The precision of cancer immunotherapy is critically dependent on accurately characterizing the tumor immune microenvironment (TIME), which represents a complex interplay of cellular components, cytokines, and metabolic factors. Traditional diagnostic methods have been limited in resolving the dynamic molecular interactions within the TIME at a microscale level. This review focuses on recent advancements in microscale measurements for identifying novel immune-oncology biomarkers and therapeutic targets within the TIME, emphasizing the importance of high-fidelity data on tumor immune infiltrates and the significance of longitudinal high-dimensional analysis for predicting treatment responses. Furthermore, the review discusses the impact of cancer metabolic reprogramming on the TIME and the potential of new biomarkers for predicting responses to immunotherapy. The role of nanotechnology in enhancing the detection of immune checkpoints and the development of AI-based sensors for real-time data analysis and predictive modeling is also explored, highlighting the potential of these advanced technologies to revolutionize the field of cancer immunotherapy.