Quantifying T cells accurately in a variety of tissues of benign, inflammatory, or malignant origin can be of great importance in a variety of clinical applications. Flow cytometry and immunohistochemistry are considered to be gold-standard methods for T-cell quantification. However, these methods require fresh, frozen, or fixated cells and tissue of a certain quality. In addition, conventional and droplet digital PCR (ddPCR), whether followed by deep sequencing techniques, have been used to elucidate T-cell content by focusing on rearranged T-cell receptor (TCR) genes. These approaches typically target the whole TCR repertoire, thereby supplying additional information about TCR use. We alternatively developed and validated two novel generic single duplex ddPCR assays to quantify T cells accurately by measuring loss of specific germline TCR loci and compared them with flow cytometry-based quantification. These assays target sequences between the Dδ2 and Dδ3 genes (TRD locus) and Dβ1 and Jβ1.1 genes (TRB locus) that become deleted systematically early during lymphoid differentiation. Because these ddPCR assays require small amounts of DNA instead of freshly isolated, frozen, or fixated material, initially unanalyzable (scarce) specimens can be assayed from now on, supplying valuable information about T-cell content. Our ddPCR method provides a novel and sensitive way for quantifying T cells relatively fast, accurate, and independent of the cellular context.

: 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 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.

<p>Amplicon sequences</p>

<p>T cell correlated genes</p>

<p>Tumor T-cell count</p>