Single-section multiplexed imaging enables comprehensive lung cancer diagnosis
Ben-uri, R.; Keidar Haran, T.; Bussi, Y.; Vainer, G.; Arnon, J.; Pillar, N.; Sourikh, H.; Fuchs, I.; Elhanani, O.; Neuman, T.; Pikarsky, E.; Keren, L.
Show abstract
Accurate and timely diagnosis is essential for effective lung cancer treatment. However, contemporary diagnostic workflows rely on sequential immunohistochemistry of small biopsy specimens, which can exhaust limited tissue, compromise diagnostic accuracy, and delay treatment decisions with clinical consequences. Here, we demonstrate that multiplexed imaging overcomes these limitations by enabling comprehensive lung cancer diagnosis from a single tissue section. We developed and validated a clinically informed multiplexed antibody panel that integrates tumor diagnosis and classification, predictive biomarker assessment, and tumor immune profiling. In diagnostic biopsies, multiplexed imaging achieved 96% concordance with standard pathological diagnosis, while enabling accurate automated PD-L1 scoring and rapid detection of clinically approved and emerging actionable targets. This approach preserves scarce tissue, supports quantitative computational analysis to streamline diagnosis, and generates research-grade spatial data while accelerating diagnostic workflow. Together, these findings establish multiplexed imaging as a robust, time and tissue-efficient framework for lung cancer diagnostics that bridges clinical care and translational discovery.
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