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Browsing by Author "Comerma, Laura"
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Item Assessing tumor infiltrating lymphocytes in solid tumors: a practical review for pathologists and proposal for a standardized method from the International Immuno-Oncology Biomarkers Working Group: Part 1: Assessing the host immune response, TILs in invasive breast carcinoma and ductal carcinoma in situ, metastatic tumor deposits and areas for further research(Wolters Kluwer, 2017-09) Hendry, Shona; Salgado, Roberto; Gevaert, Thomas; Russell, Prudence; John, Tom; Thapa, Bibhusal; Christie, Michael; van de Vijver, Koen; Estrada, M. V.; Gonzalez-Ericsson, Paula; Sanders, Melinda; Soloman, Benjamin; Solinas, Cinzia; Van den Eynden, Gert; Allory, Yves; Preusser, Matthias; Hainfellner, Johannes; Pruneri, Giancarlo; Vingiani, Andrea; Demaria, Sandra; Symmans, Fraser; Nuciforo, Paolo; Comerma, Laura; Thompson, E. A.; Lakhani, Sunil; Kim, Seong-Rim; Schnitt, Stuart; Colpaert, Cecile; Sotiriou, Christos; Scherer, Stefan; Ignatiadis, Michail; Badve, Sunil S.; Pierce, Robert; Viale, Giuseppe; Sirtaine, Nicolas; Penault-Llorca, Frederique; Sugie, Tomohagu; Fineberg, Susan; Paik, Soonmyung; Srinivasan, Ashok; Richardson, Andrea; Wang, Yihong; Chmielik, Ewa; Brock, Jane; Johnson, Douglas; Balko, Justin; Wienert, Stephan; Bossuyt, Veerle; Michiels, Stefan; Ternes, Nils; Burchardi, Nicole; Luen, Stephen; Savas, Peter; Klauschen, Frederick; Watson, Peter; Nelson, Brad; Criscitiello, Carmen; O'Toole, Sandra; Larsimont, Denis; de Wind, Roland; Curigliano, Giuseppe; André, Fabrice; Lacroix-Triki, Magali; van de Vijver, Mark; Rojo, Federico; Floris, Giuseppe; Bedri, Shahinaz; Sparano, Joseph; Rimm, David; Nielsen, Torsten; Kos, Zuzana; Hewitt, Stephen; Singh, Baljit; Farshid, Gelareh; Loibl, Sibylle; Allison, Kimberly; Tung, Nadine; Adams, Sylvia; Willard-Gallo, Karen; Horlings, Hugo; Gandhi, Leena; Moreira, Andre; Hirsch, Fred; Dieci, Maria; Urbanowicz, Maria; Brcic, Iva; Korski, Konstanty; Gaire, Fabien; Koeppen, Hartmut; Lo, Amy; Giltnane, Jennifer; Rebelatto, Marlon; Steele, Keith; Zha, Jiping; Emancipator, Kenneth; Juco, Jonathan; Denkert, Carsten; Reis-Filho, Jorge; Loi, Sherene; Fox, Stephen; Pathology and Laboratory Medicine, School of MedicineAssessment of tumor-infiltrating lymphocytes (TILs) in histopathologic specimens can provide important prognostic information in diverse solid tumor types, and may also be of value in predicting response to treatments. However, implementation as a routine clinical biomarker has not yet been achieved. As successful use of immune checkpoint inhibitors and other forms of immunotherapy become a clinical reality, the need for widely applicable, accessible, and reliable immunooncology biomarkers is clear. In part 1 of this review we briefly discuss the host immune response to tumors and different approaches to TIL assessment. We propose a standardized methodology to assess TILs in solid tumors on hematoxylin and eosin sections, in both primary and metastatic settings, based on the International Immuno-Oncology Biomarker Working Group guidelines for TIL assessment in invasive breast carcinoma. A review of the literature regarding the value of TIL assessment in different solid tumor types follows in part 2. The method we propose is reproducible, affordable, easily applied, and has demonstrated prognostic and predictive significance in invasive breast carcinoma. This standardized methodology may be used as a reference against which other methods are compared, and should be evaluated for clinical validity and utility. Standardization of TIL assessment will help to improve consistency and reproducibility in this field, enrich both the quality and quantity of comparable evidence, and help to thoroughly evaluate the utility of TILs assessment in this era of immunotherapy.Item Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group(Nature Research, 2020-05-12) Amgad, Mohamed; Stovgaard, Elisabeth Specht; Balslev, Eva; Thagaard, Jeppe; Chen, Weijie; Dudgeon, Sarah; Sharma, Ashish; Kerner, Jennifer K.; Denkert, Carsten; Yuan, Yinyin; AbdulJabbar, Khalid; Wienert, Stephan; Savas, Peter; Voorwerk, Leonie; Beck, Andrew H.; Madabhushi, Anant; Hartman, Johan; Sebastian, Manu M.; Horlings, Hugo M.; Hudeček, Jan; Ciompi, Francesco; Moore, David A.; Singh, Rajendra; Roblin, Elvire; Balancin, Marcelo Luiz; Mathieu, Marie-Christine; Lennerz, Jochen K.; Kirtani, Pawan; Chen, I-Chun; Braybrooke, Jeremy P.; Pruneri, Giancarlo; Demaria, Sandra; Adams, Sylvia; Schnitt, Stuart J.; Lakhani, Sunil R.; Rojo, Federico; Comerma, Laura; Badve, Sunil S.; Khojasteh, Mehrnoush; Symmans, W. Fraser; Sotiriou, Christos; Gonzalez-Ericsson, Paula; Pogue-Geile, Katherine L.; Kim, Rim S.; Rimm, David L.; Viale, Giuseppe; Hewitt, Stephen M.; Bartlett, John M. S.; Penault-Llorca, Frédérique; Goel, Shom; Lien, Huang-Chun; Loibl, Sibylle; Kos, Zuzana; Loi, Sherene; Hanna, Matthew G.; Michiels, Stefan; Kok, Marleen; Nielsen, Torsten O.; Lazar, Alexander J.; Bago-Horvath, Zsuzsanna; Kooreman, Loes F. S.; Van der Laak, Jeroen A.W. M.; Saltz, Joel; Gallas, Brandon D.; Kurkure, Uday; Barnes, Michael; Salgado, Roberto; Cooper, Lee A. D.; International Immuno-Oncology Biomarker Working Group; Pathology and Laboratory Medicine, School of MedicineAssessment 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.