Résumé
Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers.
langue originale | Anglais |
---|---|
Pages (de - à) | 514-532 |
Nombre de pages | 19 |
journal | Journal of Pathology |
Volume | 260 |
Numéro de publication | 5 |
Les DOIs | |
état | Publié - 1 août 2023 |
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Dans: Journal of Pathology, Vol 260, Numéro 5, 01.08.2023, p. 514-532.
Résultats de recherche: Contribution à un journal › Article 'review' › Revue par des pairs
TY - JOUR
T1 - Spatial analyses of immune cell infiltration in cancer
T2 - current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer
AU - Page, David B.
AU - Broeckx, Glenn
AU - Jahangir, Chowdhury Arif
AU - Verbandt, Sara
AU - Gupta, Rajarsi R.
AU - Thagaard, Jeppe
AU - Khiroya, Reena
AU - Kos, Zuzana
AU - Abduljabbar, Khalid
AU - Acosta Haab, Gabriela
AU - Acs, Balazs
AU - Akturk, Guray
AU - Almeida, Jonas S.
AU - Alvarado-Cabrero, Isabel
AU - Azmoudeh-Ardalan, Farid
AU - Badve, Sunil
AU - Baharun, Nurkhairul Bariyah
AU - Bellolio, Enrique R.
AU - Bheemaraju, Vydehi
AU - Blenman, Kim R.M.
AU - Botinelly Mendonça Fujimoto, Luciana
AU - Bouchmaa, Najat
AU - Burgues, Octavio
AU - Cheang, Maggie Chon U.
AU - Ciompi, Francesco
AU - Cooper, Lee A.D.
AU - Coosemans, An
AU - Corredor, Germán
AU - Dantas Portela, Flavio Luis
AU - Deman, Frederik
AU - Demaria, Sandra
AU - Dudgeon, Sarah N.
AU - Elghazawy, Mahmoud
AU - Ely, Scott
AU - Fernandez-Martín, Claudio
AU - Fineberg, Susan
AU - Fox, Stephen B.
AU - Gallagher, William M.
AU - Giltnane, Jennifer M.
AU - Gnjatic, Sacha
AU - Gonzalez-Ericsson, Paula I.
AU - Grigoriadis, Anita
AU - Halama, Niels
AU - Hanna, Matthew G.
AU - Harbhajanka, Aparna
AU - Hardas, Alexandros
AU - Hart, Steven N.
AU - Hartman, Johan
AU - Hewitt, Stephen
AU - Hida, Akira I.
AU - Horlings, Hugo M.
AU - Husain, Zaheed
AU - Hytopoulos, Evangelos
AU - Irshad, Sheeba
AU - Janssen, Emiel A.M.
AU - Kahila, Mohamed
AU - Kataoka, Tatsuki R.
AU - Kawaguchi, Kosuke
AU - Kharidehal, Durga
AU - Khramtsov, Andrey I.
AU - Kiraz, Umay
AU - Kirtani, Pawan
AU - Kodach, Liudmila L.
AU - Korski, Konstanty
AU - Kovács, Anikó
AU - Laenkholm, Anne Vibeke
AU - Lang-Schwarz, Corinna
AU - Larsimont, Denis
AU - Lennerz, Jochen K.
AU - Lerousseau, Marvin
AU - Li, Xiaoxian
AU - Ly, Amy
AU - Madabhushi, Anant
AU - Maley, Sai K.
AU - Manur Narasimhamurthy, Vidya
AU - Marks, Douglas K.
AU - McDonald, Elizabeth S.
AU - Mehrotra, Ravi
AU - Michiels, Stefan
AU - Minhas, Fayyaz ul Amir Afsar
AU - Mittal, Shachi
AU - Moore, David A.
AU - Mushtaq, Shamim
AU - Nighat, Hussain
AU - Papathomas, Thomas
AU - Penault-Llorca, Frederique
AU - Perera, Rashindrie D.
AU - Pinard, Christopher J.
AU - Pinto-Cardenas, Juan Carlos
AU - Pruneri, Giancarlo
AU - Pusztai, Lajos
AU - Rahman, Arman
AU - Rajpoot, Nasir Mahmood
AU - Rapoport, Bernardo Leon
AU - Rau, Tilman T.
AU - Reis-Filho, Jorge S.
AU - Ribeiro, Joana M.
AU - Rimm, David
AU - Vincent-Salomon, Anne
AU - Salto-Tellez, Manuel
AU - Saltz, Joel
AU - Sayed, Shahin
AU - Siziopikou, Kalliopi P.
AU - Sotiriou, Christos
AU - Stenzinger, Albrecht
AU - Sughayer, Maher A.
AU - Sur, Daniel
AU - Symmans, Fraser
AU - Tanaka, Sunao
AU - Taxter, Timothy
AU - Tejpar, Sabine
AU - Teuwen, Jonas
AU - Thompson, E. Aubrey
AU - Tramm, Trine
AU - Tran, William T.
AU - van der Laak, Jeroen
AU - van Diest, Paul J.
AU - Verghese, Gregory E.
AU - Viale, Giuseppe
AU - Vieth, Michael
AU - Wahab, Noorul
AU - Walter, Thomas
AU - Waumans, Yannick
AU - Wen, Hannah Y.
AU - Yang, Wentao
AU - Yuan, Yinyin
AU - Adams, Sylvia
AU - Bartlett, John Mark Seaverns
AU - Loibl, Sibylle
AU - Denkert, Carsten
AU - Savas, Peter
AU - Loi, Sherene
AU - Salgado, Roberto
AU - Specht Stovgaard, Elisabeth
N1 - Publisher Copyright: © 2023 The Pathological Society of Great Britain and Ireland.
PY - 2023/8/1
Y1 - 2023/8/1
N2 - Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers.
AB - Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers.
KW - Immunoscore
KW - TIL
KW - multispectral immunofluorescence
KW - sTIL score
KW - spatial heterogeneity
KW - spatial statistics
KW - tumor infiltrating lymphocytes
UR - http://www.scopus.com/inward/record.url?scp=85167992595&partnerID=8YFLogxK
U2 - 10.1002/path.6165
DO - 10.1002/path.6165
M3 - Review article
C2 - 37608771
AN - SCOPUS:85167992595
SN - 0022-3417
VL - 260
SP - 514
EP - 532
JO - Journal of Pathology
JF - Journal of Pathology
IS - 5
ER -