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.

p53-regulated GML gene expression in non-small cell lung cancer: Relation to cisplatin chemosensitivity

Lung Cancer ◽  
2000 ◽  
Vol 29 (1) ◽  
pp. 193
Author(s):  
M Higashiyama ◽  
K Kodama ◽  
H Yokouchi ◽  
K Takami ◽  
Y Miyoshi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

Effects of fine air particulates on gene expression in non-small-cell lung cancer

2017 ◽  
Vol 62 (2) ◽  
pp. 295-301 ◽  
Author(s):  
Biao Yang ◽  
Xinming Li ◽  
Dongmei Chen ◽  
Chunling Xiao
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

scholarly journals Cell-autonomous immune gene expression is repressed in pulmonary neuroendocrine cells and small cell lung cancer

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ling Cai ◽  
Hongyu Liu ◽  
Fang Huang ◽  
Junya Fujimoto ◽  
Luc Girard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Neuroendocrine Cells ◽  
Immune Gene ◽  
Small Cell Lung ◽  
Immune Gene Expression ◽  
Pulmonary Neuroendocrine Cells

AbstractSmall cell lung cancer (SCLC) is classified as a high-grade neuroendocrine (NE) tumor, but a subset of SCLC has been termed “variant” due to the loss of NE characteristics. In this study, we computed NE scores for patient-derived SCLC cell lines and xenografts, as well as human tumors. We aligned NE properties with transcription factor-defined molecular subtypes. Then we investigated the different immune phenotypes associated with high and low NE scores. We found repression of immune response genes as a shared feature between classic SCLC and pulmonary neuroendocrine cells of the healthy lung. With loss of NE fate, variant SCLC tumors regain cell-autonomous immune gene expression and exhibit higher tumor-immune interactions. Pan-cancer analysis revealed this NE lineage-specific immune phenotype in other cancers. Additionally, we observed MHC I re-expression in SCLC upon development of chemoresistance. These findings may help guide the design of treatment regimens in SCLC.

scholarly journals Predicting Diagnostic Gene Biomarkers for Non-Small-Cell Lung Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Bin Liang ◽  
Yang Shao ◽  
Fei Long ◽  
Shu-Juan Jiang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Association Network ◽  
Small Cell Lung ◽  
Functional Association ◽  
Functional Association Network ◽  
Gene Modules

Lung cancer is the primary reason for death due to cancer worldwide, and non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer. Most patients die from complications of NSCLC due to poor diagnosis. In this paper, we aimed to predict gene biomarkers that may be of use for diagnosis of NSCLC by integrating differential gene expression analysis with functional association network analysis. We first constructed an NSCLC-specific functional association network by combining gene expression correlation with functional association. Then, we applied a network partition algorithm to divide the network into gene modules and identify the most NSCLC-specific gene modules based on their differential expression pattern in between normal and NSCLC samples. Finally, from these modules, we identified genes that exhibited the most impact on the expression of their functionally associated genes in between normal and NSCLC samples and predicted them as NSCLC biomarkers. Literature review of the top predicted gene biomarkers suggested that most of them were already considered critical for development of NSCLC.

scholarly journals Prognostic significance of epigenetic regulatory gene expression in patients with non-small-cell lung cancer

Aging ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 7397-7415
Author(s):  
Zegui Tu ◽  
Xiancheng Chen ◽  
Tian Tian ◽  
Guo Chen ◽  
Meijuan Huang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Regulatory Gene ◽  
Prognostic Significance ◽  
Small Cell ◽  
Small Cell Lung
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