Abstract P54: Information Processing Through Feedback and Feed-Forward Loops in Epithelial–Mesenchymal Transition in Cancer Metastasis

Abstract

Network motifs, such as feedback loops, feed-forward loops (FFLs) and their higher-order arrangements known as hypermotifs, serve as fundamental building blocks that orchestrate cellular decision-making networks in cancer. In the context of Epithelial-Mesenchymal Transition (EMT)—a hallmark of cancer metastasis, these motifs regulate the processing of intracellular and extracellular signals across multiple signalling pathways including TGFβ, Wnt-β-Catenin, SHH, NOTCH and several Receptor Tyrosine Kinases. Central to this regulation are core transcription factors such as SNAIL, ZEB embedded within feed-forward and feedback loops mediated by both SMAD-dependent and SMAD-independent TGFβ pathways. This systems level study explores the role of motifs and hypermotifs observed in EMT regulation through dynamic modelling and analysis. The results illustrated the information processing role of major EMT transcription factor SNAIL along with its system level behaviour. SNIAL which is regulated in a coherent feed-forward loop motif exhibited noise filtering, signal integration, persistence detection, coincidence detection and temporal regulation during EM transition. Feedback loops involving p53 form bistable switches and drive multistable dynamics that underpin phenotypic plasticity and enable transitions among epithelial, hybrid, and mesenchymal states. These findings uncover the coordinated interplay among key regulators (such as p53, SNAIL, ZEB, MDM2, GLI, E-cadherin, N-cadherin, SMADs, miR-200, and miR-34), feedforward loops, and feedback loops in influencing critical decision such as epithelial to mesenchymal transition. This interconnectedness collectively contributes to the dynamic multistable behaviour observed during EMT and consequently metastatic transition. These regulatory modules, acting in concert are responsible for the pathogenic processes of metastasis in many cancer types. The identification of these functional modules presents a potential therapeutic strategy beyond targeting individual regulators. By focusing on disrupting or modulating these critical motifs instead of single regulators, researchers may develop more effective treatments for suppressing metastatic progression in cancer.