The effect of Curcuma longa extract and its active component (curcumin) on gene expression profiles of lipid metabolism pathway in liver cancer cell line (HepG2)

Gene Reports ◽  
2020 ◽  
Vol 18 ◽  
pp. 100581 ◽  
Author(s):  
Reyhaneh Taebi ◽  
Mohammad Reza Mirzaiey ◽  
Mehdi Mahmoodi ◽  
Alireza Khoshdel ◽  
Mohammad Ali Fahmidehkar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lipid Metabolism ◽  
Liver Cancer ◽  
Active Component ◽  
Expression Profiles ◽  
Curcuma Longa ◽  
Gene Expression Profiles ◽  
Cancer Cell Line ◽  
Liver Cancer Cell ◽  
Metabolism Pathway

scholarly journals Gene expression profiles of liver cancer cell lines reveal two hepatocyte-like and fibroblast-like clusters

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245939
Author(s):  
Keita Fukuyama ◽  
Masataka Asagiri ◽  
Masahiro Sugimoto ◽  
Hiraki Tsushima ◽  
Satoru Seo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Cell Lines ◽  
Liver Cancer Cell ◽  
Study Objective

Cancer cell lines are widely used in basic research to study cancer development, growth, invasion, or metastasis. They are also used for the development and screening of anticancer drugs. However, there are no clear criteria for choosing the most suitable cell lines among the wide variety of cancer cell lines commercially available for research, and the choice is often based on previously published reports. Here, we investigated the characteristics of liver cancer cell lines by analyzing the gene expression data available in the Cancer Cell Line Encyclopedia. Unsupervised clustering analysis of 28 liver cancer cell lines yielded two main clusters. One cluster showed a gene expression pattern similar to that of hepatocytes, and the other showed a pattern similar to that of fibroblasts. Analysis of hepatocellular carcinoma gene expression profiles available in The Cancer Genome Atlas showed that the gene expression patterns in most hepatoma tissues were similar to those in the hepatocyte-like cluster. With respect to liver cancer research, our findings may be useful for selecting an appropriate cell line for a specific study objective. Furthermore, our approach of utilizing a public database for comparing the properties of cell lines could be an attractive cell line selection strategy that can be applied to other fields of research.

Isolation stress for 30 days alters hepatic gene expression profiles, especially with reference to lipid metabolism in mice

2009 ◽  
Vol 37 (2) ◽  
pp. 79-87 ◽  
Author(s):  
Keiko Motoyama ◽  
Yuji Nakai ◽  
Tomoya Miyashita ◽  
Yuichiro Fukui ◽  
Maki Morita ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lipid Metabolism ◽  
Dna Microarray ◽  
Social Stress ◽  
Secretory Pathway ◽  
Expression Profiles ◽  
Regulatory Element ◽  
Gene Expression Profiles ◽  
Hepatic Gene Expression ◽  
Isolation Stress

To elucidate the physiological responses to a social stressor, we exposed mice to an isolation stress and analyzed their hepatic gene expression profiles using a DNA microarray. Male BALB/c mice were exposed to isolation stress for 30 days, and then hepatic RNA was sampled and subjected to DNA microarray analysis. The isolation stress altered the expression of 420 genes (after considering the false discovery rate). Gene Ontology analysis of these differentially expressed genes indicated that the stress remarkably downregulated the lipid metabolism-related pathway through peroxisome proliferator-activated receptor-α, while the lipid biosynthesis pathway controlled by sterol regulatory element binding factor 1, Golgi vesicle transport, and secretory pathway-related genes were significantly upregulated. These results suggest that isolation for 30 days with a mild and consecutive social stress regulates the systems for lipid metabolism and also causes endoplasmic reticulum stress in mouse liver.

scholarly journals CancerLivER: a database of liver cancer gene expression resources and biomarkers

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Harpreet Kaur ◽  
Sherry Bhalla ◽  
Dilraj Kaur ◽  
Gajendra PS Raghava
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Full Potential ◽  
Individual Gene ◽  
Comprehensive Information ◽  
Tremendous Amount ◽  
Disease Specific

