Researchers have used artificial intelligence to test a biological theory of cancer origins first proposed over 100 years ago. The somatic mutation theory, which posits that cancer begins when a single cell accumulates enough DNA damage to become malignant, has been the dominant model. However, the competing tissue organization field theory suggests cancer is primarily a problem of disrupted cellular communication and tissue architecture. Using AI to analyze vast datasets of genetic and cellular information from both cancerous and healthy tissues, scientists have found evidence supporting aspects of both theories. The AI models identified patterns indicating that while genetic mutations are crucial, the surrounding tissue environment and cell signaling networks play a significant role in whether those mutations lead to cancer. This research suggests a more integrated model of cancer initiation, combining genetic and tissue-level factors. The findings could lead to new approaches in both cancer prevention and early detection strategies. Read the full article at: https://www.sciencedaily.com/releases/2026/03/260309225152.htm