Quantitative Analysis of Immune Infiltrates in Primary Melanoma

Abstract

Novel methods to analyze the tumor microenvironment (TME) are urgently needed to stratify melanoma patients for adjuvant immunotherapy. Tumor-infiltrating lymphocyte (TIL) analysis, by conventional pathologic methods, is predictive but is insufficiently precise for clinical application. Quantitative multiplex immunofluorescence (qmIF) allows for evaluation of the TME using multiparameter phenotyping, tissue segmentation, and quantitative spatial analysis (qSA). Given that CD3CD8 cytotoxic lymphocytes (CTLs) promote antitumor immunity, whereas CD68 macrophages impair immunity, we hypothesized that quantification and spatial analysis of macrophages and CTLs would correlate with clinical outcome. We applied qmIF to 104 primary stage II to III melanoma tumors and found that CTLs were closer in proximity to activated (CD68HLA-DR) macrophages than nonactivated (CD68HLA-DR) macrophages ( < 0.0001). CTLs were further in proximity from proliferating SOX10 melanoma cells than nonproliferating ones ( < 0.0001). In 64 patients with known cause of death, we found that high CTL and low macrophage density in the stroma ( = 0.0038 and = 0.0006, respectively) correlated with disease-specific survival (DSS), but the correlation was less significant for CTL and macrophage density in the tumor ( = 0.0147 and = 0.0426, respectively). DSS correlation was strongest for stromal HLA-DR CTLs ( = 0.0005). CTL distance to HLA-DR macrophages associated with poor DSS ( = 0.0016), whereas distance to Ki67 tumor cells associated inversely with DSS ( = 0.0006). A low CTL/macrophage ratio in the stroma conferred a hazard ratio (HR) of 3.719 for death from melanoma and correlated with shortened overall survival (OS) in the complete 104 patient cohort by Cox analysis ( = 0.009) and merits further development as a biomarker for clinical application. .

Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II–III Melanoma

“…The immunoscore, consisting of a more precise quantification of CD8 þ T cells within the tumor microenvironment, has been proposed as a biomarker in multiple tumor types (34)(35)(36). Recently, we have found that the ratio of CD8 þ T cells to CD68 þ macrophages in the stroma confers a favorable prognosis in a single patient cohort of stage II-III melanoma patients (37). Histopathologic as well as genomic assessments of the tumor immune microenvironment are likely to provide useful prognostic information in early-stage melanoma, and a combined biomarker including a more quantitative assessment of TILs will likely have application in the clinical setting.…”

Trained Immunity for Personalized Cancer Immunotherapy: Current Knowledge and Future Opportunities

“…The TAMs can be originated from circulating monocytes that will enter the tissue and differentiate into macrophages, bone-marrow-derived macrophages (BMDMs) or can result from an accumulation of tissueresident macrophages (TRMs) (Pathria et al, 2019). Indeed, there is a crescent number of reports correlating TAMs with higher tumor grade and shorter survival for breast cancer, renal cell carcinoma, glioblastoma, pancreatic cancer, head and neck cancer, and lymphoma (Zhang et al, 2013(Zhang et al, , 2018Pedersen et al, 2014;Tiainen et al, 2015;Wang et al, 2015;Hu et al, 2016;Atanasov et al, 2018;Gartrell et al, 2018;Sorensen et al, 2018;Pathria et al, 2019). The relationship between TAMs and the tumor invasiveness and ability to metastasis is suggested to be related to epithelial-mesenchymal transition (EMT) (Su et al, 2014;Fu et al, 2015;Ravi et al, 2016).…”

Tumor-Immune Partitioning and Clustering (TIPC) algorithm reveals distinct signatures of tumor-immune cell interactions within the tumor microenvironment

“…Importantly, TIPC performance was robust to the choice of immune cell types, detection methods and parameter settings. Besides CD3 + T-cell, using a more specific CD3 + CD8 + CD45RO + T-cell subset 21,22 and two innate immune cell types i.e. eosinophils and neutrophils, TIPC was still able to determine prognostic spatial subtypes.…”