Introduction

Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance.We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group.Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.

Publications

  1. Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance.
    Cite this
    Emad A, Cairns J, Kalari KR, Wang L, Sinha S, 2017-08-01 - Genome biology

Credits

  1. Amin Emad
    Developer

    Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, United States of America

  2. Junmei Cairns
    Developer

    Department of Molecular Pharmacology and Experimental Therapeutics, Gonda 19, United States of America

  3. Krishna R Kalari
    Developer

    Department of Health Sciences Research, Mayo Clinic, United States of America

  4. Liewei Wang
    Developer

    Department of Molecular Pharmacology and Experimental Therapeutics, Gonda 19, United States of America

  5. Saurabh Sinha
    Investigator

    Department of Computer Science and Institute of Genomic Biology, University of Illinois at Urbana-Champaign

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Summary
AccessionBT000368
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Submitted BySaurabh Sinha