![]() Notably, cancer forms an extreme interactive complexity and progresses due to the association of multiple interactions of numerous constituents of cells and tissues (Sonnenschein et al., 2014). The stochastic nature of cancer initiation requires the dynamic approach to endue their non-linear function resulting in the alternation at both genomic and proteomic level (Bizzarri and Cucina, 2014). However, most of these approaches bring little satisfactory results to unfold cancer completely. Different methods such as clonal genetic model, epigenetic model and cancer stem cell model tried to uncover the complicatedness of cancer (Shackleton et al., 2009). Mutation produces chromosomal aberration, genomic and proteomic instability and finally, abnormal proliferation and differentiation. The differential molecular signatures identified from the work can be studied further to understand the cancer signaling process, and potential therapeutic and detection approach.Ĭancer is an abnormal manifestation caused by the process of tumorigenesis due to the mutation in oncogenes and tumor suppressor genes. Cervix and ovarian tissue showed higher increment of the molecular complex number and overlapping module network during cancer in comparison to normal state. Cluster analysis showed that the association of Myc and Cdk4 proteins is very close with other proteins within the network. Number of nodes, edges multi edge node pair, and average number of neighbor are found with significant fluctuations in case of cervix and ovarian tissues. We identified 79 commonly up-regulated and 6 down-regulated proteins in all five tissues. The number of the ranked molecular complex and the nodes involved in the overlapping modules were meaningfully higher in cancer condition. Moreover, molecular complex numbers and overlapping modularization found to be varying significantly between normal and cancerous tissues. Significant differences were observed among different common network parameters between normal and cancer states. Cytoscape platform and related plugins named network analyzer MCODE and ModuLand were used for visualization of complex networks and subsequent analysis. Methods:ĭifferential expression database GeneHub-GEPIS and interaction database STRING were applied for primary data retrieval. From this perspective, differential protein networks (PINs) have been developed based on the expression and interaction data of brain, cervix, lung, ovary and prostate for normal and cancer conditions. Network systems biology (termed NSB) is one of the most recent approaches to understand the unsolved problems of cancer development. Cancer, the disease of intricateness, has remained beyond our complete perception so far. ![]()
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