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Clin Cancer Res. 2019 Mar 1;25(5):1526-1534. doi: 10.1158/1078-0432.CCR-18-2013. Epub 2018 Sep 10.

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

Author information

1
Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, Cleveland, Ohio.
2
Computer Imaging and Medical Applications Laboratory, Universidad Nacional de Colombia, Bogotá, Colombia.
3
Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio.
4
Department of Medicine, University of Athens, Sotiria General Hospital, Athens, Greece.
5
Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
6
Department of Pathology-Anatomic, University Hospitals, Cleveland, Ohio.
7
Hematology and Medical Oncology Department, Cleveland Clinic, Cleveland, Ohio.
8
Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, Cleveland, Ohio. axm788@case.edu.
#
Contributed equally

Abstract

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.See related commentary by Peled et al., p. 1449.

PMID:
30201760
PMCID:
PMC6397708
[Available on 2020-03-01]
DOI:
10.1158/1078-0432.CCR-18-2013

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