Received 4 May 2023, accepted 31 May 2023, date of publication 6 June 2023, date of current version 12 June 2023. Digital Object Identifier 10.1109/ACCESS.2023.3283291 Drug Target Identification in Triple Negative Breast Cancer Stem Cell Pathways: A Computational Study of Gene Regulatory Pathways Using Boolean Networks ADITYA LAHIRI 1 , HASWANTH VUNDAVILLI 1,2 , (Student Member, IEEE), MADHURIMA MONDAL 1 , PRANABESH BHATTACHARJEE 1 , BRIAN DECKER 3 , GIUSEPPE DEL PRIORE 4 , N. PETER REEVES 5 , AND ANIRUDDHA DATTA 1 , (Fellow, IEEE) 1 Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA 2 Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA 3 EMOL Health, Royal Oak, MI 48073, USA 4 Department of Obstetrics and Gynecology, Morehouse School of Medicine, Atlanta, GA 30310, USA 5 Sumaq Life LLC, East Lansing, MI 48823, USA Corresponding author: Aditya Lahiri (adi441994@gmail.com) This work was supported by the U.S. National Science Foundation under Grant ECCS-1917166 and Grant IIP-2136215. ABSTRACT Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer associated with an early age of onset, greater propensity towards metastasis, and poorer clinical outcomes. It accounts for 10% to 20% of newly diagnosed breast cancer cases and disproportionately affects individuals from the African American race. While TNBC is sensitive to chemotherapy, it is also prone to relapse. This is because chemotherapy successfully targets the primary TNBC tumor cell but often fails to target the subpopulation of TNBC stem cells. TNBC stem cells display cancerous traits such as cell cycle progression, survival, proliferation, apoptosis inhibition, and epithelial-mesenchymal transition. To study the cancer initiating behavior of the TNBC stem cells, we studied their underlying signaling pathways using Boolean networks(BN). BNs are effective in capturing the causal interactions taking place in signaling pathways. We built the BN from the pathway literature and used it to evaluate the effcacies of eleven targeted inhibitory drugs in suppressing cancer-promoting genes. We simulated the BN when the pathways had single or multiple mutations, with a maximum of three mutations at a time. Our fndings indicated that STAT3, GLI, and NF-κ B are the most optimal targets for inhibition. These genes are known regulators of the cancer-promoting genes in the pathway,hence our model agrees with the existing biological literature. Therefore inhibiting these three genes has the potential to prevent TNBC relapse. Additionally, our studies found that drug effcacies decreased as mutations increased in the pathway. Furthermore, we noticed that combinations of drugs performed better than single drugs. INDEX TERMS Boolean networks, breast cancer, cancer stem cells, CSC, epithelial to mesenchymal transition, gene regulatory networks, GLI, NF-κ B, STAT3, targeted therapy, TNBC,TNBCSC. I. INTRODUCTION Cancer is the second leading cause of death in the United States and is a major barrier to increasing life expectancy The associate editor coordinating the review of this manuscript and approving it for publication was Taous Meriem Laleg-Kirati . around the world [1], [2], [3]. Breast cancer is now the most frequently diagnosed cancer and is the leading cause of cancer deaths among women around the world [2], [4], [5], [6], [7]. It is estimated that there will be 43,780 deaths due to breast cancer in the United States in 2022 [1]. Breast cancer is not a single disease; instead it is an 56672 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ VOLUME 11, 2023