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. 2019 Nov 29;10(1):5440.
doi: 10.1038/s41467-019-13043-2.

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

Balazs Acs  1   2 , Fahad Shabbir Ahmed  1 , Swati Gupta  1 , Pok Fai Wong  1 , Robyn D Gartrell  3 , Jaya Sarin Pradhan  4 , Emanuelle M Rizk  5 , Bonnie Gould Rothberg  6 , Yvonne M Saenger  5 , David L Rimm  7   8
Affiliations

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

Balazs Acs et al. Nat Commun. .

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.

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Conflict of interest statement

D.L.R. declares that he has served a consultant, advisor and/or servee on a Scientific Advisory Board for Amgen, Astra Zeneca, Agendia, Biocept, BMS, Cell Signaling Technology, Cepheid, Daiichi Sankyo, GSK, InVicro/Konica Minolta, Merck, NanoString, Perkin Elmer, PAIGE.AI, and Ultivue. He holds equity in PixelGear (start-up company related to direct tissue imaging) and Astra Zeneca, Cepheid, Navigate/Novartis, NextCure, Lilly, Ultivue, Ventana and Perkin Elmer/Akoya fund research in his lab. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Tumor-infiltrating lymphocytes (TIL) scores in cohort #1. The prognostic potential of automated TIL scores (a) and pathologist’s TIL scores (b) in cohort #1. Correlation between eTIL% scores and CD4 positive (+), CD8+, and CD20+ immune cells measured by quantitative immunofluorescence (c–f).
Fig. 2
Fig. 2
Validation of automated tumor-infiltrating lymphocytes (TIL) algorithm in three independent cohorts. The prognostic potential of automated TIL scores performed on tissue microarray (TMA slides) (a, b) and whole slides (c, d) in cohorts #2, #3, and #4.
Fig. 3
Fig. 3
Representative picture of a sample melanoma case showing the H&E image (Zoom: ×20, a) and the digital-image analysis (DIA) mask (b). Scale bar represents 20 µm. Using the NN192 algorithm, segmentation shows red indicates tumor cells, purple marks immune cells, green corresponds to stromal cells, and yellow indicate others (false cell detections or unknown or background). Since stromal and “other” cells are rare, large arrows are included to show example cells.
See this image and copyright information in PMC

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References

    1. Disis ML. Immune regulation of cancer. J. Clin. Oncol. 2010;28:4531–4538. doi: 10.1200/JCO.2009.27.2146. - DOI - PMC - PubMed
    1. Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat. Immunol. 2013;14:1014–1022. doi: 10.1038/ni.2703. - DOI - PMC - PubMed
    1. Coulie PG, Van den Eynde, van der Bruggen BJ, P., Boon T. Tumour antigens recognized by T lymphocytes: at the core of cancer immunotherapy. Nat. Rev. Cancer. 2014;14:135–146. doi: 10.1038/nrc3670. - DOI - PubMed
    1. Fridman WH, Pages F, Sautes-Fridman C, Galon J. The immune contexture in human tumours: impact on clinical outcome. Nat. Rev. Cancer. 2012;12:298–306. doi: 10.1038/nrc3245. - DOI - PubMed
    1. Eggermont AM, et al. Prolonged survival in stage III melanoma with ipilimumab adjuvant therapy. N. Engl. J. Med. 2016;375:1845–1855. doi: 10.1056/NEJMoa1611299. - DOI - PMC - PubMed

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