Background The standard test for the diagnosis of acute rejection in kidney transplants is the renal biopsy. Noninvasive tests would be preferable. Methods We prospectively collected 4300 urine specimens from 485 kidney-graft recipients from day 3 through month 12 after transplantation. Messenger RNA (mRNA) levels were measured in urinary cells and correlated with allograft-rejection status with the use of logistic regression. Results A three-gene signature of 18S ribosomal (rRNA)–normalized measures of CD3ε mRNA and interferon-inducible protein 10 (IP-10) mRNA, and 18S rRNA discriminated between biopsy specimens showing acute cellular rejection and those not showing rejection (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.78 to 0.91; P<0.001 by receiver-operating-characteristic curve analysis). The cross-validation estimate of the AUC was 0.83 by bootstrap resampling, and the Hosmer–Lemeshow test indicated good fit (P = 0.77). In an external-validation data set, the AUC was 0.74 (95% CI, 0.61 to 0.86; P<0.001) and did not differ significantly from the AUC in our primary data set (P = 0.13). The signature distinguished acute cellular rejection from acute antibody-mediated rejection and borderline rejection (AUC, 0.78; 95% CI, 0.68 to 0.89; P<0.001). It also distinguished patients who received anti–interleukin-2 receptor antibodies from those who received T-cell–depleting antibodies (P<0.001) and was diagnostic of acute cellular rejection in both groups. Urinary tract infection did not affect the signature (P = 0.69). The average trajectory of the signature in repeated urine samples remained below the diagnostic threshold for acute cellular rejection in the group of patients with no rejection, but in the group with rejection, there was a sharp rise during the weeks before the biopsy showing rejection (P<0.001). Conclusions A molecular signature of CD3ε mRNA, IP-10 mRNA, and 18S rRNA levels in urinary cells appears to be diagnostic and prognostic of acute cellular rejection in kidney allografts. (Funded by the National Institutes of Health and others.)

Background Currently, over half of breast cancer cases are unrelated to known risk factors, highlighting the importance of discovering other cancer-promoting factors. Since crosstalk between gut microbes and host immunity contributes to many diseases, we hypothesized that similar interactions could occur between the recently described breast microbiome and local immune responses to influence breast cancer pathogenesis. Methods Using 16S rRNA gene sequencing, we characterized the microbiome of human breast tissue in a total of 221 patients with breast cancer, 18 individuals predisposed to breast cancer, and 69 controls. We performed bioinformatic analyses using a DADA2-based pipeline and applied linear models with White’s t or Kruskal–Wallis H-tests with Benjamini–Hochberg multiple testing correction to identify taxonomic groups associated with prognostic clinicopathologic features. We then used network analysis based on Spearman coefficients to correlate specific bacterial taxa with immunological data from NanoString gene expression and 65-plex cytokine assays. Results Multiple bacterial genera exhibited significant differences in relative abundance when stratifying by breast tissue type (tumor, tumor adjacent normal, high-risk, healthy control), cancer stage, grade, histologic subtype, receptor status, lymphovascular invasion, or node-positive status, even after adjusting for confounding variables. Microbiome–immune networks within the breast tended to be bacteria-centric, with sparse structure in tumors and more interconnected structure in benign tissues. Notably, Anaerococcus, Caulobacter, and Streptococcus, which were major bacterial hubs in benign tissue networks, were absent from cancer-associated tissue networks. In addition, Propionibacterium and Staphylococcus, which were depleted in tumors, showed negative associations with oncogenic immune features; Streptococcus and Propionibacterium also correlated positively with T-cell activation-related genes. Conclusions This study, the largest to date comparing healthy versus cancer-associated breast microbiomes using fresh-frozen surgical specimens and immune correlates, provides insight into microbial profiles that correspond with prognostic clinicopathologic features in breast cancer. It additionally presents evidence for local microbial–immune interplay in breast cancer that merits further investigation and has preventative, diagnostic, and therapeutic potential.

Donor Ag-reactive CD4 and CD8 T cell production of IFN-γ is a principal effector mechanism promoting tissue injury during allograft rejection. The CXCR3-binding chemokines CXCL9 and CXCL10 recruit donor-reactive T cells to the allograft, but their role during the priming of donor-reactive T cells to effector function is unknown. Using a murine model of MHC-mismatched cardiac transplantation, we investigated the influence of CXCL9 and CXCL10 during donor-reactive T cell priming. In allograft recipient spleens, CXCL9 and CXCL10 were expressed as early as 24 h posttransplant and increased with similar kinetics, concurrently with CXCR3 expression on T cells. CXCL9, but not CXCL10, expression required NK cell production of IFN-γ. The absence of CXCL9 in donor allografts, recipients, or both significantly decreased the frequency of donor-reactive CD8 T cells producing IFN-γ and increased the frequency of donor-reactive CD8 T cells producing IL-17A. In contrast, the absence of CXCL10 increased the frequency of IFN-γ–producing CD8 T cells in a CXCL9-dependent manner. These data provide novel evidence that donor-reactive CD8 T cells use the CXCR3 chemokine axis as a costimulation pathway during priming to allografts where CXCL9 promotes the development of IFN-γ–producing CD8 T cells, and CXCL10 antagonizes this skewing.

