Biotechnology and Bioprocess Engineering 2024; 29(6): 1061-1070  
Discovery of anticancer targets for triple-negative breast cancer through comparative analysis of gene dependency score
Bo Kyung Kim 1 · Gahee Kim 2,3 · Wonhee Hur 2 · Yoojin Choi 4 · Suhyun Hwangbo 5 · Jae Yong Ryu 1,6
1 Department of Biotechnology , Duksung Women’s University , Seoul 01369 , Korea
2 Division of Chronic Viral Diseases, Center for Emerging Virus Research , Korea National Institute of Health , Cheongju 363951 , Korea
3 Department of Pharmacy , Chungbuk National University , Cheongju 28644 , Korea
4 Department of Chemistry , Research Institute of Chem-Bio Diagnostic Technology, Chung-Ang University , Seoul 06974 , Korea
5 Department of Genomic Medicine , Seoul National University Hospital , Seoul 03080 , Korea
6 Artifi cial Intelligence Laboratory , Oncocross Co., Ltd , Seoul 04168 , Korea
Correspondence to: ✉ Suhyun Hwangbo
83462@snuh.org

✉ Jae Yong Ryu
jyryu@duksung.ac.kr
Received: March 10, 2024; Revised: July 31, 2024; Accepted: August 2, 2024; Published online: August 14, 2024.
© The Korean Society for Biotechnology and Bioengineering. All rights reserved.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Patients with triple-negative breast cancer (TNBC) often face an unfavorable prognosis due to the lack of targeted therapy. Thus, identifying drug targets specific to the TNBC subtype is crucial for effective treatment. Here, we propose a strategy to identify potential inhibitory targets specific to this subtype based on the gene dependency score (GDS), a quantitative measure of essentiality of each gene determined in cancer cell lines. Specifically, we compared the GDS values of 17,387 genes among cell lines of four breast cancer (BC) subtypes, namely luminal A, luminal B, HER2-positive, and TNBC, to identify genes showing specific essentiality in TNBC subtype cell lines. Twenty-two genes were predicted as potential inhibitory targets. Of these, we selected two genes, ILK and RHOA, based on survival analysis conducted across the four BC subtypes. We propose these two genes as potential biomarkers for TNBC. Furthermore, we experimentally validated that inhibiting ILK expression with a specific inhibitor reduced cell viability more in TNBC subtype cell lines than in other BC subtype cell lines. Therefore, ILK is a potential drug target specific to TNBC. The strategy proposed is expected to be useful in identifying biomarker and therapeutic target genes in not only BC but also other cancers.
Keywords: Triple-negative breast cancer · Gene dependency score · Target discovery · Biomarker

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