Name
Title | ||
|---|---|---|
Identifying functional evolution processes according to the pathological stages of colorectal cancer |
Abstract | ||
|---|---|---|
Colorectal cancer (CRC) is one of the malignant tumors with high morbidity and mortality. A prevalent method for studying colorectal cancer is to identify differentially expressed genes (DEGs) between control and patient samples, followed by the pathway enrichment analyses. However, many of those studies ignore the fact that different pathological stages of the cancer are often highly different from each other. The mixture of those heterogeneous samples may lack the efficiency of identifying the real DEGs, and loss the opportunity to analyze the dynamic evolution process of cancer. In this study, we develop a feasible framework to identify function evolution processes of cancers according to their pathological stages. Firstly, the limma package was used to identify DEG sets between control and CRC stage I, II, III, and IV samples, separately. Secondly, a pathway interaction network was constructed by taking a comprehensive analysis of pathways at individual stages, and a functional module interaction network was also generated independently by clustering genes into modules in a PPI network. The relationship between pathways and modules in adjacent stages was analyzed for all stages of CRC. A total of 479, 313, 349, and 383 DEGs were identified and they were enriched in 17, 16, 20, and 24 pathways, respectively. A functional evolution network was constructed by using those modules, and two significant evolution processes a2-b1-c2-d1 (Mod1) and a1-b2-c1-d2 (Mod2) were identified which may play critical roles in the development of CRC. The framework proposed in this study can be used to explore molecular mechanisms and evolution processes of CRC. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/BIBM47256.2019.8983256 | 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) |
Keywords | Field | DocType |
colorectal cancer,differentially expressed gene,module network,functional evolution process | Computer science,Functional evolution,High morbidity,Pathological,Interaction network,Bioinformatics,Colorectal cancer,Cluster analysis,Functional module,Cancer | Conference |
ISSN | ISBN | Citations |
2156-1125 | 978-1-7281-1868-0 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bolin Chen | 1 | 5 | 2.10 |
| Manting Yang | 2 | 0 | 0.34 |
| Li Gao | 3 | 0 | 1.35 |
| Xuequn Shang | 4 | 99 | 29.07 |