Phenotype Switching during TNFa - TNRF1 Signaling
Published in Nextgen Genomics, Biology, Bioinformatics and Technologies Conference, 2019
Tumor Necrosis Factor alpha (TNFα) is a pleiotropic cytokine involved in phenotypic decisions such as apoptotic/necrotic death, proliferation. Aberrant TNFα signaling is implicated in numerous pathological conditions. Designing therapeutic strategies to modulate these conditions require insights into the mechanisms governing context-specific phenotypic response to TNFα. Signal transduction culminating in such responses is orchestrated by underlying molecular network of nodes interconnected by edges. Using a comprehensive, well-annotated, manually curated TNFαTNFR1 signaling network, we show that a graph-theory based dimensionality reduction via modularization can lead to functionally consistent, conserved modules in the network. We identify 20 candidates which when knocked down one-at-a-time preserves the network’s modularity as well as robustness. Moreover, using information from databases, we further identify cell-type specific interactions in the network. Boolean dynamic simulations of this complex system and attractor analysis of the underlying state transition graph show that targeting BCL-2 and ERK-1/2 can lead to reliable phenotype switching from proliferation to apoptosis. While, knocking-off JNK-1 with LUBAC can result in switching from apoptosis to proliferation. Analysis of tissue-specific network, generated by incorporating the relevant constituent state information, led to prediction of the fraction of an ensemble of cells of MCF7 (breast cancer) and U937 (lymphoma) exhibiting the three distinct phenotypes. These combinations causing phenotype switching maybe considered potential targets for TNFα based therapeutic strategies.
Citation
‘Hrushikesh Loya, Shubhank Sherekar, Sonal Manohar, Sharmila Biswas, Reshma Patil, Ganesh Viswanathan (2019). "Phenotype Switching during TNFa - TNRF1 Signaling; 2019 Sep 30- Oct 2; Mumbai, India</i>.’