High-Plex Multiomic Analysis in FFPE Tissue at Single-Cellular and Subcellular Resolution by Spatial Molecular Imaging

Abstract

Spatial Molecular Imager (SMI) is an automated microscope imaging system with microfluidic reagent cycling, for high-plex, spatial in-situ detection of multiomic targets (RNA and protein) on FFPE and other intact samples with subcellular resolution. The key attributes of the CosMx^TM SMI platform (NanoString®, Seattle, WA) include: 1) high-plex and high-sensitivity imaging chemistry that works for both RNA and protein detection, 2) three-dimensional subcellular-resolution image analysis with a target localization accuracy of ∼50 nm in the XY plane, 3) large Hamming-distance encoding scheme with low error rate (0.0092 false calls per cell per gene) and low background (∼ 0.04 counts per cell per gene), 4) high-throughput (up to 1 million cells per sample, four samples per run), 5) antibody-based cell segmentation methods, and 6) compatibility with formalin-fixed, paraffin-embedded (FFPE) samples.

In this study, 980 RNAs and 80 proteins were measured at subcellular resolution in FFPE cultured cell pellets, as well as FFPE tissues from biobanked samples of non-small cell lung cancer (NSCLC) and breast cancer. Cross-platform analysis using 16 cancer cell lines validated high-correlation (R² ∼0.77) and high sensitivity (∼1.44 FPKM/TPM; roughly 1 to 2 copies of RNA per cell) when compared to RNA-seq. Real-world archived NSCLC FFPE tumor sections revealed greater than 94% cell detection efficiency for RNA, despite the low RNA quality QV200 20% to the medium quality 65%. The accuracy of protein expression measurements was independent of the level of multiplexing, as demonstrated by the linear behavior of nested multiplexing panels (R² > 0.9). At 980-plex RNA detection, data analysis allowed identification of over 18 distinct cell types, at least 10 unique tumor microenvironment neighborhoods, and over 100 pairwise ligand-receptor interactions. Data from 8 NSCLC samples comprising over 800,000 single cells and ∼260 million transcripts are released into the public domain (www.nanostring.com) to allow for extended data analysis by the entire spatial biology research community.