scholarly journals Identification of consistent post-translational regulatory triplets related to oncogenic and tumour suppressive modulators in childhood acute lymphoblastic leukemia

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11803
Author(s):  
YongKiat Wee ◽  
Yining Liu ◽  
Min Zhao

Background Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. It can be caused by mutations that turn on oncogenes or turn off tumour suppressor genes. For instance, changes in certain genes including Rb and p53 are common in ALL cells. Oncogenes and TSGs may serve as a modulator gene to regulate the gene expression level via their respective target genes. To investigate the regulatory relationship between oncogenes, tumour suppressor genes and transcription factors at the post translational level in childhood ALL, we performed an integrative network analysis on the gene regulation in the post-translational level for childhood ALL based on many publicly available cancer gene expression data including TARGET and GEO database. Methods We collected 259 childhood ALL-related genes from the latest online leukemia database, Leukemia Gene Literature Database. These 259 genes were selected from a comprehensive systematic literature with experimental evidences. The identified and curated genes were also associated with patient survival cases and we incorporated this pediatric ALL-related gene list into our analysis. We extracted the known human TFs from the TRRUST database. Among 259 childhood ALL-related genes, 101 unique regulators were mapped to the list of oncogene and tumour suppressor genes (TSGs) from the ONGene and the TSGene databases, and these included 74 TSGs, 62 oncogenes and 46 TF genes. Results The resulted regulation was presented as a hierarchical regulatory network with transcription factors (TFs) as intermediate regulators connecting the top modulators (oncogene and TSGs) to the common target genes. Cross-validation was applied to the results from the TARGET dataset by identifying the consistent regulatory motifs based on three independent ALL expression datasets. A three-layer regulatory network of consistent positive modulators in childhood ALL was constructed in which 74 modulators (40 oncogenes, 34 TSGs) are considered as the most important regulators. The middle layer and the bottom layer contain 34 TFs and 176 target genes, respectively. Oncogenes mostly participated in positive regulation of gene expression and the transcription process of RNA II polymerase, while TSGs were mainly involved in the negative regulation of gene expression. In addition, the oncogene-specific targets were enriched with regulators of the MAPK cascade while tumour suppressor-specific targets were associated with cell death. Conclusion The results revealed that oncogenes and TSGs possess a different functional regulatory pattern with regard to not only their biological functions but also their specific target genes in childhood ALL cancer progression. Taken together, our findings could contribute to a better understanding of the important regulatory mechanisms and this method could be used to analyse the targeted genes at the post-translational level in childhood ALL through integrative network analysis.

1997 ◽  
Vol 76 (12) ◽  
pp. 1550-1553 ◽  
Author(s):  
E Moerland ◽  
MH Breuning ◽  
CJ Cornelisse ◽  
AM Cleton-Jansen

2002 ◽  
Vol 31 (4) ◽  
pp. 414-418 ◽  
Author(s):  
S. Kannan ◽  
H. Yokozaki ◽  
K. Jayasree ◽  
P. Sebastian ◽  
A. Mathews ◽  
...  

2012 ◽  
Vol 10 (01) ◽  
pp. 1240007 ◽  
Author(s):  
CHENGCHENG SHEN ◽  
YING LIU

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.


1995 ◽  
pp. 209-222
Author(s):  
Miguel A. Piris ◽  
Juan C. Martinez ◽  
Margarita Sanchez-Beato ◽  
Juan F. Garcia ◽  
Carmen Bellas ◽  
...  

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