Classification of the tumor immune microenvironment and associations with outcomes in patients with metastatic melanoma treated with immunotherapies

Nurudeen A Adegoke; Tuba N Gide; Yizhe Mao; Camelia Quek; Ellis Patrick; Matteo S Carlino; Serigne N Lo; Alexander Maxwell Menzies; Ines Pires da Silva; Ismael A Vergara; Georgina Long; Richard A Scolyer; James S Wilmott

doi:10.1136/jitc-2023-007144

Classification of the tumor immune microenvironment and associations with outcomes in patients with metastatic melanoma treated with immunotherapies

J Immunother Cancer. 2023 Oct;11(10):e007144. doi: 10.1136/jitc-2023-007144.

Authors

Nurudeen A Adegoke^{1

2}, Tuba N Gide^{1

2}, Yizhe Mao^{1

2}, Camelia Quek^{1

2}, Ellis Patrick^{3

4}, Matteo S Carlino^{1

5}, Serigne N Lo^{1

2}, Alexander Maxwell Menzies^{1

6}, Ines Pires da Silva^{1

5}, Ismael A Vergara^{1

2}, Georgina Long^{1

6}, Richard A Scolyer^{1

7}, James S Wilmott^{8

2}

Affiliations

¹ Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
² Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
³ Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia.
⁴ School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.
⁵ Westmead and Blacktown Hospitals, Sydney, New South Wales, Australia.
⁶ Royal North Shore and Mater Hospitals, Sydney, New South Wales, Australia.
⁷ Department of Tissue Oncology and Diagnostic Pathology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, New South Wales, Australia.
⁸ Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia james.wilmott@sydney.edu.au.

Abstract

Background: Tumor microenvironment (TME) characteristics are potential biomarkers of response to immune checkpoint inhibitors in metastatic melanoma. This study developed a method to perform unsupervised classification of TME of metastatic melanoma.

Methods: We used multiplex immunohistochemical and quantitative pathology-derived assessment of immune cell compositions of intratumoral and peritumoral regions of metastatic melanoma baseline biopsies to classify TME in relation to response to anti-programmed cell death protein 1 (PD-1) monotherapy or in combination with anti-cytotoxic T-cell lymphocyte-4 (ipilimumab (IPI)+PD-1).

Results: Spatial profiling of CD8+T cells, macrophages, and melanoma cells, as well as phenotypic PD-1 receptor ligand (PD-L1) and CD16 proportions, were used to identify and classify patients into one of three mutually exclusive TME classes: immune-scarce, immune-intermediate, and immune-rich tumors. Patients with immune-rich tumors were characterized by a lower proportion of melanoma cells and higher proportions of immune cells, including higher PD-L1 expression. These patients had higher response rates and longer progression-free survival (PFS) than those with immune-intermediate and immune-scarce tumors. At a median follow-up of 18 months (95% CI: 6.7 to 49 months), the 1-year PFS was 76% (95% CI: 64% to 90%) for patients with an immune-rich tumor, 56% (95% CI: 44% to 72%) for those with an immune-intermediate tumor, and 33% (95% CI: 23% to 47%) for patients with an immune-scarce tumor. A higher response rate was observed in patients with an immune-scarce or immune-intermediate tumor when treated with IPI+PD-1 compared with those treated with PD-1 alone.

Conclusions: Our study provides an automatic TME classification method that may predict the clinical efficacy of immunotherapy for patients with metastatic melanoma.

Keywords: Immunotherapy; Melanoma; PATHOLOGY; Tumor Microenvironment.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

B7-H1 Antigen*
Humans
Immunotherapy / methods
Ipilimumab / therapeutic use
Melanoma* / drug therapy
Programmed Cell Death 1 Receptor
Tumor Microenvironment

Substances

B7-H1 Antigen
Programmed Cell Death 1 Receptor
Ipilimumab