Construction and analysis of a breast cancer gene-drug network model.
- Author:
Xing WEI
1
,
2
;
De-Hua HU
;
Min-Han YI
;
Xue-Lian CHANG
;
Wen-Jie ZHU
;
Shao-Ling QU
;
Duan-Ying DENG
Author Information
- Publication Type:Journal Article
- MeSH: Algorithms; Antineoplastic Agents; pharmacology; Breast Neoplasms; genetics; Female; Gene Regulatory Networks; Genes, Neoplasm; Humans; ROC Curve; Reproducibility of Results
- From: Journal of Southern Medical University 2016;36(2):170-179
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo construct a breast cancer gene-drug network model for extracting and predicting the correlations between breast cancer-related genes and drugs.
METHODSWe developed an algorithm based on the ABC principle and the association rules to obtain the correlations between the biological entities. For breast cancer, we constructed 3 different correlations (gene-gene, drug-drug and gene-drug) and used the R language to implement the associated network model. The reliability of the algorithm was verified by ROC curve.
RESULTSWe identified 185 breast cancer-associated genes and 98 associations between them, 97 drugs and 170 associations between them. The breast cancer genes-drugs network contained 127 genes and 77 drugs with 384 associations between them.
CONCLUSIONSWe identified a large number of different correlations between the breast cancer-related genes and drugs and close correlations between some biological entity pairs that have not yet been reported, which may provide a new strategy for experimental design for testing personalized breast cancer treatment.
