MAPTor-NET: MAPK-mTOR network model driven individualized therapies of pancreatic neuro-endocrine tumors (pNETs)
Pancreatic NET (pNET) comprise the most prominent subgroup group of rare Neuroendocrine tumors (NET) with distinct prognostic classes, and thus diverse therapeutic regimens. Available pNET treatments include somatostatin analogs, systemic chemotherapy, and novel molecular drugs targeting receptor tyrosine kinases (Sunitinib), or the mTOR pathway (Everolimus). However, tumor heterogeneity results in an unpredictable response to the therapy, and only a limited number of patients profits from either treatment. To date, no method for diagnostic stratification of patients exists.
The MAPTor-Net consortium suggests a focused systems medicine approach that uses clinical and pathological data together with mutation/expression profiles to individually preselect patients prior to therapy. The approach uses a combination of top-down modeling of the core pathways altered in pNET, and a bottom-up approach gathering and integrating individual molecular data. For patient-specific model setup and parameterization, genetically manipulated experimental systems, closely reflecting the observed clinical situation, will be employed. The effects of therapeutic interferences will be measured under different mutational, patient/tumor specific conditions. These data will serve as a basis for primary and improved mathematical modeling of the underlying signaling network. Thus, MAPTor-NET will test and improve the predictive power of dynamic computational models by accounting for the patient-specific genetic background. Initially focusing on pNETs, the MAPTor-NET strategy can be extended to many further tumor entities as they are driven by similar pathway alterations.
Subprojects in MAPTor-NET:
SP PL Analysis of therapy response in patients and cell lines with specific mutation profiles
SP 1 mTOR Signaling analysis and proteomic approaches
SP 2 Mathematical large-scale modelling of signaling pathways in pancreatic neuroendocrine tumors (pNET)
SP 3 Analysis of therapy response in patients and cell lines with specific mutation profiles
SP 4 Development and functional characterization of pNET model systems
SP 5 Data analysis, management and integration
Keywords: Modellparameterisierung, PI3K, mTOR, pancreatic neuroendocrine Tumors (pNET), Signalling, mathematische MAPK/PI3K/mTOR Modellierung, Signaltransduktionsnetzwerke, European Neuroendicrine Tumor Society (ENETS), clinical data