Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.
Mohamed AmgadElisabeth Specht StovgaardEva BalslevJeppe ThagaardWeijie ChenSarah DudgeonAshish SharmaJennifer K KernerCarsten DenkertYinyin YuanKhalid AbdulJabbarStephan WienertPeter SavasLeonie VoorwerkAndrew H BeckAnant MadabhushiJohan HartmanManu M SebastianHugo M HorlingsJan HudečekFrancesco CiompiDavid A MooreRajendra SinghElvire RoblinMarcelo Luiz BalancinMarie-Christine MathieuJochen K LennerzPawan KirtaniI-Chun ChenJeremy P BraybrookeGiancarlo PruneriSandra DemariaSylvia AdamsStuart J SchnittSunil R LakhaniFederico RojoLaura ComermaSunil S BadveMehrnoush KhojastehWilliam Fraser SymmansChristos SotiriouPaula I Gonzalez EricssonKatherine L Pogue-GeileRim S KimDavid L RimmGiuseppe VialeStephen M HewittJohn M S BartlettFrédérique Penault-LlorcaShom GoelHuang-Chun LienSibylle LoiblZuzana KosSherene LoiMatthew G HannaStefan MichielsMarleen KokTorsten O NielsenAlexander J F LazarZsuzsanna Bago-HorvathLoes F S KooremanJeroen van der LaakJoel SaltzBrandon D GallasUday KurkureMichael BarnesRoberto SalgadoLee A D Coopernull nullPublished in: NPJ breast cancer (2020)
Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.