Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. Tumor-infiltrating lymphocytes (TILs) were identified from standard pathology cancer images by a deep-learning-derived “computational stain” developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles.

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images / J. Saltz, R. Gupta, L. Hou, T. Kurc, P. Singh, V. Nguyen, D. Samaras, K.R. Shroyer, T. Zhao, R. Batiste, J. Van Arnam, S.J. Caesar-Johnson, J.A. Demchok, I. Felau, M. Kasapi, M.L. Ferguson, C.M. Hutter, H.J. Sofia, R. Tarnuzzer, Z. Wang, L. Yang, J.C. Zenklusen, J.(. Zhang, S. Chudamani, J. Liu, L. Lolla, R. Naresh, T. Pihl, Q. Sun, Y. Wan, W. Ye, J. Cho, T. Defreitas, S. Frazer, N. Gehlenborg, G. Getz, D.I. Heiman, J. Kim, M.S. Lawrence, P. Lin, S. Meier, M.S. Noble, G. Saksena, D. Voet, H. Zhang, B. Bernard, N. Chambwe, V. Dhankani, T. Knijnenburg, R. Kramer, K. Leinonen, Y. Liu, M. Miller, S. Reynolds, I. Shmulevich, V. Thorsson, W. Zhang, R. Akbani, B.M. Broom, A.M. Hegde, J. Zhenlin, R.S. Kanchi, A. Korkut, L. Jun, H. Liang, S. Ling, W. Liu, L. Yiling, G.B. Mills, N. Kwok-Shing, A. Rao, M. Ryan, J. Wang, J.N. Weinstein, J. Zhang, A. Abeshouse, J. Armenia, D. Chakravarty, W.K. Chatila, I. de Bruijn, J. Gao, B.E. Gross, Z.J. Heins, R. Kundra, L. Konnor, M. Ladanyi, A. Luna, M.G. Nissan, A. Ochoa, S.M. Phillips, E. Reznik, F. Sanchez-Vega, C. Sander, N. Schultz, R. Sheridan, S.O. Sumer, Y. Sun, B.S. Taylor, J. Wang, H. Zhang, P. Anur, M. Peto, P. Spellman, C. Benz, J.M. Stuart, C.K. Wong, C. Yau, D.N. Hayes, J.S. Parker, M.D. Wilkerson, A. Ally, M. Balasundaram, R. Bowlby, D. Brooks, R. Carlsen, E. Chuah, N. Dhalla, R. Holt, S.J.M. Jones, K. Kasaian, D. Lee, M. Yussanne, M.A. Marra, M. Mayo, R.A. Moore, A.J. Mungall, K. Mungall, A.G. Robertson, S. Sadeghi, J.E. Schein, P. Sipahimalani, A. Tam, N. Thiessen, K. Tse, T. Wong, A.C. Berger, R. Beroukhim, A.D. Cherniack, C. Cibulskis, S.B. Gabriel, G.F. Gao, H. Gavin, M. Meyerson, S.E. Schumacher, J. Shih, M.H. Kucherlapati, R.S. Kucherlapati, S. Baylin, L. Cope, L. Danilova, M.S. Bootwalla, P.H. Lai, D.T. Maglinte, D.J. Van Den Berg, D.J. Weisenberger, J.T. Auman, S. Balu, T. Bodenheimer, C. Fan, K.A. Hoadley, A.P. Hoyle, S.R. Jefferys, C.D. Jones, S. Meng, P.A. Mieczkowski, L.E. Mose, A.H. Perou, C.M. Perou, J. Roach, Y. Shi, J.V. Simons, T. Skelly, M.G. Soloway, D. Tan, U. Veluvolu, H. Fan, T. Hinoue, P.W. Laird, H. Shen, W. Zhou, M. Bellair, K. Chang, K. Covington, C.J. Creighton, H. Dinh, H. Doddapaneni, L.A. Donehower, J. Drummond, R.A. Gibbs, R. Glenn, W. Hale, Y