PROJECT SUMMARY The overall purpose of this proposal is to develop predictive biomarkers of treatment outcome in kidney transplant rejection, specifically in T-cell mediated rejection (TCMR), as the response to treatment can be variable, is currently not predictable by clinical diagnostics nor understood from a mechanistic sense, and even partial treatment failure is associated with shortened graft longevity. In each aim, we make use of residual diagnostic biopsy samples with paired richly-detailed clinical data and timelines including treatments, graft functional responses and outcomes. In this manner, we track along the clinical timeline of TCMR, with each aim addressing an unsolved clinical problem in the field. Through the same approach, experimental data from this unique “model system” of tissue inflammation studied over time provides a rich discovery set for understanding tissue-resident T cell behavior in the human kidney. Aim 1 looks at the whole transcriptome profiles of initial acute episodes of TCMR prior to treatment, to identify a gene expression signature predictive of resistance/sensitivity to standard therapies for rejection. When treatment fails, grafts frequently contain residual T cell infiltrates, but the causal connection between these cells and long- term outcome is unclear. For example, residual infiltrates may represent (i) contracting/egressing populations of T cells effectively treated, (ii) newly recruited T cells mounting a fresh rejection response where repeat therapy may be prudent, or (iii) scant memory T cells with established tissue posts and capable of inciting repeat inflammation. Therefore, in Aim 2, we focus on post-treatment biopsies of treatment failure, characterizing multiple spatio-phenotypic aspects of the T cell infiltrate by high dimensional immunofluorescence microscopy with digital image processing and quantitative spatial analysis, to determine which functional phenotypic T cell subsets in which specific tissue niches, correlate with poor graft outcomes. These complementary but independent aims will be achieved through established cross-disciplinary collaborations and with partial industry support.