Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma

Jan Malte Placke; Camille Soun; Jenny Bottek; Rudolf Herbst; Patrick Terheyden; Jochen Utikal; Claudia Pföhler; Jens Ulrich; Alexander Kreuter; Christiane Pfeiffer; Peter Mohr; Ralf Gutzmer; Friedegund Meier; Edgar Dippel; Michael Weichenthal; Lisa Zimmer; Elisabeth Livingstone; Jürgen C. Becker; Georg Lodde; Antje Sucker; Klaus Griewank; Susanne Horn; Eva Hadaschik; Alexander Roesch; Dirk Schadendorf; Daniel Robert Engel; Selma Ugurel

doi:10.3389/fonc.2021.741993

Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma

Jan Malte Placke^*, Camille Soun, Jenny Bottek, Rudolf Herbst, Patrick Terheyden, Jochen Utikal, Claudia Pföhler, Jens Ulrich, Alexander Kreuter, Christiane Pfeiffer, Peter Mohr, Ralf Gutzmer, Friedegund Meier, Edgar Dippel, Michael Weichenthal, Lisa Zimmer, Elisabeth Livingstone, Jürgen C. Becker, Georg Lodde, Antje SuckerKlaus Griewank, Susanne Horn, Eva Hadaschik, Alexander Roesch, Dirk Schadendorf, Daniel Robert Engel, Selma Ugurel

^*Corresponding author for this work

Clinic of Dermatology, Allergology and Venerology

9 Citations (Scopus)

Abstract

Background: PD-1-based immune checkpoint blockade (ICB) is a highly effective therapy in metastatic melanoma. However, 40-60% of patients are primarily resistant, with valid predictive biomarkers currently missing. This study investigated the digitally quantified tumor PD-L1 expression for ICB therapy outcome prediction. Patients and Methods: Tumor tissues taken prior to PD-1-based ICB for unresectable metastatic disease were collected within the prospective multicenter Tissue Registry in Melanoma (TRIM). PD-L1 expression (clone 28-8; cut-off=5%) was determined by digital and physician quantification, and correlated with therapy outcome (best overall response, BOR; progression-free survival, PFS; overall survival, OS). Results: Tissue samples from 156 patients were analyzed (anti-PD-1, n=115; anti-CTLA-4+anti-PD-1, n=41). Patients with PD-L1-positive tumors showed an improved response compared to patients with PD-L1-negative tumors, by digital (BOR 50.5% versus 32.2%; p=0.026) and physician (BOR 54.2% versus 36.6%; p=0.032) quantification. Tumor PD-L1 positivity was associated with a prolonged PFS and OS by either digital (PFS, 9.9 versus 4.6 months, p=0.021; OS, not reached versus 13.0 months, p=0.001) or physician (PFS, 10.6 versus 5.6 months, p=0.051; OS, not reached versus 15.6 months, p=0.011) quantification. Multivariable Cox regression revealed digital (PFS, HR=0.57, p=0.007; OS, HR=0.44, p=0.001) and physician (OS, HR=0.54, p=0.016) PD-L1 quantification as independent predictors of survival upon PD-1-based ICB. The combination of both methods identified a patient subgroup with particularly favorable therapy outcome (PFS, HR=0.53, p=0.011; OS, HR=0.47, p=0.008). Conclusion: Pre-treatment tumor PD-L1 positivity predicted a favorable outcome of PD-1-based ICB in melanoma. Herein, digital quantification was not inferior to physician quantification, and should be further validated for clinical use.

Original language	English
Article number	741993
Journal	Frontiers in Oncology
Volume	11
ISSN	2234-943X
DOIs	https://doi.org/10.3389/fonc.2021.741993
Publication status	Published - 21.09.2021

Funding

This work was in part supported by Bristol Myers Squibb for the multicenter translational study “Tissue Registry in Melanoma” (TRIM) within the framework of the skin cancer registry ADOREG of the German Dermatologic Cooperative Oncology Group (DeCOG).

Research Areas and Centers

Academic Focus: Center for Infection and Inflammation Research (ZIEL)
Research Area: Luebeck Integrated Oncology Network (LION)
Centers: University Cancer Center Schleswig-Holstein (UCCSH)

DFG Research Classification Scheme

2.22-19 Dermatology
2.21-05 Immunology
2.22-14 Hematology, Oncology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3389/fonc.2021.741993

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Placke, J. M., Soun, C., Bottek, J., Herbst, R., Terheyden, P., Utikal, J., Pföhler, C., Ulrich, J., Kreuter, A., Pfeiffer, C., Mohr, P., Gutzmer, R., Meier, F., Dippel, E., Weichenthal, M., Zimmer, L., Livingstone, E., Becker, J. C., Lodde, G., ... Ugurel, S. (2021). Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma. Frontiers in Oncology, 11, Article 741993. https://doi.org/10.3389/fonc.2021.741993