. Han, H. Jianhong, V. Korchina, S. Lee, L. Lewis, L. Wei, X. Liu, M. Morgan, D. Morton, D. Muzny, J. Santibanez, M. Sheth, E. Shinbrot, L. Wang, M. Wang, D.A. Wheeler, X. Liu, F. Zhao, J. Hess, E.L. Appelbaum, M. Bailey, M.G. Cordes, L. Ding, C.C. Fronick, L.A. Fulton, R.S. Fulton, C. Kandoth, E.R. Mardis, M.D. Mclellan, C.A. Miller, H.K. Schmidt, R.K. Wilson, D. Crain, E. Curley, J. Gardner, K. Lau, D. Mallery, S. Morris, J. Paulauskis, R. Penny, C. Shelton, T. Shelton, M. Sherman, E. Thompson, P. Yena, J. Bowen, J.M. Gastier-Foster, M. Gerken, K.M. Leraas, T.M. Lichtenberg, N.C. Ramirez, L. Wise, E. Zmuda, N. Corcoran, T. Costello, C. Hovens, A.L. Carvalho, A.C. de Carvalho, J.H. Fregnani, A. Longatto-Filho, R.M. Reis, C. Scapulatempo-Neto, H.C.S. Silveira, D.O. Vidal, A. Burnette, J. Eschbacher, B. Hermes, A. Noss, R. Singh, M.L. Anderson, P.D. Castro, M. Ittmann, D. Huntsman, B. Kohl, L. Xuan, R. Thorp, C. Andry, E.R. Duffy, V. Lyadov, O. Paklina, G. Setdikova, A. Shabunin, M. Tavobilov, C. Mcpherson, R. Warnick, R. Berkowitz, D. Cramer, C. Feltmate, N. Horowitz, A. Kibel, M. Muto, C.P. Raut, A. Malykh, J.S. Barnholtz-Sloan, W. Barrett, K. Devine, J. Fulop, Q.T. Ostrom, K. Shimmel, Y. Wolinsky, A.E. Sloan, A. De Rose, F. Giuliante, M. Goodman, B.Y. Karlan, C.H. Hagedorn, J. Eckman, J. Harr, J. Myers, K. Tucker, L.A. Zach, B. Deyarmin, H. Hai, L. Kvecher, C. Larson, R.J. Mural, S. Somiari, A. Vicha, T. Zelinka, J. Bennett, M. Iacocca, B. Rabeno, P. Swanson, M. Latour, L. Lacombe, B. Têtu, A. Bergeron, M. Mcgraw, S.M. Staugaitis, J. Chabot, H. Hibshoosh, A. Sepulveda, S. Tao, T. Wang, O. Potapova, O. Voronina, L. Desjardins, O. Mariani, S. Roman-Roman, X. Sastre, M. Stern, F. Cheng, S. Signoretti, A. Berchuck, D. Bigner, E. Lipp, J. Marks, S. Mccall, R. Mclendon, A. Secord, A. Sharp, M. Behera, D.J. Brat, A. Chen, K. Delman, S. Force, F. Khuri, K. Magliocca, S. Maithel, J.J. Olson, T. Owonikoko, A. Pickens, S. Ramalingam, D.M. Shin, G. Sica, E.G. Van Meir, H. Zhang, W. Eijckenboom, A. Gillis, E. Korpershoek, L. Looijenga, W. Oosterhuis, H. Stoop, K.E. van Kessel, E.C. Zwarthoff, C. Calatozzolo, L. Cuppini, S. Cuzzubbo, F. Dimeco, G. Finocchiaro, L. Mattei, A. Perin, B. Pollo, C. Chen, J. Houck, P. Lohavanichbutr, A. Hartmann, C. Stoehr, R. Stoehr, H. Taubert, S. Wach, B. Wullich, W. Kycler, D. Murawa, M. Wiznerowicz, K. Chung, W.J. Edenfield, J. Martin, E. Baudin, G. Bubley, R. Bueno, A. De Rienzo, W.G. Richards, S. Kalkanis, T. Mikkelsen, H. Noushmehr, L. Scarpace, N. Girard, M. Aymerich, E. Campo, E. Giné, A.L. Guillermo, N. Van