Spatiomolecular Profiling of Human Cancer at Scale

Spatiomolecular Profiling of Human Cancer at Scale The molecular and cellular architecture of a tumor within its tissue environment dictates disease progression and sensitivity to therapy. Therefore, technologies to image and measure the spatial organization of the molecules and cells that form tumors are critical to basic and clinical cancer research. While tumors are routinely evaluated in the clinic using histopathology techniques such as hematoxylin and eosin (H&E) staining, recent technological advances have heralded a revolution in the spatiomolecular analysis of cancer. For example, the development of methods for spatially resolved transcriptomics (ST) have enabled the sequencing of the transcriptome associated with specific areas of tissue sections. The application of ST to cancer research holds the promise to crack the rules governing the structure-function relationships in tumors, but several key challenges in technology must first be overcome. Several ST technologies have emerged from academic labs over the past half a decade, but they remain limited by their low throughput, small surface area, lack of compatibility with H&E staining, and high costs and barriers to adoption. As a result, there is only one ST technology that has spread beyond its institution of origin thanks to commercialization and ease of adoption. Furthermore, the limitations of existing ST methods compound with the issues of standard freeze-sectioning techniques that are prone to section loss and damage and are not compatible with the analysis of large samples, such as surgical resections or whole organs from cancer patients. Therefore, these gaps in ST and histology technologies preclude detailed spatiomolecular analyses for cancer research across many samples, small or large, from cohorts of cancer patients. To address these challenges, we first built a large-format ST profiling platform, Array-seq, by repurposing off-the-shelf DNA microarrays with custom probes into ST-compatible slides. In proof-of-principle experiments, our Array-seq prototype outperformed a widespread commercial ST platform in all metrics tested, including resolution, sensitivity, surface area, and cost. Second, we created a technique for large-format histological sectioning while preserving RNA which, combined with Array-seq slides, enables the spatiomolecular analysis of whole human organs or adult rodents. Here, we propose to develop our Array-seq prototype and histology methods to deliver a scalable, easy-to-adopt, and multimodal ST platform which will enable the high-throughput and cost-effective spatiomolecular analysis of tumors. In addition, we will assess the performance of our spatial technology by applying it to human colorectal cancer, providing a demonstration of the broad applicability of Array-seq for the spatiomolecular characterization of cancer at scale – from whole-organ, human tumors to large patient cohorts. Thus, our technology is poised to contribute to the spatial omics revolution in cancer research by making possible large-scale studies to characterize cancer progression and response to treatment, inform clinical decision- making, or find new therapy avenues. Project Number: 1R33CA297902-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Nicolas Chevrier | Institution: UNIVERSITY OF CHICAGO, CHICAGO, IL | Award Amount: $372,628 | Activity Code: R33 | Study Section: Special Emphasis Panel[ZCA1 TCRB-J (M1)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11200595