A Physical Mechanism and Global Quantification of Breast Cancer

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.

Multiplex Gene Expression Profiling of 16 Target Genes in Neoplastic and Non-Neoplastic Canine Mammary Tissues Using Branched-DNA Assay

“…Thus, it is suggested that the results herein might correlate with existing reports [ 36 , 41 ] where the described presence of mutations could correspond to the lower levels of TP53 in neoplastic tissues found in our study. Moreover, TP53 is known to be a tumor suppressor gene [ 42 ] and, therefore, its lower expression in neoplastic tissues might lead to uncontrolled cellular growth, a fact which corroborates the findings herein. Further studies at mRNA level are worth carrying out to deepen existing knowledge concerning the role of this gene in CMT.…”

Quantification of the Underlying Mechanisms and Relationships Among Cancer, Metastasis, and Differentiation and Development

“…So this path is dominant for Normal to Cancer state transition. Therefore, to prevent cancer formation, this is worthy attention and we have demonstrated the importance of Premalignant state for cancer prevention in our previous work [29].…”

“…To emphasize the characteristics of CSCs, EMT and cancer, a core gene regulatory network motif covers specific genes and micro-RNAs of the three aspects. As shown in Fig.1, MDM2 is an oncogene of cancer, P53 is a well known tumor suppressor gene [29]. ZEB is an EMT activator gene which suppresses the stemness-inhibition of micro-RNA (mir-200) [30].…”

Mesenchymal stem cells over-expressing cxcl12 enhance the radioresistance of the small intestine

“…But for Lv- cxcl12 -MSCs, overproduction of CXCL12 would assist metastasis of CXCR4 + cancer cells, including colorectal cancer cells 39 . Nevertheless, we believe that the potential risks of Lv- cxcl12 -MSCs can be theoretically quantified by identifying the critical elements such as genes or gene regulations responsible for that from the underlying gene regulatory networks by characterizing the Waddington landscapes and biological paths for normal and cancer developments as well as the cancer stem cells under various environmental conditions including epigenetics 40 – 49 . This will be the future work for us to explore.…”