes (DEGs) between each group were identified by the limma R package. The interaction network was constructed using STRING, and significant modules coupled with hub genes were identified by cytoHubba and molecular complex detection. Pathway analyses were conducted using generally applicable gene set enrichment and further visualized in R environment. Results: A total of 102 DEGs between vitiligo lesional skin and healthy skin, 14 lesion-specific genes, and 29 predisposing genes were identified from the integrated dataset. Except for the anticipated decrease in melanogenesis, three major functional changes were identified, including oxidative phosphorylation, p53, and peroxisome proliferator-activated receptor (PPAR) signaling in lesional skin. PPARG, MUC1, S100A8, and S100A9 were identified as key hub genes involved in the pathogenesis of vitiligo. Besides, upregulation of the T cell receptor signaling pathway was considered to be associated with susceptibility of the skin in NSV patients. Conclusion: Our study reveals several potential pathways and related genes involved in NSV using integrated bioinformatics methods. It might provide references for targeted strategies for NSV.

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Peroxisome proliferator-activated receptor α activates cyclooxygenase-2 gene transcription through bile acid transport in human colorectal cancer cell lines

Journal of Gastroenterology ◽

10.1007/s00535-008-2188-3 ◽

2008 ◽

Vol 43 (7) ◽

pp. 538-549 ◽

Cited By ~ 15

Author(s):

Hiroshi Oshio ◽

Takaaki Abe ◽

Tohru Onogawa ◽

Hideo Ohtsuka ◽

Takeaki Sato ◽

...

Keyword(s):

Colorectal Cancer ◽

Bile Acid ◽

Cell Lines ◽

Gene Transcription ◽

Peroxisome Proliferator ◽

Acid Transport ◽

Human Colorectal Cancer ◽

Peroxisome Proliferator Activated Receptor ◽

Human Colorectal Cancer Cell ◽

Colorectal Cancer Cell Lines

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Functional genomic characterization of delipidation elicited by trans-10, cis-12-conjugated linoleic acid (t10c12-CLA) in a polygenic obese line of mice

Physiological Genomics ◽

10.1152/physiolgenomics.00244.2004 ◽

2005 ◽

Vol 21 (3) ◽

pp. 351-361 ◽

Cited By ~ 53

Author(s):

Ralph L. House ◽

Joseph P. Cassady ◽

Eugene J. Eisen ◽

Thomas E. Eling ◽

Jennifer B. Collins ◽

...

Keyword(s):

Gene Expression ◽

Linoleic Acid ◽

Glucose Transporter ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Liver Weight ◽

Peroxisome Proliferator ◽

Peroxisome Proliferator Activated Receptor ◽

Adult Mice ◽

Brown Adipose

Gene expression was measured during t10c12-CLA-induced body fat reduction in a polygenic obese line of mice. Adult mice ( n = 185) were allotted to a 2 × 2 factorial experiment consisting of either nonobese (ICR-control) or obese (M16-selected) mice fed a 7% fat, purified diet containing either 1% linoleic acid (LA) or 1% t10c12-CLA. Body weight (BW) by day 14 was 12% lower in CLA- compared with LA-fed mice ( P < 0.0001). By day 14, t10c12-CLA reduced weights of epididymal, mesenteric, and brown adipose tissues, as a percentage of BW, in both lines by 30, 27, and 58%, respectively, and increased liver weight/BW by 34% ( P < 0.0001). Total RNA was isolated and pooled (4 pools per tissue per day) from epididymal adipose ( days 5 and 14) of the obese mice to analyze gene expression profiles using Agilent mouse oligo microarray slides representing >20,000 genes. Numbers of genes differentially expressed by greater than or equal to twofold in epididymal adipose ( days 5 and 14) were 29 and 125, respectively. It was concluded that, in adipose tissue, CLA increased expression of uncoupling proteins (1 and 2), carnitine palmitoyltransferase system, tumor necrosis factor-α ( P < 0.05), and caspase-3 but decreased expression of peroxisome proliferator-activated receptor-γ, glucose transporter-4, perilipin, caveolin-1, adiponectin, resistin, and Bcl-2 ( P < 0.01). In conclusion, this experiment has revealed candidate genes that will be useful in elucidating mechanisms of adipose delipidation.

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Genomic Expression Profiling of Colorectal Cancer in Silico

10.21203/rs.3.rs-310514/v1 ◽

2021 ◽

Author(s):

Feifei Liu ◽

Yu Wang ◽

Wenxue Li ◽

Diancheng Li ◽

Yuwei Xin ◽

...

Keyword(s):

Colorectal Cancer ◽

Survival Analysis ◽

Mrna Expression ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Functional Enrichment ◽

Differentially Expressed ◽

Analysis Tool ◽

Hub Genes ◽

Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

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Integrated Transcriptomic Analysis Revealed Hub Genes and Pathways Involved in Sorafenib Resistance in Hepatocellular Carcinoma

Pathology & Oncology Research ◽

10.3389/pore.2021.1609985 ◽

2021 ◽

Vol 27 ◽

Author(s):

Xili Jiang ◽

Wei Zhang ◽

Lifeng Li ◽

Shucai Xie

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Expression Profiles ◽

Quantitative Polymerase Chain Reaction ◽

Pearson Correlation ◽

Acquired Resistance ◽

Rank Aggregation ◽

Health Concern ◽

Hub Genes ◽

Multikinase Inhibitor

Hepatocellular carcinoma (HCC), a high mortality malignancy, has become a worldwide public health concern. Acquired resistance to the multikinase inhibitor sorafenib challenges its clinical efficacy and the survival benefits it provides to patients with advanced HCC. This study aimed to identify critical genes and pathways associated with sorafenib resistance in HCC using integrated bioinformatics analysis. Differentially expressed genes (DEGs) were identified using four HCC gene expression profiles (including 34 sorafenib-resistant and 29 sorafenib-sensitive samples) based on the robust rank aggregation method and R software. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and small molecules reversing sorafenib resistance were searched for using the connectivity map (CMAP) database. Pearson correlation and survival analyses of hub genes were performed using cBioPortal and Gene Expression Profiling and Interactive Analysis (GEPIA). Finally, the expression levels of hub genes in sorafenib-resistant HCC cells were verified using quantitative polymerase chain reaction (q-PCR). A total of 165 integrated DEGs (66 upregulated and 99 downregulated in sorafenib resistant samples compared sorafenib sensitive ones) primarily enriched in negative regulation of endopeptidase activity, extracellular exosome, and protease binding were identified. Some pathways were commonly shared between the integrated DEGs. Seven promising therapeutic agents and 13 hub genes were identified. These findings provide a strategy and theoretical basis for overcoming sorafenib resistance in HCC patients.

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