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@ARTICLE{Page:278731,
      author       = {D. B. Page and G. Broeckx and C. A. Jahangir and S.
                      Verbandt and R. R. Gupta and J. Thagaard and R. Khiroya and
                      Z. Kos and K. Abduljabbar and G. Acosta Haab and B. Acs and
                      J. S. Almeida and I. Alvarado-Cabrero and F.
                      Azmoudeh-Ardalan and S. Badve and N. B. Baharun and E. R.
                      Bellolio and V. Bheemaraju and K. R. Blenman and L.
                      Botinelly Mendonça Fujimoto and O. Burgues and M. C. U.
                      Cheang and F. Ciompi and L. A. Cooper and A. Coosemans and
                      G. Corredor and F. L. Dantas Portela and F. Deman and S.
                      Demaria and S. N. Dudgeon and M. Elghazawy and S. Ely and C.
                      Fernandez-Martín and S. Fineberg and S. B. Fox and W. M.
                      Gallagher and J. M. Giltnane and S. Gnjatic and P. I.
                      Gonzalez-Ericsson and A. Grigoriadis and N. Halama$^*$ and
                      M. G. Hanna and A. Harbhajanka and A. Hardas and S. N. Hart
                      and J. Hartman and S. Hewitt and A. I. Hida and H. M.
                      Horlings and Z. Husain and E. Hytopoulos and S. Irshad and
                      E. A. Janssen and M. Kahila and T. R. Kataoka and K.
                      Kawaguchi and D. Kharidehal and A. I. Khramtsov and U. Kiraz
                      and P. Kirtani and L. L. Kodach and K. Korski and A. Kovács
                      and A.-V. Laenkholm and C. Lang-Schwarz and D. Larsimont and
                      J. K. Lennerz and M. Lerousseau and X. Li and A. Ly and A.
                      Madabhushi and S. K. Maley and V. Manur Narasimhamurthy and
                      D. K. Marks and E. S. McDonald and R. Mehrotra and S.
                      Michiels and F. U. A. A. Minhas and S. Mittal and D. A.
                      Moore and S. Mushtaq and H. Nighat and T. Papathomas and F.
                      Penault-Llorca and R. D. Perera and C. J. Pinard and J. C.
                      Pinto-Cardenas and G. Pruneri and L. Pusztai and A. Rahman
                      and N. M. Rajpoot and B. L. Rapoport and T. T. Rau and J. S.
                      Reis-Filho and J. M. Ribeiro and D. Rimm and A.-V. Salomon
                      and M. Salto-Tellez and J. Saltz and S. Sayed and K. P.
                      Siziopikou and C. Sotiriou and A. Stenzinger and M. A.
                      Sughayer and D. Sur and F. Symmans and S. Tanaka and T.
                      Taxter and S. Tejpar and J. Teuwen and E. A. Thompson and T.
                      Tramm and W. T. Tran and J. van der Laak and P. J. van Diest
                      and G. E. Verghese and G. Viale and M. Vieth and N. Wahab
                      and T. Walter and Y. Waumans and H. Y. Wen and W. Yang and
                      Y. Yuan and S. Adams and J. M. S. Bartlett and S. Loibl and
                      C. Denkert and P. Savas and S. Loi and R. Salgado and E.
                      Specht Stovgaard and G. Akturk and N. Bouchmaa},
      title        = {{S}patial analyses of immune cell infiltration in cancer:
                      current methods and future directions. {A} report of the
                      {I}nternational {I}mmuno-{O}ncology {B}iomarker {W}orking
                      {G}roup on {B}reast {C}ancer.},
      journal      = {The journal of pathology},
      volume       = {260},
      number       = {5},
      issn         = {0368-3494},
      address      = {Bognor Regis [u.a.]},
      publisher    = {Wiley},
      reportid     = {DKFZ-2023-01702},
      pages        = {514-532},
      year         = {2023},
      note         = {2023 Aug;260(5):514-532},
      abstract     = {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. ©
                      2023 The Pathological Society of Great Britain and Ireland.},
      subtyp        = {Review Article},
      keywords     = {Immunoscore (Other) / TIL (Other) / multispectral
                      immunofluorescence (Other) / sTIL score (Other) / spatial
                      heterogeneity (Other) / spatial statistics (Other) / tumor
                      infiltrating lymphocytes (Other)},
      cin          = {D240},
      ddc          = {610},
      cid          = {I:(DE-He78)D240-20160331},
      pnm          = {314 - Immunologie und Krebs (POF4-314)},
      pid          = {G:(DE-HGF)POF4-314},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37608771},
      doi          = {10.1002/path.6165},
      url          = {https://inrepo02.dkfz.de/record/278731},
}