Authors: Carla Coltharp, Yi Zheng, Kristin Roman, Rachel Schaefer, Ryan Dilworth, Wenliang Zhang, Kent Johnson, Chi Wang, Linying Liu, Cliff Hoyt, Peter Miller

Issue: SITC 2018 Tradeshow Poster


We describe two advances in multispectral fluorescence immunohistochemistry (fIHC), a powerful tool for quantifying interactions within the tumor microenvironment.

  1. A fully-automated 8-plex, 9-color assay plus DAPI counterstain on the same tissue section
  2. A novel scanning method that produces a multispectral whole slide scan of 6 markers plus DAPI counterstain in ~6 minutes (1x1.5 cm tissue section)


FFPE samples of primary tumors were immunostained using Opal™ reagents manually or on a Leica BOND RX™. Imagery was acquired on a Vectra Polaris® automated imaging system and analyzed with inForm®, MATLAB®, and R software.

Multiplex Staining with Opal™ Reagents

Fig 1. Opal™ Detection. The Opal Polymer HRP amplifies IHC detection by covalently depositing multiple Opal fluorophores near the detected antigen. Then, antibodies are stripped to allow for sequential labeling of multiple markers.

Multispectral Imaging on Vectra Polaris®

Fig. 2. Multispectral imaging on the Vectra Polaris is built upon an epifluorescence light path (below, left). Different combinations of agile LED bands, bandpass excitation filters, bandpass emission filters, and a liquid crystal tunable filter (LCTF) are used to select narrow spectral bands that reach the imaging sensor.

For each spectral band, an image is acquired and added to a ‘data cube’ that contains up to 40 spectral layers (above, right). The data from all spectral layers is then linearly unmixed using previously-determined pure emission spectra for each fluorophore using inForm® software. Intensity values in the resulting ‘unmixed’ image are directly related to the amount of each dye present.

Results: 9-Color Multispectral Imaging

Field-based multispectral imaging workflows can accommodate a wide range of fluorophores and up to 9 colors, but can be time consuming as they require up to 50 spectral layers to unmix 9 fluorophores, and often require exposure times in the hundreds of milliseconds.

We have developed complementary highthroughput multispectral scanning approach by optimizing a multispectral workflow for a specific set of 7 fluorophores.

High-throughput multispectral scanning and unmixing performed comparably to field-based multispectral imaging, and outperformed conventional scanning by:

  • Reducing autofluorescence contributions for all immune markers, lowering the limit of detection and extending the dynamic range of some channels by more than 30-fold.
  • Reducing crosstalk from more than 8% to under 3% (typically <0.5%), thereby increasing signal accuracy and reducing false colocalization between non-colocalized markers.

Fig 6. Cell density and interaction density across the whole slide.
A) Whole slide MSI of human lung cancer section captured in 6 minutes, shown as composite image with marker colors indicated in key. Cells were phenotyped in inForm®, and interactions assessed with R and phenoptr. (Bottom) Zoomed in views of A) illustrate differences in CD8+ T-cell (yellow) infiltration within the tissue.

B) Density contours of CK+ (left), CD8+ (middle), and CK+ within 30 µm of a CD8+ cell (right).


We introduce a 9-color fIHC assay that distinguishes 8 markers plus DAPI counterstain on the same tissue section, increasing the depth of cellular interactions that can be studied within the tumor microenvironment.

Additionally, we introduce a whole slide multispectral imaging method that provides rich quantitation of interactions among 6 markers at length scales spanning from cell biology to tumor physiology.

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