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. 2020 May 12:6:17.
doi: 10.1038/s41523-020-0156-0. eCollection 2020.

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Zuzana Kos  1 , Elvire Roblin  2   3 , Rim S Kim  4 , Stefan Michiels  2   3 , Brandon D Gallas  5 , Weijie Chen  5 , Koen K van de Vijver  6   7 , Shom Goel  8   9 , Sylvia Adams  10 , Sandra Demaria  11 , Giuseppe Viale  12 , Torsten O Nielsen  13 , Sunil S Badve  14 , W Fraser Symmans  15 , Christos Sotiriou  16 , David L Rimm  17 , Stephen Hewitt  18 , Carsten Denkert  19 , Sibylle Loibl  20 , Stephen J Luen  9   21 , John M S Bartlett  22   23 , Peter Savas  9   21 , Giancarlo Pruneri  24 , Deborah A Dillon  25   26 , Maggie Chon U Cheang  27 , Andrew Tutt  28 , Jacqueline A Hall  29 , Marleen Kok  30 , Hugo M Horlings  6   31 , Anant Madabhushi  32   33 , Jeroen van der Laak  34 , Francesco Ciompi  34 , Anne-Vibeke Laenkholm  35 , Enrique Bellolio  36 , Tina Gruosso  37 , Stephen B Fox  8   38 , Juan Carlos Araya  39 , Giuseppe Floris  40 , Jan Hudeček  41 , Leonie Voorwerk  42 , Andrew H Beck  43 , Jen Kerner  43 , Denis Larsimont  44 , Sabine Declercq  45 , Gert Van den Eynden  45 , Lajos Pusztai  46 , Anna Ehinger  47 , Wentao Yang  48 , Khalid AbdulJabbar  49 , Yinyin Yuan  49 , Rajendra Singh  50 , Crispin Hiley  51 , Maise Al Bakir  51 , Alexander J Lazar  52 , Stephen Naber  53 , Stephan Wienert  54 , Miluska Castillo  55 , Giuseppe Curigliano  56 , Maria-Vittoria Dieci  57   58 , Fabrice André  59 , Charles Swanton  51   60 , Jorge Reis-Filho  61   62 , Joseph Sparano  63 , Eva Balslev  64 , I-Chun Chen  65   66   67 , Elisabeth Ida Specht Stovgaard  64 , Katherine Pogue-Geile  4 , Kim R M Blenman  46 , Frédérique Penault-Llorca  68 , Stuart Schnitt  25 , Sunil R Lakhani  69 , Anne Vincent-Salomon  70 , Federico Rojo  71   72 , Jeremy P Braybrooke  73 , Matthew G Hanna  61 , M Teresa Soler-Monsó  74 , Daniel Bethmann  75 , Carlos A Castaneda  55 , Karen Willard-Gallo  76 , Ashish Sharma  77 , Huang-Chun Lien  78 , Susan Fineberg  79 , Jeppe Thagaard  80 , Laura Comerma  72   81 , Paula Gonzalez-Ericsson  82 , Edi Brogi  61 , Sherene Loi  9   21 , Joel Saltz  83 , Frederick Klaushen  84 , Lee Cooper  85 , Mohamed Amgad  86 , David A Moore  87   88 , Roberto Salgado  21   45 ; International Immuno-Oncology Biomarker Working Group
Collaborators, Affiliations

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Zuzana Kos et al. NPJ Breast Cancer. .

Abstract

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

Keywords: Immunosurveillance; Prognostic markers.

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Conflict of interest statement

