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1. Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Author

Jahangir, CA, Page, DB, Broeckx, G, Gonzalez, CA, Burke, C, Murphy, C, Reis-Filho, JS, Ly, A, Harms, PW, Gupta, RR, Vieth, M, Hida, A, Kahila, M, Kos, Z, van Diest, PJ, Verbandt, S, Thagaard, J, Khiroya, R, Abduljabbar, K, Haab, GA, Acs, B, Adams, S, Almeida, JS, Alvarado-Cabrero, I, Azmoudeh-Ardalan, F, Badve, S, Baharun, NB, Bellolio, ER, Bheemaraju, V, Blenman, KRM, Fujimoto, LBM, Burgues, O, Chardas, A, Cheang, MCU, Ciompi, F, Cooper, LAD, Coosemans, A, Corredor, G, Portela, FLD, Deman, F, Demaria, S, Dudgeon, SN, Elghazawy, M, Fernandez-Martin, C, Fineberg, S, Fox, SB, Giltnane, JM, Gnjatic, S, Gonzalez-Ericsson, P, Grigoriadis, A, Halama, N, Hanna, MG, Harbhajanka, A, Hart, SN, Hartman, J, Hewitt, S, Horlings, HM, Husain, Z, Irshad, S, Janssen, EAM, Kataoka, TR, Kawaguchi, K, Khramtsov, A, Kiraz, U, Kirtani, P, Kodach, LL, Korski, K, Akturk, G, Scott, E, Kovacs, A, Laenkholm, A-V, Lang-Schwarz, C, Larsimont, D, Lennerz, JK, Lerousseau, M, Li, X, Madabhushi, A, Maley, SK, Narasimhamurthy, VM, Marks, DK, McDonald, ES, Mehrotra, R, Michiels, S, Kharidehal, D, Minhas, FUAA, Mittal, S, Moore, DA, Mushtaq, S, Nighat, H, Papathomas, T, Penault-Llorca, F, Perera, RD, Pinard, CJ, Pinto-Cardenas, JC, Pruneri, G, Pusztai, L, Rajpoot, NM, Rapoport, BL, Rau, TT, Ribeiro, JM, Rimm, D, Vincent-Salomon, A, Saltz, J, Sayed, S, Hytopoulos, E, Mahon, S, Siziopikou, KP, Sotiriou, C, Stenzinger, A, Sughayer, MA, Sur, D, Symmans, F, Tanaka, S, Taxter, T, Tejpar, S, Teuwen, J, Thompson, EA, Tramm, T, Tran, WT, van Der Laak, J, Verghese, GE, Viale, G, Wahab, N, Walter, T, Waumans, Y, Wen, HY, Yang, W, Yuan, Y, Bartlett, J, Loibl, S, Denkert, C, Savas, P, Loi, S, Stovgaard, ES, Salgado, R, Gallagher, WM, Rahman, A, Jahangir, CA, Page, DB, Broeckx, G, Gonzalez, CA, Burke, C, Murphy, C, Reis-Filho, JS, Ly, A, Harms, PW, Gupta, RR, Vieth, M, Hida, A, Kahila, M, Kos, Z, van Diest, PJ, Verbandt, S, Thagaard, J, Khiroya, R, Abduljabbar, K, Haab, GA, Acs, B, Adams, S, Almeida, JS, Alvarado-Cabrero, I, Azmoudeh-Ardalan, F, Badve, S, Baharun, NB, Bellolio, ER, Bheemaraju, V, Blenman, KRM, Fujimoto, LBM, Burgues, O, Chardas, A, Cheang, MCU, Ciompi, F, Cooper, LAD, Coosemans, A, Corredor, G, Portela, FLD, Deman, F, Demaria, S, Dudgeon, SN, Elghazawy, M, Fernandez-Martin, C, Fineberg, S, Fox, SB, Giltnane, JM, Gnjatic, S, Gonzalez-Ericsson, P, Grigoriadis, A, Halama, N, Hanna, MG, Harbhajanka, A, Hart, SN, Hartman, J, Hewitt, S, Horlings, HM, Husain, Z, Irshad, S, Janssen, EAM, Kataoka, TR, Kawaguchi, K, Khramtsov, A, Kiraz, U, Kirtani, P, Kodach, LL, Korski, K, Akturk, G, Scott, E, Kovacs, A, Laenkholm, A-V, Lang-Schwarz, C, Larsimont, D, Lennerz, JK, Lerousseau, M, Li, X, Madabhushi, A, Maley, SK, Narasimhamurthy, VM, Marks, DK, McDonald, ES, Mehrotra, R, Michiels, S, Kharidehal, D, Minhas, FUAA, Mittal, S, Moore, DA, Mushtaq, S, Nighat, H, Papathomas, T, Penault-Llorca, F, Perera, RD, Pinard, CJ, Pinto-Cardenas, JC, Pruneri, G, Pusztai, L, Rajpoot, NM, Rapoport, BL, Rau, TT, Ribeiro, JM, Rimm, D, Vincent-Salomon, A, Saltz, J, Sayed, S, Hytopoulos, E, Mahon, S, Siziopikou, KP, Sotiriou, C, Stenzinger, A, Sughayer, MA, Sur, D, Symmans, F, Tanaka, S, Taxter, T, Tejpar, S, Teuwen, J, Thompson, EA, Tramm, T, Tran, WT, van Der Laak, J, Verghese, GE, Viale, G, Wahab, N, Walter, T, Waumans, Y, Wen, HY, Yang, W, Yuan, Y, Bartlett, J, Loibl, S, Denkert, C, Savas, P, Loi, S, Stovgaard, ES, Salgado, R, Gallagher, WM, and Rahman, A

