Reorganization in complex landscapes: causes and consequences of changes in meta-food-webs

We lack a thorough understanding of the ecological processes, like species interactions and dispersal, that mediate the ecological responses of whole ecosystems to global changes, and their variability in realistically complex ecosystems. These processes involve multiple interacting species that move freely about the landscapes and thus, understanding these processes demands measures that can account for this complexity, at both the local and landscape scale. I address this issue by combining the local population dynamics of complex food webs and their metacommunity dynamics (yielding so called meta-food-webs). This allows me to incorporate real-world complexity for both local and spatial processes to examine how food webs respond to global changes, focusing on land use changes that alter the spatial configuration of habitats. To delve into the underlying mechanisms governing the impacts of global changes on multitrophic communities in complex landscapes, and to explore variations in these responses among species, trophic groups, landscapes and global change drivers, I develop new theoretical frameworks in which I combine ecology and mathematics. I demonstrate that local and spatial processes mediate meta-food-web responses to global changes in complex landscapes. Specifically, I show that there is a strong trophic dependency in the response of species to land use changes and emphasize that especially (large-bodied) consumer species at high trophic positions have elevated extinction risks when habitat becomes increasingly isolated (research chapters 1 and 2). In research chapter 3, by jointly considering multiple aspects of global change (land use changes and biological invasions), I demonstrate the interdependence of different environmental stressors. Overall, this thesis presents a major step towards a clearer understanding of food web responses to global change impacts

Cancer-Associated Fibroblasts and Tumor Cells in Pancreatic Cancer Microenvironment and Metastasis: Paracrine Regulators, Reciprocation and Exosomes

Pancreatic cancer is currently the fourth leading cause of cancer deaths in the United States, and the overall 5 year survival rate is still only around 10%. Pancreatic cancer exhibits a remarkable resistance to established therapeutic options such as chemotherapy and radiotherapy, in part due to the dense stromal tumor microenvironment, where cancer-associated fibroblasts are the major stromal cell type. Cancer-associated fibroblasts further play a key role in cancer progression, invasion, and metastasis. Cancer-associated fibroblasts communicate with tumor cells, not only through paracrine as well as paracrine-reciprocal signaling regulators but also by way of exosomes. In the current manuscript, we discuss intercellular mediators between cancer-associated fibroblasts and pancreatic cancer cells in a paracrine as well as paracrine-reciprocal manner. Further recent findings on exosomes in pancreatic cancer and metastasis are summarized

Analysis of genomic alterations in cancer associated human pancreatic stellate cells

Pancreatic stellate cells (PSCs) constitute important cells of the pancreatic microenvironment and their close interaction with cancer cells is important in pancreatic cancer. It is currently not known whether PSCs accumulate genetic alterations that contribute to tumor biology. Our aim was to analyze genetic alterations in cancer associated PSCs. PSC DNA was matched to DNA isolated from pancreatic cancer patients’ blood (n = 5) and analyzed by Next-Generation Sequencing (NGS). Bioinformatic analysis was performed using the GATK software and pathogenicity prediction scores. Sanger sequencing was carried out to verify specific genetic alterations in a larger panel of PSCs (n = 50). NGS and GATK analysis identified on average 26 single nucleotide variants in PSC DNA as compared to the matched blood DNA that could be visualized with the Integrative Genomics Viewer. The absence of PDAC driver mutations (KRAS, p53, p16/INK4a, SMAD4) confirmed that PSC isolations were not contaminated with cancer cells. After filtering the variants, using different pathogenicity scores, ten genes were identified (SERPINB2, CNTNAP4, DENND4B, DPP4, FGFBP2, MIGA2, POLE, SNRNP40, TOP2B, and ZDHHC18) in single samples and confirmed by Sanger sequencing. As a proof of concept, functional analysis using control and SERPINB2 knock-out fibroblasts revealed functional effects on growth, migration, and collagen contraction. In conclusion, PSC DNA exhibit a substantial amount of single nucleotide variants that might have functional effects potentially contributing to tumor aggressiveness