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

Publication

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

Journal Paper/Review - Jun 7, 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

Citation

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.

Type

Journal Paper/Review (English)

Journal

EBioMedicine 2023; 93

Publication Date

Jun 7, 2023

Issn Electronic

2352-3964

Pages

104644

Brief description/objective

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.