Published
2024

2. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

Author

Thagaard, J, Broeckx, G, Page, DB, Jahangir, CA, Verbandt, S, Kos, Z, Gupta, R, Khiroya, R, Abduljabbar, K, Acosta Haab, G, Acs, B, Akturk, G, Almeida, JS, Alvarado-Cabrero, I, Amgad, M, Azmoudeh-Ardalan, F, Badve, S, Baharun, NB, Balslev, E, Bellolio, ER, Bheemaraju, V, Blenman, KRM, Botinelly Mendonca Fujimoto, L, Bouchmaa, N, Burgues, O, Chardas, A, Cheang, MU, Ciompi, F, Cooper, LAD, Coosemans, A, Corredor, G, Dahl, AB, Dantas Portela, FL, Deman, F, Demaria, S, Dore Hansen, J, Dudgeon, SN, Ebstrup, T, Elghazawy, M, Fernandez-Martin, C, Fox, SB, Gallagher, WM, Giltnane, JM, Gnjatic, S, Gonzalez-Ericsson, P, Grigoriadis, A, Halama, N, Hanna, MG, Harbhajanka, A, Hart, SN, Hartman, J, Hauberg, S, Hewitt, S, Hida, A, Horlings, HM, Husain, Z, Hytopoulos, E, Irshad, S, Janssen, EAM, Kahila, M, Kataoka, TR, Kawaguchi, K, Kharidehal, D, Khramtsov, A, Kiraz, U, Kirtani, P, Kodach, LL, Korski, K, Kovacs, A, Laenkholm, A-V, Lang-Schwarz, C, Larsimont, D, Lennerz, JK, Lerousseau, M, Li, X, Ly, A, Madabhushi, A, Maley, SK, Manur Narasimhamurthy, V, Marks, DK, McDonald, ES, Mehrotra, R, Michiels, S, Minhas, FUAA, Mittal, S, Moore, DA, Mushtaq, S, Nighat, H, Papathomas, T, Penault-Llorca, F, Perera, RD, Pinard, CJ, Pinto-Cardenas, JC, Pruneri, G, Pusztai, L, Rahman, A, Rajpoot, NM, Rapoport, BL, Rau, TT, Reis-Filho, JS, Ribeiro, JM, Rimm, D, Roslind, A, Vincent-Salomon, A, Salto-Tellez, M, Saltz, J, Sayed, S, Scott, E, Siziopikou, KP, Sotiriou, C, Stenzinger, A, Sughayer, MA, Sur, D, Fineberg, S, Symmans, F, Tanaka, S, Taxter, T, Tejpar, S, Teuwen, J, Thompson, EA, Tramm, T, Tran, WT, van Der Laak, J, van Diest, PJ, Verghese, GE, Viale, G, Vieth, M, Wahab, N, Walter, T, Waumans, Y, Wen, HY, Yang, W, Yuan, Y, Zin, RM, Adams, S, Bartlett, J, Loibl, S, Denkert, C, Savas, P, Loi, S, Salgado, R, Specht