Bilkent University
Department of Computer Engineering


Controlling Metastasis of Triple Negative Breast Cancer with Modeling Regulation Network


Handan Kulan
PhD Student
Computer Engineering Department
Bilkent University

Metastatic breast cancer spreads out-of-reach organs such as bone, brain, liver and lung and is responsible for %90 of breast cancer deaths. Triple Negative Breast Cancer (TNBC) is type of breast cancer which is deficient in estrogen receptor(ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (ErbB2). Patients with TNBC are composed of %15-20 breast cancer incident and have less than one year life span (Sorlie et al. 2003, Dent et al. 2009). Also, TNBC cells metastasizes most frequently to lungs (Foulkes et al. 2010).

Only %3 of human genome codes for proteins and %75 is transcribed into noncoding RNA (ncRNA). This fact shed light on an importance of ncRNA that expressed differently in normal and pathological cases (Djebali et al. 2012) microRNA (miRNA) is 22nt long ncRNA and regulates gene expression post-transcriptionally. Long noncoding RNAs (lncRNA) which are defined as more than 200 nucleotide length and not perform translation is other type of ncRNA. Like miRNA, lncRNAs take role in tumor pathogenesis. In addition, in order that lncRNAs bind miRNAs and act as sponge, they are seen as targets in cancer theraphy(Mercer et al. 2009).

System biology is interdisciplinary approach of determining interaction between biological systems. Although there are a lot of studies that investigate interactions between miRNA-mRNA and miRNA-proteins using system biology approaches (Faraji et al. 2014 and Uhlmann et. al 2012), there are no detailed studies on miRNAs-mRNAs-proteins interactions, especially in the context of metastasis in breast cancer.

The aim of this project is to clarify the role of miRNAs-mRNAs-proteins regulatory network controlling progression in lung metastasis. Firstly, primary tumors were developed by injecting aggressive TNBC cell lines into mice. After collecting primary tumors, 6 weeks were waited for development of metastatic tumors in lungs. After collecting primary and metastatic tumors RNA-seq will be done to identify differentially expressed miRNAs, mRNAs and lncRNAs between primary and metastatic tumors. Using TargetScan (Lewis et al. 2005) and starBase (Li et al. 2014) databases, interaction between miRNAs-mRNAs, miRNAs-lncRNAs and mRNAs-lncRNAs will be determined. These databases help us to delineate the miRNAs-mRNAs-lncRNAs regulatory network controlling metastatic progression in TNBC. Based on this network, we will develop a predictive logical model and perform in silico pertubrations to predict the effects of loss-of-functions of candidate sponge lncRNAs.


DATE: 12 October, 2015, Monday @ 15:40