Immunogradient Indicators for Antitumor Response Assessment by Automated Tumor-Stroma Interface Zone Detection
Allan Rasmusson, Dovile Zilenaite, Ausrine Nestarenkaite, Renaldas Augulis, Aida Laurinaviciene, Valerijus Ostapenko, Tomas Poskus, and Arvydas Laurinavicius
The American Journal of Pathology, Vol. 190, No. 6, June 2020 | DOI: doi.org/10.1016/j.ajpath.2020.01.018
The distribution of tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment provides strong prognostic value, which is increasingly important with the arrival of new immunotherapy modalities. Both visual and image analysisebased assays are developed to assess the immune contextureof the tumors. We propose an automated method based on grid subsampling of microscopy image analysis data to extract the tumor-stroma interface zone (IZ) of controlled width. The IZ is a ranking of tissue areas by their distance to the tumor edge, which is determined by a set of explicit rules. TILdensity profiles across the IZ are used to compute a set of novel immunogradient indicators that reflect TIL gradient towards the tumor. We applied this method on CD8 immunohistochemistry images of surgically excised hormone receptor positive breast and colorectal cancers to predict overall patient survival. In both cohorts, the immunogradient indicators enabled strong and independent prognostic stratification, outperforming clinical and pathologic variables. Patients with breast cancer with low immunogradient levels had a prominent decrease in survival probability 5 years after surgery. Our study provides proof of concept that data-driven, automated, operator-independent IZ sampling enables spatial immune response measurement in the tumor-host interaction frontline for prediction of disease outcomes.
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