Dissecting the Tumor Microenvironment (TME) to Decipher New Immunotherapy Targets by Using Artificial Intelligence

Cancer remains one of the leading causes of death worldwide, second only to cardiovascular diseases. Standard cancer treatments, such as chemotherapy, radiation, and surgery, are effective for primary tumors but often fail to eliminate disseminated tumor cells responsible for metastasis. This limitation underscores the necessity for advanced therapeutic strategies, leading to the rise of immunotherapy, which leverages the immune system to combat cancer. Despite its promise, immunotherapy faces challenges, including variable patient responses and immune-related toxicities, complicating the prediction of treatment efficacy. Here, artificial intelligence (AI) emerges as a vital tool that can enhance the precision and effectiveness of immunotherapy by analyzing the intricate tumor microenvironment (TME). This paper explores the limitations of current immunotherapies and examines how AI can address these challenges. It discusses the TME’s role in shaping immune responses, highlighting how understanding its complexities can improve predictive power and treatment outcomes. Furthermore, we address the limitations of AI in cancer research and propose future directions for its integration into clinical practice, with the potential to revolutionize personalized cancer therapy and improve overall patient care.