Abstract Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

scholarly journals GEDS: A Gene Expression Display Server for mRNAs, miRNAs and Proteins

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 675 ◽  
Author(s):  
Xia ◽  
Liu ◽  
Zhang ◽  
Guo
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Gene Expression Data ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Cell Line ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Expression Data ◽  
Protein Levels

High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available on http://bioinfo.life.hust.edu.cn/web/GEDS/.

scholarly journals Gene expression profiles of the one-carbon metabolism pathway

2009 ◽  
Vol 36 (5) ◽  
pp. 277-282 ◽  
Author(s):  
Yin Leng Lee ◽  
Xinran Xu ◽  
Sylvan Wallenstein ◽  
Jia Chen
Keyword(s):  
Gene Expression ◽  
Carbon Metabolism ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Metabolism Pathway ◽  
One Carbon Metabolism ◽  
The One

scholarly journals CCLA: an accurate method and web server for cancer cell line authentication using gene expression profiles

2019 ◽  
Author(s):  
Qiong Zhang ◽  
Mei Luo ◽  
Chun-Jie Liu ◽  
An-Yuan Guo
Keyword(s):  
Gene Expression ◽  
Cell Line ◽  
Cancer Cell ◽  
Expression Profiles ◽  
Web Server ◽  
Gene Expression Profiles ◽  
Cancer Cell Line ◽  
Model Systems ◽  
Validation Data ◽  
Cell Line Authentication

AbstractCancer cell lines (CCLs) as important model systems play critical roles in cancer researches. The misidentification and contamination of CCLs are serious problems, leading to unreliable results and waste of resources. Current methods for CCL authentication are mainly based on the CCL-specific genetic polymorphisms, whereas no method is available for CCL authentication using gene expression profiles. Here, we developed a novel method and homonymic web server (CCLA, Cancer Cell Line Authentication, http://bioinfo.life.hust.edu.cn/web/CCLA/) to authenticate 1,291 human CCLs of 28 tissues using gene expression profiles. CCLA curated CCL-specific gene signatures and employed machine learning methods to measure overall similarities and distances between the query sample and each reference CCL. CCLA showed an excellent speed advantage and high accuracy with a top 1 accuracy of 96.58% or 92.15% (top 3 accuracy of 100% or 95.11%) for microarray or RNA-Seq validation data (719 samples, 461 CCLs), respectively. To the best of our knowledge, CCLA is the first approach to authenticate CCLs based on gene expression. Users can freely and conveniently authenticate CCLs using gene expression profiles or NCBI GEO accession on CCLA website.

scholarly journals Integrative analysis of multiple gene expression profiles applied to liver cancer study

FEBS Letters ◽  
2004 ◽  
Vol 565 (1-3) ◽  
pp. 93-100 ◽  
Author(s):  
Jung Kyoon Choi ◽  
Jong Young Choi ◽  
Dae Ghon Kim ◽  
Dong Wook Choi ◽  
Bu Yeo Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrative Analysis ◽  
Multiple Gene ◽  
Cancer Study

scholarly journals Correlation between liver cancer occurrence and gene expression profiles in rat liver tissue

2011 ◽  
Vol 10 (4) ◽  
pp. 3480-3513 ◽  
Author(s):  
C.S. Xu ◽  
G.P. Wang ◽  
L.X. Zhang ◽  
C.F. Chang ◽  
J. Zhi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Rat Liver ◽  
Liver Tissue ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Occurrence

scholarly journals Analysis of gene expression profiles as a tool to uncover tumor markers of liver cancer progression in a rat model

2014 ◽  
Vol 3 (2) ◽  
pp. 167-172 ◽  
Author(s):  
VERÓNICA R. VÁSQUEZ-GARZÓN ◽  
OLGA BELTRÁN-RAMÍREZ ◽  
MARTHA E. SALCIDO-NEYOY ◽  
NANCY CERVANTE-ANAYA ◽  
SAÚL VILLA-TREVIÑO
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Tumor Markers ◽  
Cancer Progression ◽  
Rat Model ◽  
Expression Profiles ◽  
Gene Expression Profiles
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