@article{67711446e3f446c89d84c5eabd1767d0,

title = "Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma",

abstract = "Background: PD-1-based immune checkpoint blockade (ICB) is a highly effective therapy in metastatic melanoma. However, 40-60\% of patients are primarily resistant, with valid predictive biomarkers currently missing. This study investigated the digitally quantified tumor PD-L1 expression for ICB therapy outcome prediction. Patients and Methods: Tumor tissues taken prior to PD-1-based ICB for unresectable metastatic disease were collected within the prospective multicenter Tissue Registry in Melanoma (TRIM). PD-L1 expression (clone 28-8; cut-off=5\%) was determined by digital and physician quantification, and correlated with therapy outcome (best overall response, BOR; progression-free survival, PFS; overall survival, OS). Results: Tissue samples from 156 patients were analyzed (anti-PD-1, n=115; anti-CTLA-4+anti-PD-1, n=41). Patients with PD-L1-positive tumors showed an improved response compared to patients with PD-L1-negative tumors, by digital (BOR 50.5\% versus 32.2\%; p=0.026) and physician (BOR 54.2\% versus 36.6\%; p=0.032) quantification. Tumor PD-L1 positivity was associated with a prolonged PFS and OS by either digital (PFS, 9.9 versus 4.6 months, p=0.021; OS, not reached versus 13.0 months, p=0.001) or physician (PFS, 10.6 versus 5.6 months, p=0.051; OS, not reached versus 15.6 months, p=0.011) quantification. Multivariable Cox regression revealed digital (PFS, HR=0.57, p=0.007; OS, HR=0.44, p=0.001) and physician (OS, HR=0.54, p=0.016) PD-L1 quantification as independent predictors of survival upon PD-1-based ICB. The combination of both methods identified a patient subgroup with particularly favorable therapy outcome (PFS, HR=0.53, p=0.011; OS, HR=0.47, p=0.008). Conclusion: Pre-treatment tumor PD-L1 positivity predicted a favorable outcome of PD-1-based ICB in melanoma. Herein, digital quantification was not inferior to physician quantification, and should be further validated for clinical use.",

author = "Placke, \{Jan Malte\} and Camille Soun and Jenny Bottek and Rudolf Herbst and Patrick Terheyden and Jochen Utikal and Claudia Pf{\"o}hler and Jens Ulrich and Alexander Kreuter and Christiane Pfeiffer and Peter Mohr and Ralf Gutzmer and Friedegund Meier and Edgar Dippel and Michael Weichenthal and Lisa Zimmer and Elisabeth Livingstone and Becker, \{J{\"u}rgen C.\} and Georg Lodde and Antje Sucker and Klaus Griewank and Susanne Horn and Eva Hadaschik and Alexander Roesch and Dirk Schadendorf and Engel, \{Daniel Robert\} and Selma Ugurel",

note = "Publisher Copyright: {\textcopyright} Copyright {\textcopyright} 2021 Placke, Soun, Bottek, Herbst, Terheyden, Utikal, Pf{\"o}hler, Ulrich, Kreuter, Pfeiffer, Mohr, Gutzmer, Meier, Dippel, Weichenthal, Zimmer, Livingstone, Becker, Lodde, Sucker, Griewank, Horn, Hadaschik, Roesch, Schadendorf, Engel and Ugurel.",

year = "2021",

month = sep,

day = "21",

doi = "10.3389/fonc.2021.741993",

language = "English",

volume = "11",

journal = "Frontiers in Oncology",

issn = "2234-943X",

}

Placke, JM, Soun, C, Bottek, J, Herbst, R, Terheyden, P, Utikal, J, Pföhler, C, Ulrich, J, Kreuter, A, Pfeiffer, C, Mohr, P, Gutzmer, R, Meier, F, Dippel, E, Weichenthal, M, Zimmer, L, Livingstone, E, Becker, JC, Lodde, G, Sucker, A, Griewank, K, Horn, S, Hadaschik, E, Roesch, A, Schadendorf, D, Engel, DR & Ugurel, S 2021, 'Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma', Frontiers in Oncology, vol. 11, 741993. https://doi.org/10.3389/fonc.2021.741993

TY - JOUR

T1 - Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma

AU - Placke, Jan Malte

AU - Soun, Camille

AU - Bottek, Jenny

AU - Herbst, Rudolf

AU - Terheyden, Patrick

AU - Utikal, Jochen

AU - Pföhler, Claudia

AU - Ulrich, Jens

AU - Kreuter, Alexander

AU - Pfeiffer, Christiane

AU - Mohr, Peter

AU - Gutzmer, Ralf

AU - Meier, Friedegund

AU - Dippel, Edgar

AU - Weichenthal, Michael

AU - Zimmer, Lisa

AU - Livingstone, Elisabeth

AU - Becker, Jürgen C.

AU - Lodde, Georg

AU - Sucker, Antje

AU - Griewank, Klaus

AU - Horn, Susanne

AU - Hadaschik, Eva

AU - Roesch, Alexander

AU - Schadendorf, Dirk

AU - Engel, Daniel Robert

AU - Ugurel, Selma

N1 - Publisher Copyright: © Copyright © 2021 Placke, Soun, Bottek, Herbst, Terheyden, Utikal, Pföhler, Ulrich, Kreuter, Pfeiffer, Mohr, Gutzmer, Meier, Dippel, Weichenthal, Zimmer, Livingstone, Becker, Lodde, Sucker, Griewank, Horn, Hadaschik, Roesch, Schadendorf, Engel and Ugurel.