Stovgaard, E, Thagaard, J, Broeckx, G, Page, DB, Jahangir, CA, Verbandt, S, Kos, Z, Gupta, R, Khiroya, R, Abduljabbar, K, Acosta Haab, G, Acs, B, Akturk, G, Almeida, JS, Alvarado-Cabrero, I, Amgad, M, Azmoudeh-Ardalan, F, Badve, S, Baharun, NB, Balslev, E, Bellolio, ER, Bheemaraju, V, Blenman, KRM, Botinelly Mendonca Fujimoto, L, Bouchmaa, N, Burgues, O, Chardas, A, Cheang, MU, Ciompi, F, Cooper, LAD, Coosemans, A, Corredor, G, Dahl, AB, Dantas Portela, FL, Deman, F, Demaria, S, Dore Hansen, J, Dudgeon, SN, Ebstrup, T, Elghazawy, M, Fernandez-Martin, C, Fox, SB, Gallagher, WM, Giltnane, JM, Gnjatic, S, Gonzalez-Ericsson, P, Grigoriadis, A, Halama, N, Hanna, MG, Harbhajanka, A, Hart, SN, Hartman, J, Hauberg, S, Hewitt, S, Hida, A, Horlings, HM, Husain, Z, Hytopoulos, E, Irshad, S, Janssen, EAM, Kahila, M, Kataoka, TR, Kawaguchi, K, Kharidehal, D, Khramtsov, A, Kiraz, U, Kirtani, P, Kodach, LL, Korski, K, Kovacs, A, Laenkholm, A-V, Lang-Schwarz, C, Larsimont, D, Lennerz, JK, Lerousseau, M, Li, X, Ly, A, Madabhushi, A, Maley, SK, Manur Narasimhamurthy, V, Marks, DK, McDonald, ES, Mehrotra, R, Michiels, S, Minhas, FUAA, Mittal, S, Moore, DA, Mushtaq, S, Nighat, H, Papathomas, T, Penault-Llorca, F, Perera, RD, Pinard, CJ, Pinto-Cardenas, JC, Pruneri, G, Pusztai, L, Rahman, A, Rajpoot, NM, Rapoport, BL, Rau, TT, Reis-Filho, JS, Ribeiro, JM, Rimm, D, Roslind, A, Vincent-Salomon, A, Salto-Tellez, M, Saltz, J, Sayed, S, Scott, E, Siziopikou, KP, Sotiriou, C, Stenzinger, A, Sughayer, MA, Sur, D, Fineberg, S, Symmans, F, Tanaka, S, Taxter, T, Tejpar, S, Teuwen, J, Thompson, EA, Tramm, T, Tran, WT, van Der Laak, J, van Diest, PJ, Verghese, GE, Viale, G, Vieth, M, Wahab, N, Walter, T, Waumans, Y, Wen, HY, Yang, W, Yuan, Y, Zin, RM, Adams, S, Bartlett, J, Loibl, S, Denkert, C, Savas, P, Loi, S, Salgado, R, and Specht Stovgaard, E

Published
2023

3. Spatial analyses of immune cell infiltration in cancer: current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Author