The presence of CD28− memory CD8 T cells in the peripheral blood of renal transplant patients is a risk factor for graft rejection and resistance to CTLA-4Ig induction therapy. In vitro analyses have indicated poor alloantigen-induced CD28− memory CD8 T cell proliferation, raising questions about mechanisms mediating their clonal expansion in kidney grafts to mediate injury. Candidate proliferative cytokines were tested for synergy with alloantigen in stimulating CD28− memory CD8 T cell proliferation. Addition of IL-15, but not IL-2 or IL-7, to co-cultures of CD28− or CD28+ memory CD8 T cells and allogeneic B cells rescued proliferation of the CD28− and enhanced CD28+ memory T cell proliferation. Proliferating CD28− memory CD8 T cells produced high amounts of IFN-γ and TNFα and expressed higher levels of the cytolytic marker CD107a than CD28+ memory CD8 T cells. CTLA-4Ig inhibited alloantigen-induced proliferation of CD28+ memory CD8 T cell proliferation but had no effect on alloantigen plus IL-15-induced proliferation of either CD28− or CD28+ memory CD8 T cells. These results indicate the ability of IL-15, a cytokine produced by renal epithelial during inflammation, to provoke CD28− memory CD8 T cell proliferation and to confer memory CD8 T cell resistance to CTLA-4Ig-mediated costimulation blockade.

Recent advances in immunosuppressive regimens have decreased acute cellular rejection (ACR) rates and improved intestinal and multivisceral transplant (ITx) recipient survival. We investigated the role of myeloid-derived suppressor cells (MDSCs) in ITx. We identified MDSCs as CD33 CD11b lineage(CD3/CD56/CD19) HLA-DR cells with 3 subsets, CD14 CD15 (e-MDSCs), CD14 CD15 (M-MDSCs), and CD14 CD15 (PMN-MDSCs), in peripheral blood mononuclear cells (PBMCs) and mononuclear cells in the grafted intestinal mucosa. Total MDSC numbers increased in PBMCs after ITx; among MDSC subsets, M-MDSC numbers were maintained at a high level after 2 months post ITx. The MDSC numbers decreased in ITx recipients with ACR. MDSC numbers were positively correlated with serum interleukin (IL)-6 levels and the glucocorticoid administration index. IL-6 and methylprednisolone enhanced the differentiation of bone marrow cells to MDSCs in vitro. M-MDSCs and e-MDSCs expressed CCR1, -2, and -3; e-MDSCs and PMN-MDSCs expressed CXCR2; and intestinal grafts expressed the corresponding chemokine ligands after ITx. Of note, the percentage of MDSCs among intestinal mucosal CD45 cells increased after ITx. A novel in vitro assay demonstrated that MDSCs suppressed donor-reactive T cell-mediated destruction of donor intestinal epithelial organoids. Taken together, our results suggest that MDSCs accumulate in the recipient PBMCs and the grafted intestinal mucosa in ITx, and may regulate ACR.

Gene expression profiling of transplant recipient blood and urine can potentially be used to monitor graft function, but the multitude of protocols in use make sharing data and comparing results from different laboratories difficult. The goal of this study was to evaluate the performance of current methods of RNA isolation, reverse transcription, and quantitative polymerase chain reaction (qPCR) and to test whether multiple centers using a standardized protocol can obtain the same results. Samples, reagents, and detailed instructions were distributed to six participating sites that performed RNA isolation, reverse transcription and qPCR for 18S, PRF, GZB, IL8, CXCL9 and CXCL10 as instructed. All data were analyzed at a single site. All sites demonstrated proficiency in RNA isolation and qPCR analysis. Gene expression measurements for all targets and samples had correlations >0.938. The coefficient of variation of fold-changes between pairs of samples was less than 40%. All sites were able to accurately quantify a control sample of known concentration within a factor of 1.5. Collectively, we have formulated and validated detailed methods for measuring gene expression in blood and urine that can yield consistent results in multiple laboratories.

Complement activation contributes to antibody-mediated allograft rejection, but increasing evidence also implicates complement proteins produced locally within the graft, in part by infiltrating mononuclear cells, as important mediators of tissue injury. To test this concept in transplant recipients we evaluated complement, complement regulator and Tcell/proinflammatory marker gene expression by quantitative real-time polymerase chain reaction in 71 archived heart transplant biopsies and correlated the results with the histologic grade of rejection. Significantly more transcripts encoding alternative pathway components factor B, C3 and properdin, and C3a receptor and C5a receptor, were detected in grade 3 vs. grade 0 or 1 biopsies. The grade 3 rejections also contained significantly higher amounts of CD3, interferon γ, perforin and granzyme B genes. In addition to providing supportive evidence for a pathogenic role of graft-derived complement in human heart transplant injury, these correlations suggest that molecular profiling of complement gene expression could be useful in the diagnosis of human allograft rejection.

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