The contemporary clinical successes of immunotherapies have highlighted the key role of tumor-infiltrating cells
in mediating anti-tumor immunity and have generally associated the presence of T cells within tumors with
therapeutic response. However, until now, a systematic approach for evaluating how T cell state, their clonal
identity and localization are related has not been possible. In recent years, the Wu lab has achieved several
notable technical advances, including generation of a best-in-class HLA class I epitope predictor (HLAthena); a
highly robust targeted plate-based method for single-cell TCR sequencing (rhTCRseq); and a means to
parallelize the cloning of hundreds of TCRs such that they can be interrogated to definitively link a TCR with its
antigen specificity. Because dynamic interactions between tumor-reactive T cells and malignant clones occur
within the defined spatial ordering of tissue, our valuable new insights motivate us to investigate how the spatial
organization of tumor-specific T cells relates to in situ positioning of tumor clones. We hypothesize that antigen
specificity, which drives the interactions between T cells and tumor cells, impacts the distinct regional localization
of T cells within the tumor microenvironment at baseline and in the context of therapy; conversely, that knowledge
of spatial localization identifies T cell clones specific for distinct antigen types. Slide-seq technology, created by
the Chen lab, provides a tractable and exciting path to investigate this hypothesis by implementing a scalable
approach to undertake in-depth analyses of informative human and murine tumor tissues. By expanding the
capabilities of this unbiased cellular resolution spatial capture method, we aim to gain tissue level understanding
of how the abundance and functional state of T cell clones and their spatial orientation within the tumor
microenvironment are linked. In particular, the study will address the spatial organization of T cell clones and
tumor subclones in human and mouse tumors. Our technology goals will be to increase the efficiency of
transcript capture of the technology, extend the capability to include robust detection of tumor mutations, and to
develop a suite of analytic tools to integrate in a multi model fashion the transcript, DNA-level and TCR levels of
information (Aims 1-2). Focusing on RCC tumors, we will evaluate the cell-cell localization patterns of T cell
clones in relation to tumor subclones and stromal cells through integrated spatial analyses of TCR and DNA
Slide-seq data (Aim 2). Finally, we will evaluate the impact of antigen specificity (definitively assessed by robust
TCR reconstruction and interrogation methods established in our lab) on T cell phenotype and localization using
TCR and DNA Slide-seq integrated spatial analyses at baseline and following immune checkpoint blockade and
neoantigen vaccine. (Aim 3) Altogether, we will develop and test these tools to understand spatially localized
cellular networks which drive immune response, and T-cell receptor relationships with the tumor
microenvironment. The completion of our work will yield a comprehensive toolset to enable a molecular,
cellular and histological understanding of the tumor immune response.