Open Access
ARTICLE
Comprehensive Network Analysis of Different Subtypes of Molecular Disorders in Lung Cancer
Haoliang Zhang1,*, Xiaowei Xing2, Yang Liu1, Shuangli Li1, Weiyuan Li3
1 Department of Oncology, Tangshan Workers’ Hospital, Tangshan, China
2 Department of Cardiovascular Internal Medicine, Tangshan, China
3 Graduate School of North China Institute of Technology, Tangshan, China
* Corresponding Author: Haoliang Zhang. Email:
Oncologie 2020, 22(2), 107-116. https://doi.org/10.32604/oncologie.2020.012494
Abstract
Lung cancer is the leading cause of death in cancer patients. Based on
a modular and comprehensive analysis method, it is intended to identify their
common pathogenesis. We downloaded data and analyzed differences in lung
adenocarcinoma samples, lung squamous cell carcinoma samples, and normal
samples. Co-expression analysis, enrichment analysis, and hypergeometric testing
were used to predict transcription factors, ncRNAs, and retrospective target genes.
We get 4596 differentially expressed genes in common differences in high
multiples and clustered into 14 modules dysfunction. The 14 genes (including
DOK2, COL5A1, and TSPAN8) have the highest connectivity in the dysfunction
module and are identified as the core genes of the module. Module genes are also
substantially involved in biological processes, including extracellular matrix,
carbohydrate-binding and renal system development, and involved signal
transduction including PPAR signal transduction, cGMP-PKG signal transduction,
PI3K-Akt signal transduction, and Apelin signal transduction. We identified
ncRNA pivot (miR-335-5p, ANCR, TUG1) and Transcription Factors pivot
(RELA, SP1) to regulate dysfunction module genes primarily. The analysis
showed that comprehensive co-expression analysis helped us to understand the
transcription factor ncRNA. Moreover, it helps us understand the molecular
pathogenesis of co-expression of modular genes that regulate lung
adenocarcinoma and squamous cell carcinoma. It provides a precious resource and
theoretical basis for further experiments by biologists.
Keywords
Cite This Article
Zhang, H., Xing, X., Liu, Y., Li, S., Li, W. (2020). Comprehensive Network Analysis of Different Subtypes of Molecular Disorders in Lung Cancer.
Oncologie, 22(2), 107–116.
Citations