A Multi-Omics Analysis of Metastatic Melanoma Identifies a Germinal Center-Like Tumor Microenvironment in HLA-DR-Positive Tumor Areas

Abstract

The emergence of immune checkpoint inhibitors has dramatically changed the therapeutic landscape for patients with advanced melanoma. However, relatively low response rates and a high incidence of severe immune-related adverse events have prompted the search for predictive biomarkers. A positive predictive value has been attributed to the aberrant expression of Human Leukocyte Antigen-DR (HLA-DR) by melanoma cells, but it remains unknown why this is the case. In this study, we have examined the microenvironment of HLA-DR positive metastatic melanoma samples using a multi-omics approach. First, using spatial, single-cell mapping by multiplexed immunohistochemistry, we found that the microenvironment of HLA-DR positive melanoma regions was enriched by professional antigen presenting cells, including classical dendritic cells and macrophages, while a more general cytotoxic T cell exhaustion phenotype was present in these regions. In parallel, transcriptomic analysis on micro dissected tissue from HLA-DR positive and HLA-DR negative areas showed increased IFNγ signaling, enhanced leukocyte adhesion and mononuclear cell proliferation in HLA-DR positive areas. Finally, multiplexed cytokine profiling identified an increased expression of germinal center cytokines CXCL12, CXCL13 and CCL19 in HLA-DR positive metastatic lesions, which, together with IFNγ and IL4 could serve as biomarkers to discriminate tumor samples containing HLA-DR overexpressing tumor cells from HLA-DR negative samples. Overall, this suggests that HLA-DR positive areas in melanoma attract the anti-tumor immune cell infiltration by creating a dystrophic germinal center-like microenvironment where an enhanced antigen presentation leads to an exhausted microenvironment, nevertheless representing a fertile ground for a better efficacy of anti-PD-1 inhibitors due to simultaneous higher levels of PD-1 in the immune cells and PD-L1 in the HLA-DR positive melanoma cells.

Transcriptional landscape in BRAF wild type metastatic melanoma

“…GSEA and ToppFun functional enrichment analysis of upregulated DEGs showed a consistent involvement of the immune system, with 70% of the overexpressed genes coherently annotated to some immune response-related process. This is in line with the well-known immunogenic nature of melanoma and the recent literature pointing at MHC-I/II protein expression as a powerful prognostic marker to predict the effectiveness of anti-CTLA-4 and anti-PD-1 immunotherapy in metastatic melanoma and other cancer types [18][19][20][21][22].…”

The Transcriptional Landscape of BRAF Wild Type Metastatic Melanoma: A Pilot Study

“…The GSEA and ToppFun functional enrichment analysis of the upregulated DEGs showed a consistent involvement of the immune system, with 70% of the overexpressed genes coherently annotated to some immune response-related process. This is in line with the well-known immunogenic nature of melanoma and the recent literature pointing at MHC-I/II protein expression as a powerful prognostic marker to predict the effectiveness of anti-CTLA-4 and anti-PD-1 immunotherapy in metastatic melanoma and other cancer types [24][25][26][27][28]. Even though most of these papers agree on the fact that a transcriptional downregulation of the MHC-I and MHC-II genes is a common feature of advanced untreated melanomas, in our study, the opposite seems to be true.…”

The spatial landscape of progression and immunoediting in primary melanoma at single cell resolution

“… (F) Shift plot shows the distance between melanocytes and CTLs, PDL1 + myeloid cells, and Tregs in normal (top) and precursor (bottom) regions. Significance is calculated for each percentile (10, 20, 30, 40, 50, 60, 70, 80, 90) using the robust Harrell-Davis quantile estimator. Red indicates a significant difference (P <0.05) and grey represents non-significance for each percentile.…”

“…To estimate the frequency of such interactions, we performed a detailed inspection of two high-resolution FOVs lying at the tumor-stroma interface. A total of 199 cells (15 PDL1 + macrophages and 64 PD1 + T cells) were identified; in 58 cases these cells were judged to be within 20 µm of each other (a commonly used cutoff for proximity analysis) (40). In total, 21 immune cells (27%) had morphologies consistent with polarized PD1-PDL1 interaction.…”