Abstract 5626: Multiomic spatial profiling of the tumor immune microenvironment at single cell resolution

• Published in: Cancer research (Chicago, Ill.) Ill.), 2023-04, Vol.83 (7_Supplement), p.5626-5626
• Main Authors: Jhaveri, Niyati, Ji, HaYeun, Dikshit, Anushka, Yuan, Jessica, Doolittle, Emerald, Zhou, Steve, Srinivasan, Maithreyan, Cheikh, Bassem B., Schneider, Fabian, Mansfield, James, Kennedy-Darling, Julia, Braubach, Oliver
• Format: Article
• Language: English
• ISSN: 1538-7445; 1538-7445
• DOI: 10.1158/1538-7445.AM2023-5626

Background: It has been well established that the tumor microenvironment (TME), which comprises cancer cells, stromal cells, and surrounding extracellular matrix, plays a critical role in cancer development, progression, and control. The immunological components within tumors, known as the tumor immune microenvironment (TiME), have also been implicated in tumor development, recurrence, and metastasis. Effective strategies for cancer immunotherapies will require a deep understanding of the factors that shape both the TME and TiME. Here, we describe a spatial multiomics approach that utilizes RNAscope™ ISH technology paired with high-plex whole-slide spatial phenotyping with the PhenoCycler™-Fusion platform. This two-step approach is compatible with human FFPE tissues and enables researchers to characterize the spatial biology of the TiME more accurately by detecting RNA and protein markers on serial sections. The resulting multiomic data more accurately reveal the interplay between TME and TiME by giving insight into cell lineages, surrounding structures, as well as secreted chemokines and cytokines that exist within the TME ecosystem. Methods: We performed ultrahigh-plex spatial phenotyping on the PhenoCycler-Fusion on FFPE tumor tissue sections, using an antibody panel that is designed for immune cell phenotyping, evaluation of immune contexture and proliferation across the TME. Using serial sections from the same tissue blocks, we then ran the RNAscope HiPlex v2 assay automated on the PhenoCycler-Fusion system. This assay consisted of a 12-plex immuno-oncology panel of RNA target probes, which were selected to detect macrophages, chemokines, and cytokines within tumors. We used Phenoplex software to analyze the protein and RNA datasets and to compute cell phenotypes and spatial associations. Results and Conclusions: In this proof-of-concept study, we demonstrate the utility of multiomic spatial profiling on the PhenoCycler-Fusion platform. Analysis of the resulting multiplex imaging data not only revealed the structural organization of cells within the TME, but also activation states of immune cells. Together, this information provides a more complete functional map of immune cells within the TME and TiME and thereby enriches our understanding of tumor biology that may be deterministic of immunotherapy responsiveness. This work paves the way for future research that will rely on deep spatial phenotyping with protein biomarkers coupled with accurate quant