High-plex immunofluorescence imaging and traditional histology of the same tissue section for discovering image-based biomarkers

Sorger and colleagues present Orion, a technique to analyze H & E histology and multiplex immunofluorescence imaging data from the same cells, which they apply to human colorectal cancer samples to identify spatial biomarkers of disease progression. Precision medicine is critically dependent on better methods for diagnosing and staging disease and predicting drug response. Histopathology using hematoxylin and eosin (H & E)-stained tissue (not genomics) remains the primary diagnostic method in cancer. Recently developed highly multiplexed tissue imaging methods promise to enhance research studies and clinical practice with precise, spatially resolved single-cell data. Here, we describe the 'Orion' platform for collecting H & E and high-plex immunofluorescence images from the same cells in a whole-slide format suitable for diagnosis. Using a retrospective cohort of 74 colorectal cancer resections, we show that immunofluorescence and H & E images provide human experts and machine learning algorithms with complementary information that can be used to generate interpretable, multiplexed image-based models predictive of progression-free survival. Combining models of immune infiltration and tumor-intrinsic features achieves a 10- to 20-fold discrimination between rapid and slow (or no) progression, demonstrating the ability of multimodal tissue imaging to generate high-performance biomarkers.

Automated summary

Researchers have developed a technique called Orion, which can analyze H&E histology and multiplex immunofluorescence imaging data from the same cells. They applied this technique to human colorectal cancer samples to identify spatial biomarkers of disease progression. Histopathology using H&E-stained tissue remains the primary diagnostic method in cancer.