Analysis of Intra-tumoral Heterogeneity in Context of Tissue Specific Gene Expression with Computational Approach


Thesis Type: Postgraduate

Institution Of The Thesis: Yildiz Technical University, Faculty Of Chemıcal And Metallurgıcal Engıneerıng, Department Of Bioengineering, Turkey

Approval Date: 2018

Thesis Language: English

Student: HATİCE BÜŞRA KONUK

Supervisor: Alper Yılmaz

Abstract:

Identification of tissue-specific genes is essential for understanding molecular mechanisms. Intra-tumoral heterogeneity as diversity among cells and layers of tissues in only one single tumor limits therapeutic efficacy. Tumor heterogeneity is an important challenge for successful personalized medicine. We aimed to identify tissue-specific genes rigorously for examining intersection between differentially expressed genes (DEG) and tissue specific genes, analyzing cancer gene expressions in terms of tissue specificity, demonstration and interpretation of intra-tumoral heterogeneity, revealing specific molecular targets for tumors and elucidating roles of tissue-specific genes in biological processes. Gene expression, derived from five RNA-Sequencing projects, spanning 96 human tissues were used. Detection of tissue-specific genes not only included tau, but also required integrating of tau and statistical distance. This new method is defined as "extended tau". We investigated intersection of 16 different cancer DEG with specifically expressed genes in corresponding tissue. After that, gene expression data for 11 primary solid tumors, retrieved from The Cancer Genome Atlas (TCGA), were analyzed by integrating our tissue specificity findings. Significant genes obtained after all calculations were functionally annotated for identifying their roles. Consequently, we successfully assigned genes to multiple tissues by extended tau. Then discovered that DEG in a cancer tissue has low overlap with genes specific to that tissue. Most importantly, we identified candidate biomarkers for heterogeneity exhibiting gene expression in cancer tissue although its expression is restricted to unrelated tissue. The genes identified in our study were already shown in literature to be associated with tumor heterogeneity or genetic instability of cancer cells for various cancers. Our results are likely to contribute to the road paved by many researchers trying to understand cancer for many years by bringing the tissue-specific genes into the scene.