Title Immunogradient indicators for antitumor response assessment by automated tumor-stroma interface zone detection /
Authors Rasmusson, Allan ; Žilėnaitė, Dovilė ; Nestarenkaitė, Aušrinė ; Augulis, Renaldas ; Laurinavičienė, Aida ; Ostapenko, Valerijus ; Poškus, Tomas ; Laurinavičius, Arvydas
DOI 10.1016/j.ajpath.2020.01.018
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Is Part of American journal of pathology.. New York : Elsevier Science Inc. 2020, vol. 190, no. 6, p. 1309-1322.. ISSN 0002-9440. eISSN 1525-2191
Keywords [eng] Immunogradient ; antitumor ; tumor-stroma
Abstract [eng] 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 analysis-based assays are developed to assess the immune contexture of 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. TIL density profiles across the IZ are used to compute a set of novel immunogradient indicators that reflect TIL gradient towards the tumor. We applied the 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.
Published New York : Elsevier Science Inc
Type Journal article
Language English
Publication date 2020
CC license CC license description