Competing interestsA.E. is on the Roche advisory board and has reported honoraria from Amgen, Novartis and Roche. A.J.L. is a consultant for BMS, Merck, AZ/Medimmune, and Genentech. R.S. reports research funding from Roche, Puma, Merck; advisory board and consultancy for BMS; travel funding from Roche, Merck, and Astra Zeneca. S.G. reports Lab research funding from Lilly, Clinical research funding from Eli Lilly and Novartis and is a Paid advisor to Eli Lilly, Novartis, and G1 Therapeutics. J.v.d.L. is member of the scientific advisory boards of Philips, the Netherlands and ContextVision, Sweden and receives research funding from Philips, the Netherlands and Sectra, Sweden. S.A. reports Research funding to institution from Merck, Genentech, BMS, Novartis, Celgene and Amgen and is an uncompensated consultant /steering committee member for Merck, Genentech and BMS. T.O.N. has consulted for Nanostring and received compensation and has intellectual property rights/ownership interests from Bioclassifier LLC [not related to the subject material under consideration]. S.L. receives research funding to institution from Novartis, Bristol Meyers Squibb, Merck, Roche-Genentech, Puma Biotechnology, Pfizer and Eli Lilly, has acted as consultant (not compensated) to Seattle Genetics, Pfizer, Novartis, BMS, Merck, AstraZeneca and Roche-Genentech and acted as consultant (paid to her institution) to Aduro Biotech. S.R.L. has received travel and educational funding from Roche/Ventana. A.M. is an equity holder in Elucid Bioimaging and in Inspirata Inc., a scientific advisory consultant for Inspirata Inc, has served as a scientific advisory board member for Inspirata Inc, Astrazeneca, Bristol Meyers-Squibb and Merck, has sponsored research agreements with Philips and Inspirata Inc, is involved in a NIH U24 grant with PathCore Inc, and 3 different R01 grants with Inspirata Inc. and his technology has been licensed to Elucid Bioimaging and Inspirata Inc. G.C. is on the advisory boards of Roche, BMS, Pfizer, Seattle Genetics and Ellipsis, and reports personal fees from Roche, BMS, Pfizer, Seattle Genetics, and Ellipsis, outside of the submitted work. J.H. is the director and owner of Vivactiv Ltd. J.H. is the director and owner of Slide Score B.V. F.P.L. reports funding from Astrazeneca, BMS, Roche, MSD, Pfizer, Novartis, Sanofi, Eli Lilly. J.B. reports consultancies from Insight Genetics, BioNTech AG, Biotheranostics, Pfizer, RNA Diagnostics and OncoXchange, research funding from Thermo Fisher Scientific, Genoptix, Agendia, NanoString Technologies, Stratifyer GmbH and Biotheranostics, applied for patents, including Jan 2017: Methods and Devices for Predicting Anthracycline Treatment Efficacy, US utility—15/325,472; EPO—15822898.1; Canada—not yet assigned; Jan 2017: Systems, Devices and Methods for Constructing and Using a Biomarker, US utility—15/328,108; EPO—15824751.0; Canada—not yet assigned; Oct 2016: Histone gene module predicts anthracycline benefit, PCT/CA2016/000247; Dec 2016: 95‐Gene Signature of Residual Risk Following Endocrine Treatment, PCT/CA2016/000304; Dec 2016: Immune Gene Signature Predicts Anthracycline Benefit, PCT/CA2016/000305. M.A.S. reports consulting work for Achilles Therapeutics. C.S. reports receipt of grants/research support from Pfizer, AstraZeneca, BMS and Ventana; receipt of honoraria, consultancy, or SAB Member fees from Pfizer, Novartis, GlaxoSmithKline, MSD, BMS, Celgene, AstraZeneca, Illumina, Sarah Canon Research Institute, Genentech, Roche-Ventana, GRAIL, Medicxi; Advisor for Dynamo Therapeutics; Stock shareholder in Apogen Biotechnologies, Epic Bioscience, GRAIL; Co-Founder & stock options in Achilles Therapeutics. A.H.B. is the co-founder and CEO of PathAI. J.K. is an employee of PathAI. D.D. is on the advisory board for Oncology Analytics, Inc, and a consultant for Novartis. D.L.R. is on the advisory board of Amgen, Astra Zeneca, Cell Signaling Technology, Cepheid, Daiichi Sankyo, GSK, Konica/Minolta, Merck, NanoString, Perkin Elmer, Ventana, Ultivue; receives research support from Astra Zeneca, Cepheid, Navigate BioPharma, NextCure, Lilly, Ultivue; instrument support from Ventana, Akoya/Perkin Elmer, NanoString; paid consultant for Biocept; received travel honoraria from BMS, founder and equity holder for PixelGear and received royalty from Rarecyte. A.T. reports benefits from ICR’s Inventors Scheme associated with patents for one of PARP inhibitors in BRCA1/2 associated cancers, as well as honoraria from Pfizer, Vertex, Prime Oncology, Artios, honoraria and stock in InBioMotion, honoraria and financial support for research from AstraZeneca, Medivation, Myriad Genetics and Merck Serono. This work includes contributions from, and was reviewed by, individuals at the FDA. This work has been approved for publication by the agency, but it does not necessarily reflect official agency policy. Certain commercial materials and equipment are identified in order to adequately specify experimental procedures. In no case does such identification imply recommendation or endorsement by the FDA, nor does it imply that the items identified are necessarily the best available for the purpose. This work includes contributions from, and was reviewed by, individuals who received funding from the National Institutes of Health, the U.S. Department of Veterans Affairs and the Department of Defense. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the U.S. Department of Veterans Affairs, the Department of Defense, or the United States Government.

