Genomic and transcriptomic signatures of inflammation and malignancy in the intestinal tract
Cancer is one of the main causes of death in industrialized countries. A better understanding of genomic mechanisms underlying tumor development would create novel treatment possibilities. In the present study, methods based on next-generation sequencing (NGS) were employed to analyze the molecular background of two gastrointestinal cancer types. The first part of my studies aimed to decipher novel molecular insights into gastric cancer (GC). Therefore, two exemplary human GC samples and the surrounding control tissues were investigated with whole exome and whole genome sequencing at high resolution. To identify relevant molecular features with this small sample number, a novel approach using two different NGS technologies and population based resources was suggested. In the second part of my studies, the AOM/DSS mouse model, which is a well-established model for the investigation of human colitis-associated colorectal cancer (CAC), was characterized with an integrative analysis based on whole exome and transcriptome data. Thereby, samples from different tumor stages were compared with tumor-free colonic tissue samples from mice exposed to AOM/DSS, with formerly inflamed colonic tissue samples from mice exposed to DSS only, and with colonic controls from untreated mice. While most of the observed molecular features reflected human CAC, also critical molecular differences were revealed. This knowledge should be taken into consideration when using AOM/DSS-induced cancer as model for human CAC. As part of my studies, I developed novel bioinformatic tools and pipelines, including a program for the detection and characterization of novel transcriptionally active regions. Taken together, my studies further emphasize the power of investigating cancer pathophysiology via NGS in individual clinical settings and in experimental animal models. The reported results are an important step towards the development of novel treatment and diagnostic approaches.
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