Consensus Molecular Subtyping of Pancreatic Ductal Adenocarcinoma and Tumor-intrinsic Regulatory Network Inference from Deconvolved Gene Expression Profiles

Project: ResearchGRF

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Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases among major malignancies, with only six-month overall survival from diagnosis. Due to limited response to adjuvant chemotherapies, surgical excision provides the best chance for longer survival. Local and distal recurrence, however, are found in 80% patients after surgery, precluding curative resection in more advanced disease. At present clinical, radiological, and pathological data are used for decision-making, but these characteristics are insufficient to identify clinically relevant subgroups. Furthermore, genetic analysis of PDAC intertumor heterogeneity has identified many genetic alterations, but relatively few consistent driver genes. How to stratify PDAC patients into molecularly distinct subgroups, in relation to clinical outcomes, is critical for selection of patients for optimized adjuvant therapies and design of targeted agents. Gene expression-based subtyping has been widely accepted as a relevant source of disease stratification. Four major classification systems for PDAC have been reported in the literature, demonstrating that similar to many other types of cancers PDAC is not a single disease. Our recent work on in-house-generated RNA-Seq data for 90 stage II PDAC patients also identified 4 molecularly distinct subtypes (PDACS1-4). More specifically, PDACS1 and PDACS4 are both enriched for diabetes mellitus (DM) as shown by the increased expression of b-cell and insulin secretion signatures. However, PDACS4 shows higher immune activities, which explains its better overall survival than PDACS1. PDACS2 shows dysregulation of various metabolism programs, mitochondrion-related pathways, DNA repair and MYC- and Wnt-pathways. PDACS3, with the poorest overall survival, is characterized by upregulation of epithelial-to-mesenchymal transition, cell migration, TGF-b1 signaling, stroma infiltration, as well as highly expressed PD-L1 and PD-L2 genes. Despite these various molecular subtyping effort, its translational potential is hampered by discrepant results, which are probably due to differences in bioinformatic algorithms, diverse discovery cohorts, sample preparation methods and gene expression platforms. Of utmost importance is to elucidate the interrelations between the five PDAC taxonomies, including ours, and define common disease patterns (or consensus molecular subtypes, CMSs) in a principled, unbiased manner, which is our 1st objective in the proposal. Through integrative analysis of multi-omic data and clinical information for ~1500 PDAC samples, our 2nd objective is to comprehensively characterize identified CMSs. Focusing on the poor prognosis subtype, our 3rd objective is to dissect tumor-intrinsic regulatory mechanism based on network inference from deconvolved gene expression profiles, and subsequently to prioritize master regulators for experimental validation by our collaborators at the University of Amsterdam. ?


Effective start/end date1/01/18 → …