Page, DB, Broeckx, G, Jahangir, CA, Jahangir, C, Verbandt, S, Gupta, RR, Thagaard, J, Khiroya, R, Kos, Z, Abduljabbar, K, Acosta Haab, G, Acs, B, Almeida, JS, Alvarado-Cabrero, I, Azmoudeh-Ardalan, F, Badve, S, Baharun, NB, Bellolio, ER, Bheemaraju, V, Blenman, KRM, Botinelly Mendonca Fujimoto, L, Burgues, O, Cheang, MCU, Ciompi, F, Cooper, LAD, Coosemans, A, Corredor, G, Dantas Portela, FL, Deman, F, Demaria, S, Dudgeon, SN, Elghazawy, M, Ely, S, Fernandez-Martin, C, Fineberg, S, Fox, SB, Gallagher, WM, Giltnane, JM, Gnjatic, S, Gonzalez-Ericsson, P, Grigoriadis, A, Halama, N, Hanna, MG, Harbhajanka, A, Hardas, A, Hart, SN, Hartman, J, Hewitt, S, Hida, A, Horlings, HM, Husain, Z, Hytopoulos, E, Irshad, S, Janssen, EAM, Kahila, M, Kataoka, TR, Kawaguchi, K, Kharidehal, D, Khramtsov, A, Kiraz, U, Kirtani, P, Kodach, LL, Korski, K, Kovacs, A, Laenkholm, A-V, Lang-Schwarz, C, Larsimont, D, Lennerz, JK, Lerousseau, M, Li, X, Ly, A, Madabhushi, A, Maley, SK, Manur Narasimhamurthy, V, Marks, DK, McDonald, ES, Mehrotra, R, Michiels, S, Minhas, FUAA, Mittal, S, Moore, DA, Mushtaq, S, Nighat, H, Papathomas, T, Penault-Llorca, F, Perera, RD, Pinard, CJ, Pinto-Cardenas, JC, Pruneri, G, Pusztai, L, Rahman, A, Rajpoot, NM, Rapoport, BL, Rau, TT, Reis-Filho, JS, Ribeiro, JM, Rimm, D, Salomon, A-V, Salto-Tellez, M, Saltz, J, Sayed, S, Siziopikou, KP, Sotiriou, C, Stenzinger, A, Sughayer, MA, Sur, D, Symmans, F, Tanaka, S, Taxter, T, Tejpar, S, Teuwen, J, Thompson, EA, Tramm, T, Tran, WT, van Der Laak, J, van Diest, PJ, Verghese, GE, Viale, G, Vieth, M, Wahab, N, Walter, T, Waumans, Y, Wen, HY, Yang, W, Yuan, Y, Adams, S, Bartlett, JMS, Loibl, S, Denkert, C, Savas, P, Loi, S, Salgado, R, Specht Stovgaard, E, Akturk, G, Bouchmaa, N, Page, DB, Broeckx, G, Jahangir, CA, Jahangir, C, Verbandt, S, Gupta, RR, Thagaard, J, Khiroya, R, Kos, Z, Abduljabbar, K, Acosta Haab, G, Acs, B, Almeida, JS, Alvarado-Cabrero, I, Azmoudeh-Ardalan, F, Badve, S, Baharun, NB, Bellolio, ER, Bheemaraju, V, Blenman, KRM, Botinelly Mendonca Fujimoto, L, Burgues, O, Cheang, MCU, Ciompi, F, Cooper, LAD, Coosemans, A, Corredor, G, Dantas Portela, FL, Deman, F, Demaria, S, Dudgeon, SN, Elghazawy, M, Ely, S, Fernandez-Martin, C, Fineberg, S, Fox, SB, Gallagher, WM, Giltnane, JM, Gnjatic, S, Gonzalez-Ericsson, P, Grigoriadis, A, Halama, N, Hanna, MG, Harbhajanka, A, Hardas, A, Hart, SN, Hartman, J, Hewitt, S, Hida, A, Horlings, HM, Husain, Z, Hytopoulos, E, Irshad, S, Janssen, EAM, Kahila, M, Kataoka, TR, Kawaguchi, K, Kharidehal, D, Khramtsov, A, Kiraz, U, Kirtani, P, Kodach, LL, Korski, K, Kovacs, A, Laenkholm, A-V, Lang-Schwarz, C, Larsimont, D, Lennerz, JK, Lerousseau, M, Li, X, Ly, A, Madabhushi, A, Maley, SK, Manur Narasimhamurthy, V, Marks, DK, McDonald, ES, Mehrotra, R, Michiels, S, Minhas, FUAA, Mittal, S, Moore, DA, Mushtaq, S, Nighat, H, Papathomas, T, Penault-Llorca, F, Perera, RD, Pinard, CJ, Pinto-Cardenas, JC, Pruneri, G, Pusztai, L, Rahman, A, Rajpoot, NM, Rapoport, BL, Rau, TT, Reis-Filho, JS, Ribeiro, JM, Rimm, D, Salomon, A-V, Salto-Tellez, M, Saltz, J, Sayed, S, Siziopikou, KP, Sotiriou, C, Stenzinger, A, Sughayer, MA, Sur, D, Symmans, F, Tanaka, S, Taxter, T, Tejpar, S, Teuwen, J, Thompson, EA, Tramm, T, Tran, WT, van Der Laak, J, van Diest, PJ, Verghese, GE, Viale, G, Vieth, M, Wahab, N, Walter, T, Waumans, Y, Wen, HY, Yang, W, Yuan, Y, Adams, S, Bartlett, JMS, Loibl, S, Denkert, C, Savas, P, Loi, S, Salgado, R, Specht Stovgaard, E, Akturk, G, and Bouchmaa, N

