Whole genome and transcriptome profilling for cancer biomarker detection via comparison of somatic versus germ/line variants and its bioinformatic analysis

Next Generation Sequencing (NGS) technologies have constituted a turning point toward clinical routine genetic testing of both cancer and rare disease to deliver reliable and high sensitivity results. However, due to the challenges in management of extensive ease of analyse and cost most of NGS testing, somatic sequencing for cancers mostly limited to specific gene(s) or gene regions. Even though, this targeted approach is useful for routine testing, discovering new biomarkers to understand pathogenesis of cancer. The analysis of the entire genomic DNA sequence called as WGS provides the most comprehensive characterization; WGS still cannot be interpreted in clinical level of precision oncology without the transcriptome profiling yet due to the lack of literature and knowledge. In this thesis, we performed both germ-line and somatic WGS and transcriptome sequencing within the Cukurova University AGENTEM (Adana Genetic Diseases Diagnosis and Treatment Center) infrastructure of samples from peripheral blood, FFPE tissue and liquid biopsy in a rare cancer patient, then the comparative bioinformatic analysis. Through this study, we aimed to define an algorithm and implement the bioinformatic analysis via comparing the germ-line and somatic data including the liquid biopsy, FFPE tissue and peripheral blood samples to establish the practices in WGS and transcriptome sequencing data analysis for identifying new biomarker(s) and/or investigating the cancer pathogenesis. Moreover, since there is no such study in literature, this thesis also provides valuable information and workflow for further studies both national and international.