Dynamics of the microbiome in pancreatic cancer from inception to invasion
by Nina Pfisterer
Date of Examination:2023-09-11
Date of issue:2023-10-23
Advisor:Prof. Dr. Dr. Albrecht Neeße
Referee:Prof. Dr. Dr. Albrecht Neeße
Referee:Prof. Dr. Matthias Dobbelstein
Persistent Address:
http://dx.doi.org/10.53846/goediss-10152
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Abstract
English
Recently, the microbiome was associated with hallmark features of pancreatic ductal adenocarcinoma (PDAC). This dismal human disease with one of the lowest survival rates of below 10% is characterized by clinical challenges such as unspecific symptoms, lack of biomarkers, late diagnosis, refractoriness against systemic therapies, and a high recurrence rate after surgery. The biology behind these difficulties has been approached in multiple ways, for instance by tackling the pronounced desmoplastic stroma or investigating chemotherapy-inactivating enzymes. To date, no significant progress with clinical usage was made. After being long known for its impact on a plethora of physiological and pathophysiological processes, studies of considerable impact have lately demonstrated the microbiome to be involved in all kinds of aspects of various cancer types. Moreover, the discovery of tumors and healthy organs to harbor differential microbiota was groundbreaking. These findings were also and most notably shown in PDAC. Being one of the deadliest cancers, PDAC would benefit immensely from systematic, reliable microbiome research. Being convinced that third generation sequencing is the most effective technology for precise and reproducible microbiome studies, a sequencing platform by Oxford Nanopore Technologies (ONT) together with a comprehensive workflow for DNA extraction, library preparation and bioinformatic analysis was established as a major project within the scope of this thesis. This comprised testing seven different DNA isolation protocols and benchmarking several other parameters. Further, the pipeline was optimized for murine high (feces) and low microbial biomass (pancreatic) samples. Ensuing successful establishment of ONT sequencing, the presence of bacterial material in murine KPC tumor and human PDAC tissue was shown via IHC targeting lipopolysaccharide and FISH targeting the 16s rRNA gene. The occurrence of both components was visualized and, for KPC tumors, also quantified demonstrating a significantly higher abundance in diseased tissue as compared to healthy controls. The characterization of the fecal microbiome at various time points during disease progression as well as the end stage tumor microbiome in the KPC mouse model via ONT sequencing impressively showed significant differences in beta diversity metrics compared to their healthy counterparts. Furthermore, the similarity with recently published human stool and PDAC microbiomes could be ascertained via regression models. Finally, first experiments involving FFPE tissue material as most commonly available sample source in the clinical setting were performed aiming at evaluating the impact of PDAC subtypes on their intratumoral microbiomes. Therefore, samples from tumors derived from orthotopically transplanted human PDAC cell lines of the classical and basal-like subtype, as well as xenografted classical tumors treated with TNFα causing lineage reprogramming, and resected human PDAC which was subtyped via IHC were employed. In the course of these experiments, contamination issues were encountered and are explicitly discussed in the following. The results were not as conclusive as the KPC data, however, first evidence for the PDAC subtype to impinge on the microbiome is given. Taken together, new sequencing technology by ONT was installed in a customized way, distinct local microbiomes of the KPC model were characterized and found to be similar to the situation in humans, and PDAC subtypes seem to influence the microbiome.
Keywords: pancreatic ductal adenocarcinoma; PDAC; pancreas; tumor; KPC mouse model; microbiome; orthotopic transplantation; Oxford Nanopore Technologies; ONT sequencing; third generation sequencing; alpha diversity; beta diversity; cell lines; feces; subtypes; 16S rRNA
