Clinical trial data demonstrates how Bio-Techne's spatial biology technology and Nucleai's AI-powered multimodal platforms can identify predictive biomarkers in immunotherapy and targeted therapy-treated melanoma patients.
Bio-Techne Corporation and spatial biology firm Nucleai have presented pivotal data from the SECOMBIT clinical trial at the Society for Immunotherapy of Cancer (SITC) 2025 Annual Meeting. The study, conducted in collaboration with Professor Paolo Ascierto, Full Professor of Oncology at the University of Napoli Federico II and Istituto Nazionale Tumori IRCCS Fondazione Pascale, showcases the significance of spatial biology in translational research by combining, for the first time, an immuno-oncology (IO) multiplex immunofluorescence (mIF) panel with advanced AI-driven multimodal biomarker analysis.
Using the COMET platform (pictured) and a 28-plex mIF panel, researchers profiled 42 pre-treatment biopsies from patients with metastatic melanoma. Nucleai's multimodal spatial operating system integrated high-plex imaging, histopathology, and clinical outcome data to identify distinct immune cell interactions that correlate with progression-free survival (PFS), overall survival (OS), and clinical benefit across three treatment arms incorporating Immune Checkpoint Blockade (ICB).
Key findings
- Arm A (MAPKi → ICB): Immune activation markers such as PD-L1+ CD8 T-cells and ICOS+ CD4 T-cells are linked to better outcomes
- Arm B (ICB → MAPKi): PD-1+ CD8 T-cells in the tumour invasive margin and their interactions with PD-L1+ CD4 T-cells correlated with improved survival
- Arm C (MAPKi → ICB → MAPKi): APC-T-cell interactions in tumour margins associated with better outcomes; macrophage interactions in outer tumour microenvironment (TME) indicated poorer prognosis.
The study shows that where immune cells are located and how they interact within the tumour matters significantly for treatment success. By using AI and spatial biology to map these immune niches, researchers can better predict which patients will benefit from specific therapies moving toward more personalised and effective cancer treatment.
"This study exemplifies how our innovative spatial imaging and analysis workflow can be applied broadly to clinical research to ultimately transform clinical decision-making in immuno-oncology," said Matt McManus, President of the Diagnostics and Spatial Biology Segment at Bio-Techne.
"Our multimodal spatial operating system enables integration of high-plex imaging, data, and clinical information to identify predictive biomarkers in clinical settings," added Avi Veidman, CEO of Nucleai. "This collaboration shows how precision medicine products can become more accurate, explainable, and differentiated when powered by high-plex spatial proteomics – not limited by low-plex or H&E data alone."