Figures

Fig. 1
Fig. 1. Study flow diagram.
Raw data and original scanned images from 3 previously performed ring studies were evaluated (shaded Box 1).
Fig. 2
Fig. 2. Reference images representing percent sTIL scores.
Available at www.tilsinbreastcancer.org.
Fig. 3
Fig. 3. Standard deviation as a function of mean across all sTILs scores for each slide in 3 ring studies assessing concordance amongst pathologists.
a Ring study 1, 32 pathologists evaluated 60 scanned core biopsy specimens. b Ring study 2, 28 pathologists evaluated 60 scanned core biopsy specimens. c Ring study 3, 6 pathologists evaluated 100 scanned whole section specimens. 10% of cases in each study showing the greatest variability in sTIL scores are shown as red squares. Black triangles identify additional cases identified for slide assessment.
Fig. 4
Fig. 4. Heterogeneity in sTIL distribution as a cause of variation in sTIL assessment in breast cancer.
Different examples of heterogeneity include a increased sTILs at the leading edge (blue arrow) compared to the central tumor (yellow arrow); b marked heterogeneity in sTIL density within the tumor; and c variably spaced apart clusters of cancer cells with a dense tight lymphocytic infiltrate separated by collagenous stroma with sparse infiltrate.
Fig. 5
Fig. 5. Technical factors as a cause of variation in sTIL assessment in breast cancer.
Examples of different technical factors include a a poor quality slide as can be seen secondary to prolonged ischemic time, poor fixation or issues during processing; b crush artifact; and c out-of-focus scan.
Fig. 6
Fig. 6. Scoring the wrong area as a cause of variation in sTIL assessment in breast cancer.
Scenarios where there may be challenges in deciding which areas to score include a difficulty defining the tumor boundary (dashed line) and including fibrous scars (yellow arrow) or lymphoid aggregates (blue arrow) beyond the invasive front; b including lymphocytes surrounding ductal carcinoma in situ (DCIS) which may be difficult to distinguish from invasive carcinoma; c including lymphocytes associated with an encapsulated papillary carcinoma component of a tumor; and d including lymphocytes surrounding benign glands. Shown is invasive carcinoma (yellow arrows) surrounding a benign lobule with associated lymphocytes; adjacent benign lobules (blue arrows) show dense lymphoid aggregates identify the lymphocytic infiltrate to be related to the entrapped lobule rather than the carcinoma.
Fig. 7
Fig. 7. Scoring the wrong cells as a cause of variation in sTIL assessment in breast cancer.
Examples where the wrong cells are scored include a counting intratumoral TILs (iTILS); b counting neutrophils; c counting histiocytes; d misinterpreting apoptotic cells as lymphocytes; and e artifactual falling apart of cells mimicking TILs.
Fig. 8
Fig. 8. Limited stroma within tumors as a cause of variation in sTIL assessment in breast cancer.
Difficulties in sTIL assessment related to stroma include a tumor with small volume of intratumoral stroma present for evaluation; b large areas of necrosis which decrease scorable stromal component; and c mucinous tumors.
Fig. 9
Fig. 9. Variation in outcome estimation based on stromal TIL assessment.
Shown is the variation in estimated outcome based on sTIL assessment for a 60-year-old patient with a histological grade 3 tumor, 2–5cm in size and receiving anthracycline+taxane based chemotherapy. Presuming a true value for sTILs of 30%, changes in estimated 5-year iDFS for 5, 10, and 20% deviations (increase and decrease) in sTIL assessments are represented with 95% confidence bands. (All calculations were performed using the online triple-negative breast cancer (TNBC)-prognosis tool available at www.tilsinbreastcancer.org).
See this image and copyright information in PMC

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