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Uveal melanoma progression can be predicted by gene expression profiles enabling a clear subdivision between tumors with a good (class I) and a poor (class II) prognosis. Poor prognosis uveal melanoma can be subdivided by expression of immune-related genes; however, it is unclear whether this subclassification is justified; therefore, T cells in uveal melanoma specimens were quantified using a digital PCR approach. Absolute T-cell quantification revealed that T-cell influx is present in all uveal melanomas associated with a poor prognosis. However, this infiltrate is only accompanied by differential immune-related gene expression profiles in uveal melanoma with the highest T-cell infiltrate. Molecular deconvolution of the immune profile revealed that a large proportion of the T-cell-related gene expression signature does not originate from lymphocytes but is derived from other immune cells, especially macrophages. Expression of the lymphocyte-homing chemokine CXCL10 by activated macrophages correlated with T-cell infiltration and thereby explains the correlation of T-cell numbers and macrophages. This was validated by in situ analysis of CXCL10 in uveal melanoma tissue with high T-cell counts. Surprisingly, CXCL10 or any of the other genes in the activated macrophage-cluster was correlated with reduced survival due to uveal melanoma metastasis. This effect was independent of the T-cell infiltrate, which reveals a role for activated macrophages in metastasis formation independent of their role in tumor inflammation. IMPLICATIONS: The current report uses an innovative digital PCR method to study the immune environment and demonstrates that absolute T-cell quantification and expression profiles can dissect disparate immune components.

molecular cancer research

Digital PCR-Based T-cell Quantification–Assisted Deconvolution of the Microenvironment Reveals that Activated Macrophages Drive Tumor Inflammation in Uveal Melanoma