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Clin Cancer Res. 2018 Sep 10. doi: 10.1158/1078-0432.CCR-18-2013. [Epub ahead of print]

Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer.

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Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, Cleveland, Ohio.
Computer Imaging and Medical Applications Laboratory, Universidad Nacional de Colombia, Bogotá, Colombia.
Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio.
Department of Medicine, University of Athens, Sotiria General Hospital, Athens, Greece.
Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
Department of Pathology-Anatomic, University Hospitals, Cleveland, Ohio.
Hematology and Medical Oncology Department, Cleveland Clinic, Cleveland, Ohio.
Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, Cleveland, Ohio.
Contributed equally


Purpose: The presence of a high degree of tumor-infiltrating lymphocytes (TIL) has been proven to be associated with outcome in patients with non-small cell lung cancer (NSCLC). However, recent evidence indicates that tissue architecture is also prognostic of disease-specific survival and recurrence. We show a set of descriptors (spatial TIL, SpaTIL) that capture density, and spatial colocalization of TILs and tumor cells across digital images that can predict likelihood of recurrence in early-stage NSCLC.Experimental Design: The association between recurrence in early-stage NSCLC and SpaTIL features was explored on 301 patients across four different cohorts. Cohort D1 (n = 70) was used to identify the most prognostic SpaTIL features and to train a classifier to predict the likelihood of recurrence. The classifier performance was evaluated in cohorts D2 (n = 119), D3 (n = 112), and D4 (n = 112). Two pathologists graded each sample of D1 and D2; intraobserver agreement and association between manual grading and likelihood of recurrence were analyzed.Results: SpaTIL was associated with likelihood of recurrence in all test sets (log-rank P < 0.02). A multivariate Cox proportional hazards analysis revealed an HR of 3.08 (95% confidence interval, 2.1-4.5, P = 7.3 × 10-5). In contrast, agreement among expert pathologists using tumor grade was moderate (Kappa = 0.5), and the manual TIL grading was only prognostic for one reader in D2 (P = 8.0 × 10-3).Conclusions: A set of features related to density and spatial architecture of TILs was found to be associated with a likelihood of recurrence of early-stage NSCLC. This information could potentially be used for helping in treatment planning and management of early-stage NSCLC.

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