Abstract B005: Linking transcriptomic and imaging features of the melanoma tumor microenvironment
Authors: Chen Andrew X. , Gartrell Robyn , Marks Douglas K. , Hart Thomas , Rizk Emanuelle , Monod Anthea , Rabadan Raul , Saenger Yvonne 
Published: February 2019

Abstract
Background: While immunotherapy has demonstrated success in melanoma, a deeper understanding of the heterogeneous tumor microenvironment is needed for stratifying patients for treatment. Technologies such as quantitative multiplex immunofluorescence (qmIF) imaging and transcriptomic profiling both have the potential to provide such insights. Using these tools, we had previously shown that immune cellular compositions and bulk gene expression in tumors are each related to patient survival. However, the connection between these modalities and their impact on prognosis is not well-understood. Here, we investigate the link between the microenvironmental composition of immune cells, such as cytotoxic T lymphocytes (CTLs) and macrophages, with observed transcriptomic signatures. Furthermore, we uncover spatial correlations in cellular positioning, which supports a mechanistic basis underlying these relationships. Methods: QmIF imaging was obtained from 104 stage II-III primary melanomas from Columbia University Irving Medical Center (CUIMC), which included staining for CTLs (CD3 and CD8), macrophages (CD68), and tumor cells (SOX10). HLA-DR and Ki67 were also stained in order to assess activation and proliferation of immune and tumor cells. Visualization, cell segmentation, and phenotyping were performed using inForm software within Mantra workstation. Spatial relationships between cells were quantified via the inhomogeneous pair correlation function (PCF), which compares the observed probability of two cell types being separated by a given distance to that expected by chance. Disease-specific survival status was known for 64 patients, while mRNA expression for 63 immune-related genes was obtained via NanoString for 53 patients. We assessed the similarity of each sample’s gene expression profile to the cellular subtype signatures from LM22, the reference standard for CIBERSORT. Results: The proportion of CTLs observed via qmIF was significantly associated with the CD8 T-cell transcriptomic signature (Spearman’s rho = 0.33, p &lt; 0.02). Likewise, the proportion of HLA-DR+ macrophages was correlated with the M1 macrophage signature (rho = 0.31, p &lt; 0.03). Point-wise discrepancies in PCFs were found in the spatial distribution of cells between disease-specific survivors versus non-survivors. Greater clustering between macrophages and CTLs was negatively associated with survival (Mann-Whitney, p &lt; 6e-5), while greater clustering between macrophages and Ki67- tumor cells was positively associated with survival (p &lt; 6e-4). Conclusions: Bulk RNA profiling reflects the underlying proportions of immune cells within the tumor microenvironment. Additionally, even after accounting for variations in cell density, different patterns of positioning among immune and tumor cells are related to prognosis. The importance of spatial proximity of immune cells to each other and to tumor cells suggests a mechanism by which their infiltration affects disease progression. Future work will investigate the genomic determinants that may lead to these spatial findings. Understanding these connections between the imaging and the genetics of melanoma will bring us closer to forming effective clinical biomarkers for evaluating immunotherapies.
Citation Format: Andrew X. Chen, Robyn Gartrell, Douglas K. Marks, Thomas Hart, Emanuelle Rizk, Anthea Monod, Raul Rabadan, Yvonne Saenger. Linking transcriptomic and imaging features of the melanoma tumor microenvironment [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B005.