Abstract

Assessment of tumor infiltrating lymphocytes (TILs) as a prognostic variable in melanoma has not seen broad adoption due to lack of standardization. Automation could represent a solution. Here, using open source software, we build an algorithm for image-based automated assessment of TILs on hematoxylin-eosin stained sections in melanoma. Using a retrospective collection of 641 melanoma patients comprising four independent cohorts; one training set (N = 227) and three validation cohorts (N = 137, N = 201, N = 76) from 2 institutions, we show that the automated TIL scoring algorithm separates patients into favorable and poor prognosis cohorts, where higher TILs scores were associated with favorable prognosis. In multivariable analyses, automated TIL scores show an independent association with disease-specific overall survival. Therefore, the open source, automated TIL scoring is an independent prognostic marker in melanoma. With further study, we believe that this algorithm could be useful to define a subset of patients that could potentially be spared immunotherapy.

Details

Title
An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma
Author
Acs, Balazs 1   VIAFID ORCID Logo  ; Ahmed, Fahad Shabbir 2   VIAFID ORCID Logo  ; Gupta, Swati 2 ; Wong, Pok Fai 2 ; Gartrell, Robyn D 3 ; Jaya Sarin Pradhan 4 ; Rizk, Emanuelle M 5 ; Bonnie Gould Rothberg 6 ; Saenger, Yvonne M 5 ; Rimm, David L 7   VIAFID ORCID Logo 

1  Department of Pathology, Yale School of Medicine, New Haven, CT, USA; Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden 
2  Department of Pathology, Yale School of Medicine, New Haven, CT, USA 
3  Department of Medicine, Division of Hematology/Oncology, Columbia University Medical Center/New York Presbyterian, New York, NY, USA 
4  Department of Pathology and Cell Biology, Division of Oral and Maxillofacial Pathology, Columbia University Irving Medical Center/New York Presbyterian, New York, NY, USA 
5  Department of Medicine, Division of Hematology/Oncology, Columbia University Irving Medical Center/New York Presbyterian, New York, NY, USA 
6  Department of Medicine, Yale School of Medicine, New Haven, CT, USA 
7  Department of Pathology, Yale School of Medicine, New Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA 
Pages
1-7
Publication year
2019
Publication date
Nov 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-019-13043-2
ProQuest document ID
2319733118
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.