Recent collaborations, such as between Mount Sinai's OCCAM Immune and the Cancer Research Institute, are focusing on longitudinal immune monitoring in clinical trials, notably starting with studies in platinum-resistant ovarian cancer. These efforts use advanced RNA/DNA sequencing and immune cell mapping to better match patients to effective immunotherapies and identify predictive biomarkers3.
High-dimensional immune profiling strategies are being leveraged to enhance prediction and monitoring in early immuno-oncology trials. Techniques like integrated single-cell and spatial proteomics, along with mass cytometry, are uncovering functional cellular states and providing insights into response dynamics. These methods have demonstrated improved outcomes in checkpoint immunotherapy response prediction, particularly in lung cancer5.
AI and digital tools are playing an expanding role in immune profiling by sharpening target identification, accelerating drug discovery, and optimizing trial design and validation, further enabling precision medicine in immuno-oncology1.
Recent conference presentations and case studies have shown how spatial profiling of the tumor microenvironment using imaging mass cytometry can unravel metabolic reprogramming and cell signaling in cancer, highlighting the translational impact of multi-omic approaches for understanding therapeutic mechanisms and resistance5.
The increasing complexity and volume of immune data (‘the data deluge’) is being addressed through new analytical platforms and collaborative academic-industry frameworks, aiming to deliver actionable insights that can improve clinical trial outcomes and ultimately, patient care35.
Sources:
1. https://www.cancerresearch.org/blog/immuno-oncology-2025-expert-panel
3. https://www.mountsinai.org/about/newsroom/2025/mount-sinai-and-cancer-research-institute-team-up-to-improve-patient-outcomes-in-immunotherapy