Description
Primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of Janus-activated kinase (JAK) / signal transducer and activator of transcription (STAT) signaling pathway. Due to complex non-linear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. To untangle these features, we used dynamic pathway modeling that employs model development and calibration based on extensive quantitative data generation. Quantitative data were collected on JAK/STAT pathway signaling components in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We showed that the amounts of STAT5 and STAT6 are higher whereas the amount of SHP1 is lower in the two lymphoma cell lines compared to B cells from healthy donors. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In our experimental setting interleukin-13 (IL13) stimulation levels remained constant over time. In MedB-1 cells surface IL13 receptor alpha 2 had a strong IL13-sequestering/decoy function. In both lymphoma cell lines we observed IL13-induced activation of interleukin-4 receptor alpha, JAK2 and STAT5, but not of STAT6, which was highly phosphorylated even without stimulus. Furthermore, the known STAT-inducible negative regulators CISH and SOCS3 were up-regulated within 2 hours in MedB-1 but not in L1236 cells. Global transcription profiling revealed 11 early and 16 sustained common genes up-regulated by IL13 in both lymphoma cell lines. Based on this detailed information we established two individual mathematical models, MedB-1 and L1236 model, which were able to describe the respective experimental data. Sensitivity analysis of the model identified six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1 cells. By inhibition of STAT5 phosphorylation we successfully validated one of the predicted targets demonstrating the potential of the approach in guiding target identification for highly deregulated signaling networks in cancer cells. We established mathematical models of the JAK/STAT pathway in two lymphoma cell types (PMBL and cHL), able to reproduce experimental data and to predict possible therapeutic targets.