Published
2023

4. Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Author

Jahangir CA, Page DB, Broeckx G, Gonzalez CA, Burke C, Murphy C, Reis-Filho JS, Ly A, Harms PW, Gupta RR, Vieth M, Hida AI, Kahila M, Kos Z, van Diest PJ, Verbandt S, Thagaard J, Khiroya R, Abduljabbar K, Acosta Haab G, Acs B, Adams S, Almeida JS, Alvarado-Cabrero I, Azmoudeh-Ardalan F, Badve S, Baharun NB, Bellolio ER, Bheemaraju V, Blenman KR, Botinelly Mendonça Fujimoto L, Burgues O, Chardas A, Cheang MCU, Ciompi F, Cooper LA, Coosemans A, Corredor G, Dantas Portela FL, Deman F, Demaria S, Dudgeon SN, Elghazawy M, Fernandez-Martín C, Fineberg S, Fox SB, Giltnane JM, Gnjatic S, Gonzalez-Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hart SN, Hartman J, Hewitt S, Horlings HM, Husain Z, Irshad S, Janssen EA, Kataoka TR, Kawaguchi K, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Akturk G, Scott E, Kovács A, Laenkholm AV, Lang-Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Kharidehal D, Minhas FUAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault-Llorca F, Perera RD, Pinard CJ, Pinto-Cardenas JC, Pruneri G, Pusztai L, Rajpoot NM, Rapoport BL, Rau TT, Ribeiro JM, Rimm D, Vincent-Salomon A, Saltz J, Sayed S, Hytopoulos E, Mahon S, Siziopikou KP, Sotiriou C, Stenzinger A, Sughayer MA, Sur D, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson EA, Tramm T, Tran WT, van der Laak J, Verghese GE, Viale G, Wahab N, Walter T, Waumans Y, Wen HY, Yang W, Yuan Y, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Specht Stovgaard E, Salgado R, Gallagher WM, and Rahman A

Subjects
Humans, Female, Biomarkers, Tumor genetics, Prognosis, Phenotype, United Kingdom, Tumor Microenvironment, Breast Neoplasms
Abstract

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland., (© 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.)

Published
2024
Full Text
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5. Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Author

Page DB, Broeckx G, Jahangir CA, Verbandt S, Gupta RR, Thagaard J, Khiroya R, Kos Z, Abduljabbar K, Acosta Haab G, Acs B, Akturk G, Almeida JS, Alvarado-Cabrero I, Azmoudeh-Ardalan F, Badve S, Baharun NB, Bellolio ER, Bheemaraju V, Blenman KR, Botinelly Mendonça Fujimoto L, Bouchmaa N, Burgues O, Cheang MCU, Ciompi F, Cooper LA, Coosemans A, Corredor G, Dantas Portela FL, Deman F, Demaria S, Dudgeon SN, Elghazawy M, Ely S, Fernandez-Martín C, Fineberg S, Fox SB, Gallagher WM, Giltnane JM, Gnjatic S, Gonzalez-Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hardas A, Hart SN, Hartman J, Hewitt S, Hida AI, Horlings HM, Husain Z, Hytopoulos E, Irshad S, Janssen EA, Kahila M, Kataoka TR, Kawaguchi K, Kharidehal D, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Kovács A, Laenkholm AV, Lang-Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Ly A, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Minhas FUAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault-Llorca F, Perera RD, Pinard CJ, Pinto-Cardenas JC, Pruneri G, Pusztai L, Rahman A, Rajpoot NM, Rapoport BL, Rau TT, Reis-Filho JS, Ribeiro JM, Rimm D, Vincent-Salomon A, Salto-Tellez M, Saltz J, Sayed S, Siziopikou KP, Sotiriou C, Stenzinger A, Sughayer MA, Sur D, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson EA, Tramm T, Tran WT, van der Laak J, van Diest PJ, Verghese GE, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen HY, Yang W, Yuan Y, Adams S, Bartlett JMS, Loibl S, Denkert C, Savas P, Loi S, Salgado R, and Specht Stovgaard E

