Abstract
Initiation and progression of cancer depend on many factors. Those on the genetic level are often considered crucial. To gain insight into the physical mechanisms of breast cancer, we construct a gene regulatory network (GRN) which reflects both genetic and environmental aspects of breast cancer. The construction of the GRN is based on available experimental data. Three basins of attraction, representing the normal, premalignant and cancer states respectively, were found on the phenotypic landscape. The progression of breast cancer can be seen as switching transitions between different state basins. We quantified the stabilities and kinetic paths of the three state basins to uncover the biological process of breast cancer formation. The gene expression levels at each state were obtained, which can be tested directly in experiments. Furthermore, by performing global sensitivity analysis on the landscape topography, six key genes (HER2, MDM2, TP53, BRCA1, ATM, CDK2) and four regulations (HER2⊣TP53, CDK2⊣BRCA1, ATM→MDM2, TP53→ATM) were identified as being critical for breast cancer. Interestingly, HER2 and MDM2 are the most popular targets for treating breast cancer. BRCA1 and TP53 are the most important oncogene of breast cancer and tumor suppressor gene, respectively. This further validates the feasibility of our model and the reliability of our prediction results. The regulation ATM→MDM2 has been extensive studied on DNA damage but not on breast cancer. We notice the importance of ATM→MDM2 on breast cancer. Previous studies of breast cancer have often focused on individual genes and the anti-cancer drugs are mainly used to target the individual genes. Our results show that the network-based strategy is more effective on treating breast cancer. The landscape approach serves as a new strategy for analyzing breast cancer on both the genetic and epigenetic levels and can help on designing network based medicine for breast cancer.
Highlights
Cancer is one of the most dangerous and fatal disease at present
This gene regulatory network (GRN) contains the following genes: oncogenes as BRCA1, MDM2, RAS, HER2; tumor suppressor genes as TP53, P21, RB; kinases as CHEK1, CHEK2, AKT1, CDK2, RAF, essential to the maintenance of cell cycle regulations; the transcription factor E2F1; and ATM, ATR, which play critical roles in early signal transduction through cell-cycle checkpoints. This GRN includes the main functional pathways: BRCA1-TP53 for signaling tumor suppression [18]; ATR-CHEK1 vital to the maintenance of genome stability [19]; TP53-P21-RB related to apoptosis [20]; MDM2-TP53 which modulates p53-dependent metabolic regulation [21]; ATM-MDM2-TP53 involved in DNA damage response [22]; ATR-CHEK1 and ATR-TP53 necessary for oxidative stress [23, 24]; ATR-TP53-P21 which responds to DNA damage and pathogenesis of cancers [25]; RB-E2F1 regulating the initiation of DNA replication [26]; HER2-TP53 related to the regulation of telomerase [27]; HER2-P21-AKT whose connection to doi:10.1371/journal.pone.0157422.g001
We constructed a gene regulatory network of breast cancer based on available experimental literatures and database
Summary
Cancer is one of the most dangerous and fatal disease at present. The global cancer mortality increased by 8% from 7.6 million in 2008 to 8.2 million in 2013 [1]. With the high mortality rates of cancer, early diagnosis will be vital for breast cancer survival. Many reports showed that if detected and treated promptly, 5-year relative survival is over 93% for localized breast cancer. 5-year survival will drop to less than 24%, if the cancer has spread to other organs [3]. It is of great importance to diagnose cancer in time for immediate treatment. People often go for therapy when they have already developed latestage cancer. Clinical observations have shown that traditional methods are not efficient at early diagnosis of breast cancer
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