Bang, P.T. Hanh, B.D. Phu, Y. Tang, H. Colman, K. Evason, P.R. Dottino, J.A. Martignetti, H. Gabra, H. Juhl, T. Akeredolu, S. Stepa, D. Hoon, K. Ahn, K.J. Kang, F. Beuschlein, A. Breggia, M. Birrer, D. Bell, M. Borad, A.H. Bryce, E. Castle, V. Chandan, J. Cheville, J.A. Copland, M. Farnell, T. Flotte, N. Giama, H. Thai, M. Kendrick, J. Kocher, K. Kopp, C. Moser, D. Nagorney, D. O'Brien, B.P. O'Neill, T. Patel, G. Petersen, F. Que, M. Rivera, L. Roberts, R. Smallridge, T. Smyrk, M. Stanton, R.H. Thompson, M. Torbenson, J.D. Yang, L. Zhang, F. Brimo, J.A. Ajani, A.M.A. Gonzalez, C. Behrens, J. Bondaruk, R. Broaddus, B. Czerniak, B. Esmaeli, J. Fujimoto, J. Gershenwald, C. Guo, A.J. Lazar, C. Logothetis, F. Meric-Bernstam, C. Moran, L. Ramondetta, D. Rice, A. Sood, P. Tamboli, T. Thompson, P. Troncoso, A. Tsao, I. Wistuba, C. Carter, L. Haydu, P. Hersey, V. Jakrot, H. Kakavand, R. Kefford, K. Lee, G. Long, G. Mann, M. Quinn, R. Saw, R. Scolyer, K. Shannon, A. Spillane, O. Stretch, M. Synott, J. Thompson, J. Wilmott, H. Al-Ahmadie, T.A. Chan, R. Ghossein, A. Gopalan, D.A. Levine, V. Reuter, S. Singer, B. Singh, N.V. Tien, T. Broudy, C. Mirsaidi, P. Nair, P. Drwiega, J. Miller, J. Smith, H. Zaren, J. Park, N.P. Hung, E. Kebebew, W.M. Linehan, A.R. Metwalli, K. Pacak, P.A. Pinto, M. Schiffman, L.S. Schmidt, C.D. Vocke, N. Wentzensen, R. Worrell, H. Yang, M. Moncrieff, C. Goparaju, J. Melamed, H. Pass, N. Botnariuc, I. Caraman, M. Cernat, I. Chemencedji, A. Clipca, S. Doruc, G. Gorincioi, S. Mura, M. Pirtac, I. Stancul, D. Tcaciuc, M. Albert, I. Alexopoulou, A. Arnaout, J. Bartlett, J. Engel, S. Gilbert, J. Parfitt, H. Sekhon, G. Thomas, D.M. Rassl, R.C. Rintoul, C. Bifulco, R. Tamakawa, W. Urba, N. Hayward, H. Timmers, A. Antenucci, F. Facciolo, G. Grazi, M. Marino, R. Merola, R. de Krijger, A. Gimenez-Roqueplo, A. Piché, S. Chevalier, G. Mckercher, K. Birsoy, G. Barnett, C. Brewer, C. Farver, T. Naska, N.A. Pennell, D. Raymond, C. Schilero, K. Smolenski, F. Williams, C. Morrison, J.A. Borgia, M.J. Liptay, M. Pool, C.W. Seder, K. Junker, L. Omberg, M. Dinkin, G. Manikhas, D. Alvaro, M.C. Bragazzi, V. Cardinale, G. Carpino, E. Gaudio, D. Chesla, S. Cottingham, M. Dubina, F. Moiseenko, R. Dhanasekaran, K. Becker, K. Janssen, J. Slotta-Huspenina, M.H. Abdel-Rahman, D. Aziz, S. Bell, C.M. Cebulla, A. Davis, R. Duell, J.B. Elder, J. Hilty, B. Kumar, J. Lang, N.L. Lehman, R. Mandt, P. Nguyen, R. Pilarski, K. Rai, L. Schoenfield, K. Senecal, P. Wakely, P. Hansen, R. Lechan, J. Powers, A. Tischler, W.E. Grizzle, K.C. Sexton, A. Kastl, J. Henderson