Subjects
Humans, Biomarkers, Benchmarking, Lymphocytes, Tumor-Infiltrating, Spatial Analysis, Tumor Microenvironment, Colonic Neoplasms
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., (© 2023 The Pathological Society of Great Britain and Ireland.)

Published
2023
Full Text
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6. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Author

Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, Gupta R, Khiroya R, Abduljabbar K, Acosta Haab G, Acs B, Akturk G, Almeida JS, Alvarado-Cabrero I, Amgad M, Azmoudeh-Ardalan F, Badve S, Baharun NB, Balslev E, Bellolio ER, Bheemaraju V, Blenman KR, Botinelly Mendonça Fujimoto L, Bouchmaa N, Burgues O, Chardas A, Chon U Cheang M, Ciompi F, Cooper LA, Coosemans A, Corredor G, Dahl AB, Dantas Portela FL, Deman F, Demaria S, Doré Hansen J, Dudgeon SN, Ebstrup T, Elghazawy M, Fernandez-Martín C, Fox SB, Gallagher WM, Giltnane JM, Gnjatic S, Gonzalez-Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hart SN, Hartman J, Hauberg S, Hewitt S, Hida AI, Horlings HM, Husain Z, Hytopoulos E, Irshad S, Janssen EA, Kahila M, Kataoka TR, Kawaguchi K, Kharidehal D, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Kovács A, Laenkholm AV, Lang-Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Ly A, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Minhas FUAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault-Llorca F, Perera RD, Pinard CJ, Pinto-Cardenas JC, Pruneri G, Pusztai L, Rahman A, Rajpoot NM, Rapoport BL, Rau TT, Reis-Filho JS, Ribeiro JM, Rimm D, Roslind A, Vincent-Salomon A, Salto-Tellez M, Saltz J, Sayed S, Scott E, Siziopikou KP, Sotiriou C, Stenzinger A, Sughayer MA, Sur D, Fineberg S, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson EA, Tramm T, Tran WT, van der Laak J, van Diest PJ, Verghese GE, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen HY, Yang W, Yuan Y, Zin RM, Adams S, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Salgado R, and Specht Stovgaard E

Subjects
Humans, Animals, Lymphocytes, Tumor-Infiltrating, Biomarkers, Machine Learning, Triple Negative Breast Neoplasms, Mammary Neoplasms, Animal
Abstract

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland., (© 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.)

Published
2023
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7. Tumor Immune Microenvironment and Response to Neoadjuvant Chemotherapy in Hormone Receptor/HER2+ Early Stage Breast Cancer.

Author

Vanguri RS, Fenn KM, Kearney MR, Wang Q, Guo H, Marks DK, Chin C, Alcus CF, Thompson JB, Leu CS, Hibshoosh H, Kalinsky KM, Mathews JC, Nadeem S, Hollmann TJ, and Connolly EP

Subjects
Antineoplastic Combined Chemotherapy Protocols therapeutic use, Biomarkers, Tumor genetics, Biomarkers, Tumor metabolism, Female, Forkhead Transcription Factors metabolism, Forkhead Transcription Factors therapeutic use, Hormones metabolism, Humans, Lymphocytes, Tumor-Infiltrating, Prognosis, Receptor, ErbB-2 metabolism, Tumor Microenvironment, Breast Neoplasms drug therapy, Breast Neoplasms genetics, Breast Neoplasms pathology, Neoadjuvant Therapy methods
Abstract