PY - 2021/9/21

Y1 - 2021/9/21

N2 - Background: PD-1-based immune checkpoint blockade (ICB) is a highly effective therapy in metastatic melanoma. However, 40-60% of patients are primarily resistant, with valid predictive biomarkers currently missing. This study investigated the digitally quantified tumor PD-L1 expression for ICB therapy outcome prediction. Patients and Methods: Tumor tissues taken prior to PD-1-based ICB for unresectable metastatic disease were collected within the prospective multicenter Tissue Registry in Melanoma (TRIM). PD-L1 expression (clone 28-8; cut-off=5%) was determined by digital and physician quantification, and correlated with therapy outcome (best overall response, BOR; progression-free survival, PFS; overall survival, OS). Results: Tissue samples from 156 patients were analyzed (anti-PD-1, n=115; anti-CTLA-4+anti-PD-1, n=41). Patients with PD-L1-positive tumors showed an improved response compared to patients with PD-L1-negative tumors, by digital (BOR 50.5% versus 32.2%; p=0.026) and physician (BOR 54.2% versus 36.6%; p=0.032) quantification. Tumor PD-L1 positivity was associated with a prolonged PFS and OS by either digital (PFS, 9.9 versus 4.6 months, p=0.021; OS, not reached versus 13.0 months, p=0.001) or physician (PFS, 10.6 versus 5.6 months, p=0.051; OS, not reached versus 15.6 months, p=0.011) quantification. Multivariable Cox regression revealed digital (PFS, HR=0.57, p=0.007; OS, HR=0.44, p=0.001) and physician (OS, HR=0.54, p=0.016) PD-L1 quantification as independent predictors of survival upon PD-1-based ICB. The combination of both methods identified a patient subgroup with particularly favorable therapy outcome (PFS, HR=0.53, p=0.011; OS, HR=0.47, p=0.008). Conclusion: Pre-treatment tumor PD-L1 positivity predicted a favorable outcome of PD-1-based ICB in melanoma. Herein, digital quantification was not inferior to physician quantification, and should be further validated for clinical use.

AB - Background: PD-1-based immune checkpoint blockade (ICB) is a highly effective therapy in metastatic melanoma. However, 40-60% of patients are primarily resistant, with valid predictive biomarkers currently missing. This study investigated the digitally quantified tumor PD-L1 expression for ICB therapy outcome prediction. Patients and Methods: Tumor tissues taken prior to PD-1-based ICB for unresectable metastatic disease were collected within the prospective multicenter Tissue Registry in Melanoma (TRIM). PD-L1 expression (clone 28-8; cut-off=5%) was determined by digital and physician quantification, and correlated with therapy outcome (best overall response, BOR; progression-free survival, PFS; overall survival, OS). Results: Tissue samples from 156 patients were analyzed (anti-PD-1, n=115; anti-CTLA-4+anti-PD-1, n=41). Patients with PD-L1-positive tumors showed an improved response compared to patients with PD-L1-negative tumors, by digital (BOR 50.5% versus 32.2%; p=0.026) and physician (BOR 54.2% versus 36.6%; p=0.032) quantification. Tumor PD-L1 positivity was associated with a prolonged PFS and OS by either digital (PFS, 9.9 versus 4.6 months, p=0.021; OS, not reached versus 13.0 months, p=0.001) or physician (PFS, 10.6 versus 5.6 months, p=0.051; OS, not reached versus 15.6 months, p=0.011) quantification. Multivariable Cox regression revealed digital (PFS, HR=0.57, p=0.007; OS, HR=0.44, p=0.001) and physician (OS, HR=0.54, p=0.016) PD-L1 quantification as independent predictors of survival upon PD-1-based ICB. The combination of both methods identified a patient subgroup with particularly favorable therapy outcome (PFS, HR=0.53, p=0.011; OS, HR=0.47, p=0.008). Conclusion: Pre-treatment tumor PD-L1 positivity predicted a favorable outcome of PD-1-based ICB in melanoma. Herein, digital quantification was not inferior to physician quantification, and should be further validated for clinical use.

UR - https://www.scopus.com/pages/publications/85116499494

U2 - 10.3389/fonc.2021.741993

DO - 10.3389/fonc.2021.741993

M3 - Journal articles

AN - SCOPUS:85116499494

SN - 2234-943X

VL - 11

JO - Frontiers in Oncology

JF - Frontiers in Oncology

M1 - 741993

ER -

Digital Quantification of Tumor PD-L1 Predicts Outcome of PD-1-Based Immune Checkpoint Therapy in Metastatic Melanoma

Abstract

Funding

Research Areas and Centers

DFG Research Classification Scheme

UN SDGs

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