, S. Porten, J. Waldmann, M. Fassnacht, S.L. Asa, D. Schadendorf, M. Couce, M. Graefen, H. Huland, G. Sauter, T. Schlomm, R. Simon, P. Tennstedt, O. Olabode, M. Nelson, O. Bathe, P.R. Carroll, J.M. Chan, P. Disaia, P. Glenn, R.K. Kelley, C.N. Landen, J. Phillips, M. Prados, J. Simko, K. Smith-McCune, S. Vandenberg, K. Roggin, A. Fehrenbach, A. Kendler, S. Sifri, R. Steele, A. Jimeno, F. Carey, I. Forgie, M. Mannelli, M. Carney, B. Hernandez, B. Campos, C. Herold-Mende, C. Jungk, A. Unterberg, A. von Deimling, A. Bossler, J. Galbraith, L. Jacobus, M. Knudson, T. Knutson, M. Deqin, M. Milhem, R. Sigmund, A.K. Godwin, R. Madan, H.G. Rosenthal, C. Adebamowo, S.N. Adebamowo, A. Boussioutas, D. Beer, T. Giordano, A. Mes-Masson, F. Saad, T. Bocklage, L. Landrum, R. Mannel, K. Moore, K. Moxley, R. Postier, J. Walker, R. Zuna, M. Feldman, F. Valdivieso, R. Dhir, J. Luketich, E.M.M. Pinero, M. Quintero-Aguilo, C.G. Carlotti, J.S. Dos Santos, R. Kemp, A. Sankarankuty, D. Tirapelli, J. Catto, K. Agnew, E. Swisher, J. Creaney, B. Robinson, C.S. Shelley, E.M. Godwin, S. Kendall, C. Shipman, C. Bradford, T. Carey, A. Haddad, J. Moyer, L. Peterson, M. Prince, L. Rozek, G. Wolf, R. Bowman, K.M. Fong, I. Yang, R. Korst, W.K. Rathmell, J.L. Fantacone-Campbell, J.A. Hooke, A.J. Kovatich, C.D. Shriver, J. Dipersio, B. Drake, R. Govindan, S. Heath, T. Ley, B. Van Tine, P. Westervelt, M.A. Rubin, J.I. Lee, N.D. Aredes, A. Mariamidze, I. Shmulevich, A.U.K. Rao, A.J. Lazar, A. Sharma, V. Thorsson. - In: CELL REPORTS. - ISSN 2211-1247. - 23:1(2018 Apr 03), pp. 181-193.e7. [10.1016/j.celrep.2018.03.086]

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

F. Dimeco;
2018

Abstract

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. Tumor-infiltrating lymphocytes (TILs) were identified from standard pathology cancer images by a deep-learning-derived “computational stain” developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles.
artificial intelligence; bioinformatics; computer vision; deep learning; digital pathology; immuno-oncology; lymphocytes; machine learning; tumor microenvironment; tumor-infiltrating lymphocytes; Biochemistry, Genetics and Molecular Biology (all)
Settore MED/27 - Neurochirurgia
3-apr-2018
Article (author)
File in questo prodotto:
File Dimensione Formato  
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 4.01 MB
Formato Adobe PDF
4.01 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/586507
Citazioni
  • ???jsp.display-item.citation.pmc??? 364
  • Scopus 630
  • ???jsp.display-item.citation.isi??? 579
social impact