Research Projects

Acute Myeloid Leukemia (AML) is an aggressive and heterogeneous blood cancer with poor prognosis, largely due to chemoresistance to standard drug treatment like Cytarabine. This drug resistance is driven by leukemic stem cell (LSC) diversity and protective signals from the tumor microenvironment (TME). Tumor Necrosis Factor alpha (TNFa), a cytokine abundant in the TME, promotes LSC survival through constitutive activation of NFκB signaling, which regulates key cellular processes like apoptosis, necroptosis, and hematopoiesis. NFκB activation, observed in 40% of AML patients, enhances anti-apoptotic pathways and contributes to treatment failure. Receptor Interacting Protein Kinase 1 (RIPK1) serves as a critical switch in TNFa signaling, capable of promoting apoptosis or necroptosis. Despite growing evidence of crosstalk between these cell death pathways, the precise role of RIPK1 in modulating these responses in AML remains unclear. Moreover, AML cells exhibit significant single-cell variability in their responses to TNFa, complicating treatment strategies. The primary goal of this proposal is to unravel the signaling crosstalk between pathways involving RIPK1 that regulates TNFa-induced signaling toward the three phenotypic responses, namely, pro-survival, apoptotic, or necroptotic outcomes in AML cells, with and without chemoresistance, while accounting for inherent cell-to-cell variability. Specifically, systems biology single-cell experimental data constrained network modelling and simulations will be employed to distil out the underlying intracellular mechanisms that guide the signal flow towards different phenotypic responses in regular and chemoresistant AML tissue in the presence of heterogeneities. The proposed approach will involve high-throughput single-cell experimentation for both phenotypic and intracellular level detection, and use of these in the Boolean dynamic simulations of a manually curated Boolean dynamic model of the TNFR1 signal transduction in AML cells. The thus arrived at mechanisms will be systematically analysed using a combination of experimental measurements and the model simulations to identify target nodes and interactions which may be modulated to facilitate ensemble-level cellular phenotypic switching towards cell-death. Insights from this work on how to modulate the identified targets could help arriving at novel therapeutic approaches to sensitize resistant AML cells to cell death and improve clinical outcomes.