AUTHOR=Beklen Hande , Gulfidan Gizem , Arga Kazim Yalcin , Mardinoglu Adil , Turanli Beste 

TITLE=Drug Repositioning for P-Glycoprotein Mediated Co-Expression Networks in Colorectal Cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 10 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.01273

DOI=10.3389/fonc.2020.01273

ISSN=2234-943X

ABSTRACT=Colorectal cancer (CRC) is one of the most fatal types of cancers which is seen in both men and women. CRC is the third most common type of cancer in worldwide. Over the years several drugs are developed for treatment of CRC, however, the patients with advanced CRC can be resistant to some drugs. P-glycoprotein (P-gp) (also known as Multidrug Resistance 1, MDR1) is a well-identified membrane transporter protein expressed by ABCB1 gene. The high expression of MDR1 protein found in several cancer types causes chemotherapy failure due to efflux drug molecules out of the cancer cell, decreases the drug concentration and causes drug resistance. As same as other cancers, drug-resistant colorectal cancer is one of the major obstacles for effective therapy and novel therapeutic strategies are urgently needed. Network-based approaches can be used to determine specific biomarkers, potential drug targets or repurposing approved drugs in drug-resistant cancers. Drug repositioning is the approach for using existing drugs for the new therapeutic purpose, it is highly efficient process and low cost. To improve current understanding of the MDR-1 related drug resistance in colorectal cancer, we explored gene co-expression networks around MDR-1 protein with different network size (50,100,150,200 edges) and repurposed candidate drugs targeting to MDR1 protein and its co-expression network by using drug repositioning approach for treatment of colorectal cancer. The candidate drugs were also assessed by using molecular docking for determining potential of physical interactions between drug and MDR1 protein as a drug target. We also evaluated these four networks whether they are diagnostic or prognostic features in CRC besides biological function determined by functional enrichment analysis. Lastly, differentially expressed genes of drug-resistant (i.e. oxoplatin, methotrexate, SN38) HT29 cell lines were found and used for repurposing drugs with reversal gene expressions. As a result, it is shown that all networks were exhibited high diagnostic and prognostic performance besides the identification of various drug candidates for drug-resistant patients with CRC. All these results can shed light on the development of effective diagnosis, prognosis, and treatment strategies for drug resistance in CRC.