Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases.

Publikation

Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases.

Wissenschaftlicher Artikel/Review - 07.06.2023

Chatziioannou Eftychia, Roßner Jana, Aung Thazin New, Rimm David L, Niessner Heike, Keim Ulrike, Serna-Higuita Lina María, Bonzheim Irina, Kuhn Cuellar Luis, Westphal Dana, Steininger Julian, Meier Friedegund, Pop Oltin Tiberiu, Forchhammer Stephan, Flatz Lukas, Eigentler Thomas Kurt, Garbe Claus, Röcken Martin, Amaral Teresa, Sinnberg Tobias

Zitation

Chatziioannou E, Roßner J, Aung T, Rimm D, Niessner H, Keim U, Serna-Higuita L, Bonzheim I, Kuhn Cuellar L, Westphal D, Steininger J, Meier F, Pop O, Forchhammer S, Flatz L, Eigentler T, Garbe C, Röcken M, Amaral T, Sinnberg T. Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases. EBioMedicine 2023; 93:104644.

Art

Wissenschaftlicher Artikel/Review (Englisch)

Zeitschrift

EBioMedicine 2023; 93

Veröffentlichungsdatum

07.06.2023

eISSN (Online)

2352-3964

Seiten

104644

Kurzbeschreibung/Zielsetzung

Recent advances in digital pathology have enabled accurate and standardised enumeration of tumour-infiltrating lymphocytes (TILs). Here, we aim to evaluate TILs as a percentage electronic TIL score (eTILs) and investigate its prognostic and predictive relevance in cutaneous melanoma.