What question did this study set out to answer?

To enhance understanding and detection of pancreatic pre-malignant lesions using a multiomic approach.

April 5, 2026

Abstract 2687: First single slide spatially resolved multiomic integration of pancreatic cancer: High-plex proteomic and whole transcriptome analysis.

Key Points

To enhance understanding and detection of pancreatic pre-malignant lesions using a multiomic approach.
Applied high-plex proteomic and whole transcriptome analysis on a tissue microarray.
Utilized spatial transcriptomics to profile molecular landscapes of intraductal papillary mucinous neoplasms (IPMNs).
Implemented a hybrid computational-manual approach for cell type annotation based on RNA and protein data.
Identified 340,069 cells from RNA analysis with a mean of 1,545 transcripts per cell.
Discovered 416,766 cells in protein data with a mean fluorescence intensity of 16,287.
Achieved multiomic integration showing enhanced alignment of proteomic data with RNA annotations.

Abstract

Abstract The increasing prevalence of incidentally diagnosed pre-malignant pancreatic Intraductal Papillary Mucinous Neoplasms (IPMNs), the cost of surveillance and the low rate of progression to cancer, underscores the importance of identifying IPMNs likely to progress to cancer. Currently available imaging and endoscopic tools cannot assess the complexity of IPMNs in their evolution to cancer. Understanding the spatial and molecular heterogeneity of pancreatic pre-malignant lesions is a critical strategy to enhance biological understanding, improve early detection and inform therapeutic strategies. Spatial transcriptomics offers the ability to robustly profile the spatial molecular landscape of IPMNs; however, cell type heterogeneity poses challenges. A same slide multiomic approach, combining high-plex proteomic and transcriptomic profiling, overcomes the limitations of transcriptionally defined cell type heterogeneity while preserving the exploration of cellular functionality through transcriptomic pathway and gene module analysis. A 64 plex protein panel followed by a whole transcriptome RNA panel using CosMx SMI (Bruker) was applied to a Tissue Microarray (TMA) of 40 x 1.5mm cores from patients with pancreatic cancer originating in IPMNs from various histological subtypes. Experimental time was 9 days to first visualisation of the data. From the RNA analysis 340,069 cells were identified with a mean of 1,545 transcripts and 1,157 unique genes per cell. In the protein 416,766 cells were identified, expression analysis demonstrated a mean fluorescence intensity of 16,287. After alignment of the decoded RNA transcripts to the co-ordinates of the protein data there were 412,680 cells across 335 fields of view, enabling multiomic integration within the same tissue regions. The analysis pipeline incorporated three distinct approaches for cell typing: RNA: 33 clusters RNA Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2687.

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