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Analyzing How Gene Regulatory Networks Influence the Drug Response of Human Cancer Cells

Undergraduate #2
Discipline: Biological Sciences
Subcategory: Cancer Research
Session: 3
Room: Exhibit Hall

Irenosen Aboiralor - POMONA COLLEGE
Co-Author(s): Sheng Wang, Northwestern University, Chicago, ILZhe Ji, Northwestern University, Chicago, IL



The major cause for the failure of cancer chemotherapy is drug resistance. The molecular regulatory mechanisms that control drug resistance have been poorly understood by researchers in this field, thus calling for the development of new methods to identify the key gene regulatory networks aiding in the resistance to certain chemotherapy drugs. Using gene expression modules created by our lab and human cancer cell line data from the Cancer Cell Line Encyclopedia (CCLE), a computational model can be created to dissect the gene networks mediating drug resistance. Identification of such networks will aid in understanding the mechanisms that control drug resistance. For example, a sub-module of gene ontology term GO:0012501 (programmed cell death) containing the hub genes PKP3, SFN, KRT19, and PPL has a significant positive correlation (0.927) with the resistance of the CCLE’s bone cancer cell line to the chemotherapy drug Topotecan. This positive correlation indicates that this gene module is contributing to the sensitivity of the bone cancer cell line to Topotecan. The unbiased computational analysis of this work can help cancer drug developers to understand which gene networks contribute to drug immunity, thus informing their methods to develop novel therapeutic targets.

Funder Acknowledgement(s): Northwestern SROP/EFRI-REM program

Faculty Advisor: Zhe Ji, zhe.ji@northwestern.edu

Role: I conducted the experiment, created the computational models, the poster, and wrote the research paper with the assistance of mentor Sheng Wang.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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