An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma

Balazs Acs, Fahad Shabbir Ahmed, Swati Gupta, Pok Fai Wong, Robyn D. Gartrell, Jaya Sarin Pradhan, Emanuelle M. Rizk, Bonnie Gould Rothberg, Yvonne M. Saenger, David L. Rimm

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

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.

Original languageEnglish (US)
Article number5440
JournalNature communications
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2019
Externally publishedYes

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

Fingerprint

Dive into the research topics of 'An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma'. Together they form a unique fingerprint.

Cite this