Abstract 1671: Characterization of the immune landscape in stage II-III melanoma using qIF
Authors: Gartrell Robyn , Marks Douglas , Stack Edward C. , Lu Yan , Hart Thomas D. , Gerard Camille , Esancy Camden , Jia Dan Tong , Armenta Paul , Izaki Daisuke , Davari Danielle , White-Stern Ashley , Blake Zoe , Fu Yichun , Horst Basil , Saenger Yvonne 
Published: July 2017

Abstract
Background: The tumor microenvironment plays a crucial role in cancer progression, often supporting immune evasion. This is of particular importance in melanoma, where immune checkpoint therapies have resulted in significant clinical benefit, yet only in a subset of melanoma patients respond. Precise biomarkers are urgently needed to characterize the tumor immune micro-environment, both for prognostication and to predict the benefit of immuno-therapeutic intervention. HLA-DR on tumor cells and Ki67 on cytotoxic (CD8+) T cells have been proposed as biomarkers of anti-PD1 activity. Quantitative immunofluorescence (qIF) allows for automated quantitation of phenotypes and spatial distributions of immune cell populations within formalin fixed paraffin embedded (FFPE) tissues.
Methods: To characterize the tumor immune microenvironment, we screened databases at the Herbert Irving Cancer Center (HICC) at Columbia University for early stage melanoma patients with documented clinical follow up. We identified a preliminary population of 40 stage II-III melanoma patients diagnosed between 2000 and 2012. Clinical follow up was available on 21 patients, 12 of whom were alive with no evidence of recurrence, 1 who died of another malignancy, and 8 who died of melanoma. 19 patients had more than 24 months of survival information available but no detailed clinical information. 5µm slides from either primary biopsy or subsequent wide local excision procedure were stained using qIF for DAPI, CD3, CD8, CD68, SOX10, HLA-DR and Ki67. Cell phenotypes within representative fields selected by a trained dermatopathologist (BH), were visualized using multispectral imaging, and analysis of spatial distribution of cells were analyzed using inForm image analysis software (Perkin Elmer), and Spotfire software (TIBCO).
Results: We were able to quantify and identify coordinates for multiple immune cell subsets in melanoma tissues. In 21 patients with clinical follow up, we found that higher densities of CD3+CD8+ T cells in tumor and stroma trended towards correlation with non-recurrence. In addition, CD68+HLA-DR- predicts poor prognosis (p&lt;0.05), whether in tumor or stroma. Assessment of spatial distribution across all 40 tumors demonstrated that CD3+CD8+ cells are closer to CD68+ cells and Sox10+ tumor cells when they express HLA-DR (p&lt;0.001). Conversely, CD3+CD8+ cells are significantly farther from tumor cells when they express Ki-67, (p&lt;0.001). Among patients with clinical follow up, CD3+CD8+ cells were closer to CD68+HLA-DR- cells in recurrent patients (p &lt; 0.05).
Conclusion: Using qIF imaging and analysis we find that density and spatial relationships of immune cell subsets correlates with recurrence status. qIF may offer the potential for the development of prognostic biomarkers in stage II/III melanoma.
Citation Format: Robyn Gartrell, Douglas Marks, Edward C. Stack, Yan Lu, Thomas D. Hart, Camille Gerard, Camden Esancy, Dan Tong Jia, Paul Armenta, Daisuke Izaki, Danielle Davari, Ashley White-Stern, Zoe Blake, Yichun Fu, Basil Horst, Yvonne Saenger. Characterization of the immune landscape in stage II-III melanoma using qIF [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1671. doi:10.1158/1538-7445.AM2017-1671