Network motifs and hypermotifs in TGFβ-induced epithelial to mesenchymal transition and metastasis - Sai Bhavani, Gottumukkala; Palanisamy, Anbumathi (Frontiers in Systems Biology, 2023)
Epithelial to Mesenchymal Transition (EMT) is a complex, non-linear, dynamic multistep process which plays an integral role in the development of metastatic cancers. Diverse range of signaling molecules along with their associated pathways were observed to be involved in promoting the process of EMT and cancer metastasis. Transforming Growth Factor - β (TGFβ) through its SMAD dependent and SAMD independent signaling orchestrates numerous regulators that converge on to the key EMT Transcription Factors (TFs). These TFs further govern the phenotypic transition of cancer cells from epithelial to mesenchymal states. This study explores the TGFβ signaling pathway for its unique network architecture towards understanding their information processing role in executing EMT. Two coherent type1 feed forward network motifs regulating the expression of SNAIL and N cadherin were observed. SNAIL which is one of the crucial regulators of EMT links both the C1FFLs leading to a hypermotif (Adler and Medzhitov, 2022) like structure. Systems modelling and analysis of these motifs and hypermotif illustrated several interesting emergent information processing roles of the regulators involved. The known roles of these regulators in literature were found to be highly correlated with the emergent properties observed. The motifs illustrated persistence detection and noise filtration in regulating the expression of SNAIL and N-Cadherin. Along with these system level properties the hypermotif architecture also exhibited temporal expression of GLI, SNAIL, ZEB and N-Cadherin. Further, a hypothetical three layered C1FFL hypermotif was postulated and analyzed. The analysis has revealed various interesting system level properties. However, possible existence of such real biological networks needs further exploration both theoretically and experimentally. Thus, deciphering these network motifs and hypermotifs has provided additional understanding of the complex biological phenomenon such as EMT in cancer metastasis.