Background: Pathologic response at the time of surgery after neoadjuvant therapy for HER2 positive early breast cancer impacts both prognosis and subsequent adjuvant therapy. Comprehensive descriptions of the tumor microenvironment (TME) in patients with HER2 positive early breast cancer is not well described. We utilized standard stromal pathologist-assessed tumor infiltrating lymphocyte (TIL) quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting., Methods: We utilized standard stromal pathologist-assessed TIL quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in 28 patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting., Results: Pathologist-assessed stromal TILs were significantly associated with pathologic complete response (pCR). By quantitative multiplex immunofluorescence, univariate analysis revealed significant increases in CD3+, CD3+CD8-FOXP3-, CD8+ and FOXP3+ T-cell densities as well as increased immune cell aggregates in pCR patients. In subsets of paired pre/post-treatment samples, we observed significant changes in gene expression signatures in non-pCR patients and significant decreases in CD8+ densities after treatment in pCR patients. No RNA based pathway signature was associated with pCR., Conclusion: TME characterization HER2 positive breast cancer patients revealed several stromal T-cell densities and immune cell aggregates associated with pCR. These results demonstrate the feasibility of these novel methods in TME evaluation and contribute to ongoing investigations of the TME in HER2+ early breast cancer to identify robust biomarkers to best identify patients eligible for systemic de-escalation strategies., (Copyright © 2022. Published by Elsevier Inc.)

Published
2022
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8. Outcomes of Breast Cancer Patients Treated with Chemotherapy, Biologic Therapy, Endocrine Therapy, or Active Surveillance During the COVID-19 Pandemic.

Author

Marks DK, Budhathoki N, Kucharczyk J, Fa'ak F, D'Abreo N, Kwa M, Plasilova M, Dhage S, Soe PP, Becker D, Hindenburg A, Lee J, Winner M, Okpara C, Daly A, Shah D, Ramdhanny A, Meyers M, Oratz R, Speyer J, Novik Y, Schnabel F, Jones SA, and Adams S

Subjects
Biological Therapy, COVID-19 Testing, Female, Humans, Pandemics, SARS-CoV-2, Watchful Waiting, Breast Neoplasms drug therapy, COVID-19 epidemiology
Abstract

Purpose: Provide real-world data regarding the risk for SARS-CoV-2 infection and mortality in breast cancer (BC) patients on active cancer treatment., Methods: Clinical data were abstracted from the 3778 BC patients seen at a multisite cancer center in New York between February 1, 2020 and May 1, 2020, including patient demographics, tumor histology, cancer treatment, and SARS-CoV-2 testing results. Incidence of SARS-CoV-2 infection by treatment type (chemotherapy [CT] vs endocrine and/or HER2 directed therapy [E/H]) was compared by Inverse Probability of Treatment Weighting. In those diagnosed with SARS-CoV-2 infection, Mann-Whitney test was used to a assess risk factors for severe disease and mortality., Results: Three thousand sixty-two patients met study inclusion criteria with 641 patients tested for SARS-COV-2 by RT-PCR or serology. Overall, 64 patients (2.1%) were diagnosed with SARS-CoV-2 infection by either serology, RT-PCR, or documented clinical diagnosis. Comparing matched patients who received chemotherapy (n = 379) with those who received non-cytotoxic therapies (n = 2343) the incidence of SARS-CoV-2 did not differ between treatment groups (weighted risk; 3.5% CT vs 2.7% E/H, P = .523). Twenty-seven patients (0.9%) expired over follow-up, with 10 deaths attributed to SARS-CoV-2 infection. Chemotherapy was not associated with increased risk for death following SARS-CoV-2 infection (weighted risk; 0.7% CT vs 0.1% E/H, P = .246). Advanced disease (stage IV), age, BMI, and Charlson's Comorbidity Index score were associated with increased mortality following SARS-CoV-2 infection (P ≤ .05)., Conclusion: BC treatment, including chemotherapy, can be safely administered in the context of enhanced infectious precautions, and should not be withheld particularly when given for curative intent., (© The Author(s) 2022. Published by Oxford University Press.)

Published
2022
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