# Thesis defence A. Allahyar: cancer

12 November 2018 15:00 - Location: Aula, TU Delft - By: webredactie

Molecular interactomes. Network-guided cancer prognosis prediction & multi-way chromatin interaction analysis. Promotor: Prof.dr.ir. M.J.T. Reinders (EWI).

Our understanding of the molecular mechanisms in cell has witnessed a great leap forward thanks to the recent developments in genomic measurements and computational methods processing the produced massive datasets. A notable example is Network based Outcome Predictors (NOP) that consider the cellular wiring diagram of cell when analyzing gene expression profiles of tumors in cancer patients to predict their prognosis. In this thesis, we introduce FERAL that alleviates several fundamental issues in state-of-the-art NOPs. We furthermore demonstrate that generic biological networks do not contain sufficiently informative interactions and infer a phenotype-specific network called SyNet that govern NOPs to improved performance merely by considering groups of genes in SyNet.

We next show that higher order interactions between functional elements in the cell are relevant in outcome prediction and introduce a novel genomics method called Multi-Contact 4C (MC-4C) to investigate multi-way interactions between functional elements. In contrast to existing methods, MC-4C exploits long-read 3rd generation sequencing technologies and detects higher order interactions that occur in a region of interest at the level of a single allele. Notably using MC-4C, we experimentally confirm a 26 years old hypothesis regarding the looping and co-localization of enhancers in the $\beta$ -globin region in the mouse genome.

Therefore, argue that multi-way interactomes can have a major impact in uncovering the multitude of communications between regulatory sequences and genes in the cell, resulting in a coordinated activity within the cell’s machinery.