An integrative approach towards personalized treatment of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumor types with extremely poor prognosis. The most effective treatment, curative surgery, is only feasible for about 20% of patients with the median survival being limited to approximately 6 months for other approaches. Despite apparent tumor heterogeneity, PDAC is clinically still treated as a single disease. Thus, there is a strong need to both identify novel biomarkers, which facilitate patient stratification according to clinically relevant parameters and to subsequently develop tailored treatment schemes that are more effective against different tumor subtypes.
Within PANC-STRAT, we follow a highly focused and integrated systems medicine approach combining clinical expertise with cancer biology, next generation sequencing and theoretical systems biology.

Workflow of the e:MED PANC-STRAT Project

First, high-throughput sequencing and array-based methylation analysis is performed to establish the complex mutational, transcriptomic and epigenomic landscape of resected PDACs and liver metastases. Second, the same PDACs will be introduced in parallel into a workflow to generate a cohort of orthotopic xenograft models, followed by the isolation and expansion of tumor-initiating cells (PACO). Our previous results show that all three reported PDAC subtypes exist and can be segregated according to the expression of novel biomarkers. Moreover, the personalized PACOs will provide a unique experimental system, in which dynamic, patient matched data can be readily obtained for systems biology based modeling approaches. Third, molecular data sets will be analyzed and drug response pathways computationally modeled to develop novel biomarkers for stratification and identification of efficacious individualized pathway inhibitors as well as predictors for treatment outcome. The work is based on a unique collection of patient cohorts with accompanying clinical and molecular information, which will be used for permanent validation of observed findings.

Subprojects in PANC-STRAT:

SP 1   Clinical sample collection, Tissue workup and Histological evaluation

SP 2   High-Through-Put Data Generation and Integrated Data Analysis

SP 3   Establishment of patient derived xenograft-models and personalized TIC (tumor-initiating cell) cultures and analysis of the PDAC microenvironment

SP 4   Dynamic Systems Biology Models for Pathway and Drug Discovery

SP 5   Preclinical Translation

SP 6   Clinical Validation and Translation

SP 7   Integrated Data and Project Management

Keywords: pancreatic cancer, pancreatic ductal adenocarcinoma, PDAC