P-034 Occupational lung cancer: Application of microarray technology for monitoring gene expression patterns in chromate-related lung cancer

Lung Cancer ◽  
2005 ◽  
Vol 49 ◽  
pp. S123-S124
Author(s):  
A. Ewis ◽  
K. Kondo ◽  
Y. Shinohara ◽  
M. Ishikawa ◽  
Y. Baba
2016 ◽  
Vol 311 (6) ◽  
pp. L1245-L1258 ◽  
Author(s):  
Isaac K. Sundar ◽  
Irfan Rahman

Chromatin-modifying enzymes mediate DNA methylation and histone modifications on recruitment to specific target gene loci in response to various stimuli. The key enzymes that regulate chromatin accessibility for maintenance of modifications in DNA and histones, and for modulation of gene expression patterns in response to cigarette smoke (CS), are not known. We hypothesize that CS exposure alters the gene expression patterns of chromatin-modifying enzymes, which then affects multiple downstream pathways involved in the response to CS. We have, therefore, analyzed chromatin-modifying enzyme profiles and validated by quantitative real-time PCR (qPCR). We also performed immunoblot analysis of targeted histone marks in C57BL/6J mice exposed to acute and subchronic CS, and of lungs from nonsmokers, smokers, and patients with chronic obstructive pulmonary disease (COPD). We found a significant increase in expression of several chromatin modification enzymes, including DNA methyltransferases, histone acetyltransferases, histone methyltransferases, and SET domain proteins, histone kinases, and ubiquitinases. Our qPCR validation data revealed a significant downregulation of Dnmt1, Dnmt3a, Dnmt3b, Hdac2, Hdac4, Hat1, Prmt1, and Aurkb. We identified targeted chromatin histone marks (H3K56ac and H4K12ac), which are induced by CS. Thus CS-induced genotoxic stress differentially affects the expression of epigenetic modulators that regulate transcription of target genes via DNA methylation and site-specific histone modifications. This may have implications in devising epigenetic-based therapies for COPD and lung cancer.


2021 ◽  
Vol 9 ◽  
Author(s):  
Xiaodong Cui ◽  
Binghao Ren ◽  
Zhenghan Li

Inference of the gene regulation mechanism from gene expression patterns has become increasingly popular, in recent years, with the advent of microarray technology. Obtaining the states of genes and their regulatory relationships would greatly enable the scientists to investigate and understand the mechanisms of the diseases. However, it is still a big challenge to determine relationships from several thousands of genes. Here, we simplify the above complex gene state determination problem as an inference of the distribution of the ensemble Boolean networks (BNs). In order to investigate and calculate the distribution of the BNs’ states, we first compute the probabilities of the different BNs’ states and obtain the number of states Ω. Then, we find the maximum possible distribution of the number of the BNs’ states and calculate the fluctuation of the distribution. Finally, two representative experiments are conducted, and the efficiency of the obtained results is verified. The proposed algorithm is conceptually concise and easily applicable to many other realistic models; furthermore, it is highly extensible for various situations.


10.1038/87096 ◽  
2001 ◽  
Vol 27 (S4) ◽  
pp. 56-56
Author(s):  
Nalan Gokgoz ◽  
Xiang Sun ◽  
Shelly Bull ◽  
Jim Woodgett ◽  
Irene Andrulis

2008 ◽  
Vol 43 ◽  
pp. 359-367 ◽  
Author(s):  
ACO Evans ◽  
N Forde ◽  
GM OGorman ◽  
AE Zielak ◽  
P Lonergan ◽  
...  

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