Triple-Negative Breast Cancer: A Brief Review About Epidemiology, Risk Factors, Signaling Pathways, Treatment and Role of Artificial Intelligence

• Published in: Frontiers in molecular biosciences Vol. 9; p. 836417
• Main Author: Almansour, Nahlah Makki
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 25-01-2022
• Subjects: artificial intelligence; Molecular Biosciences; prognosis; risk factor; signaling pathways; triple negative breast cancer; triple negative breast cancer; signaling pathways; prognosis; risk factor; artificial intelligence
• ISSN: 2296-889X; 2296-889X
• DOI: 10.3389/fmolb.2022.836417

Triple-negative breast cancer (TNBC) is a kind of breast cancer that lacks estrogen, progesterone, and human epidermal growth factor receptor 2. This cancer is responsible for more than 15-20% of all breast cancers and is of particular research interest as it is therapeutically challenging mainly because of its low response to therapeutics and highly invasive nature. The non-availability of specific treatment options for TNBC is usually managed by conventional therapy, which often leads to relapse. The focus of this review is to provide up-to-date information related to TNBC epidemiology, risk factors, metastasis, different signaling pathways, and the pathways that can be blocked, immune suppressive cells of the TNBC microenvironment, current and investigation therapies, prognosis, and the role of artificial intelligence in TNBC diagnosis. The data presented in this paper may be helpful for researchers working in the field to obtain general and particular information to advance the understanding of TNBC and provide suitable disease management in the future.