Abstract B006: Gridded tissue profiling strategy with digital spatial profiling for unbiased tissue sampling

Abstract

Abstract Characterization of the spatial distribution and abundance of protein and RNAs within a tissue enables deep understanding of biologic systems. The ability to interrogate multiple targets simultaneously from clinical samples enhances the potential for discovery, but has proven to be challenging for formalin fixed paraffin embedded (FFPE) tissue. NanoString Technologies® has developed the Digital Spatial Profiling (DSP) platform to enable highly multiplexed profiling of protein or RNA from FFPE tissue using a non-destructive protocol. This technology can be used to quantify the abundance of targets within user-defined regions of interest (ROI) using a variety of masking strategies to select and define those regions, including geometric, phenotypic, or automatically generated masks based on expression of certain markers within the tissue. The current technology is capable of profiling dozens of targets, and future iterations could enable hundreds or thousands of targets to be profiled simultaneously. Controlling ROI size, shape, and features defines the heterogeneity and granularity of the information generated. To date, studies on the DSP have largely focused on profiling regions of interest in a nonsystematic way. However, profiling a tissue in a gridded fashion enables a uniform sampling of protein expression either across a whole tissue section or within a smaller area of the tissue to enable nonbiased evaluation, which may aid in biomarker discovery. This study utilizes DSP and a gridded ROI selection strategy to profile protein distribution within normal and tumor tissue. FFPE tissue from tonsil or colorectal tumors are stained with a 44-plex cocktail of antibodies conjugated to unique DNA oligos via a photocleavable linker and up to 3 fluorescent antibodies. Visual images of the tissue are collected with the fluorescent antibodies, and selected regions of interest are subsequently illuminated with UV light to release the oligos for collection. ROIs are profiled serially and captured oligos are then quantitated in the standard NanoString assay. In this study, tonsil and colorectal cancer (CRC) tissue is profiled on the DSP platform using a gridded ROI selection strategy to collect protein profiles from an entire tissue section either via low-resolution sampling or from specific regions within the tissue via high-resolution sampling. Low-resolution sampling of the tissue provides an estimate of the protein distribution across a section of tonsil or CRC. It further enables identification of regions of interest within the tumor suitable for deeper profiling with the high-resolution approach. The higher resolution profiling enables reconstruction of the tissue morphology at the molecular level by looking solely at the distribution of proteins. A distinct protein profiles for the germinal centers and T-cell zones within lymph nodes. Furthermore, we see variations emerges of protein expression between different lymph nodes that may contribute to different biologic functionality. Similarly, in CRC tissue, we see protein profiles that distribute uniquely between the tumor and the tumor microenvironment. For example, there is highly localized expression of immune cell type markers in particular, discrete regions of the tissue rather than distributed throughout the tumor microenvironment, and strong expression of pathways know to be involved in tumor growth/progression distributed to tumor-rich region of the tissue. Furthermore, there appears to be expression of select immune checkpoint molecules (e.g., PD-L1 and TIM3) in regions of the tissue that are predominantly tumor. Whether this represents tumor infiltration by immune cells or aberrant expression of the checkpoint molecules remains to be determined. These results demonstrate the utility of a gridded ROI selection strategy for deep profiling of tissue in an unbiased way to interrogate the immune biology within FFPE tissue using the NanoString DSP platform. Citation Format: Sarah Church, Chris Merritt, Giang Ong, Andrew White, Kristi Zevin, Sarah Warren, Joseph M. Beechem. Gridded tissue profiling strategy with digital spatial profiling for unbiased tissue sampling [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B006.