Project description:The data set contains 67 array (lymphochip cDNA array), published in N Engl J Med 2003 Jul 10;349(2):125-38. PMID: 12853585. TITLE: Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. BACKGROUND: The causes and clinical course of acute rejection vary, and it is not possible to predict graft outcome reliably on the basis of available clinical, pathological, and genetic markers. We hypothesized that previously unrecognized molecular heterogeneity might underlie some of the variability in the clinical course of acute renal allograft rejection and in its response to treatment. METHODS: We used DNA microarrays in a systematic study of gene-expression patterns in biopsy samples from normal and dysfunctional renal allografts. A combination of exploratory and supervised bioinformatic methods was used to analyze these profiles. : We found consistent differences among the gene-expression patterns associated with acute rejection, nephrotoxic effects of drugs, chronic allograft nephropathy, and normal kidneys. The gene-expression patterns associated with acute rejection suggested at least three possible distinct subtypes of acute rejection that, although indistinguishable by light microscopy, were marked by differences in immune activation and cellular proliferation. Since the gene-expression patterns pointed to substantial variation in the composition of immune infiltrates, we used immunohistochemical staining to define these subtypes further. This analysis revealed a striking association between dense CD20+ B-cell infiltrates and both clinical glucocorticoid resistance (P=0.01) and graft loss (P<0.001). CONCLUSIONS: Systematic analysis of gene-expression patterns provides a window on the biology and pathogenesis of renal allograft rejection. Biopsy samples from patients with acute rejection that are indistinguishable on conventional histologic analysis reveal extensive differences in gene expression, which are associated with differences in immunologic and cellular features and clinical course. The presence of dense clusters of B cells in a biopsy sample was strongly associated with severe graft rejection, suggesting a pivotal role of infiltrating B cells in acute rejection. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: normal vs disease Keywords: disease_state_design Using regression correlation

Project description:T cell-mediated rejection (TCMR) remains a challenge in kidney transplantation. Based on a histopathological biopsy examination, patients can be classified into groups defining their kidney’s status, i.e. no rejection (NR), borderline rejection (BR) and acute rejection (AR). Yet, this classification is not perfect, since for the borderline cases, a number of patients may or may not require further clinical intervention. Although in other studies, detection of early signs of rejection in the urine proteome was already attempted, these results failed to be replicated. Thus, a robust method of classification by biopsy proteome profiling may provide a possible solution. Unlike for urine or small extracellular vesicle’s analysis, biopsy proteome directly reflects the subclinical changes leading to allograft loss. Kidney tissue biopsies from patients classified into NR, BR and AR groups based on the current Banff guidelines were subjected to a mass spectrometry based proteomic profiling. Using qualitative, quantitative, profile and ROC analysis, a set of four proteins (i.e., GNB4, PDK1, AGXT and CD73) was chosen for further validation using immunohistochemical (IHC) methods. Proteomic analysis identified 2547 proteins across all groups with their abundance profiles showing high degree of similarity between the BR and AR datasets. In a quantitative comparison, GNB4 and AGXT emerged as the proteins significantly differentiating the groups with the highest fold change. Moreover, AGXT was indicated as a potential biomarker candidate following a ROC analysis. Morover, PDK1 and CD73 were found to best classify the samples in a binary fashion. These candidate biomarkers were validated using an IHC approach, where only upregulation of GNB4 in immune cells and PDK1 in macrophages could be confirmed, with no significant changes in the tubular epithelium. Based on these results, GNB4 and PDK1 presence in the immune cells and macrophages has been identified as an interesting target for further extensive studies. If their relevance was to be confirmed in a large patient cohort, their analysis could potentially serve an extension of the already established histopathological classification in the context of kidney transplant rejection. This retrospective study was approved by the Bioethics Committee of the Medical University of Gdańsk no. NKBBN/201/2021.

Project description:The data set contains 67 array (lymphochip cDNA array), published in N Engl J Med 2003 Jul 10;349(2):125-38. PMID: 12853585. TITLE: Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. BACKGROUND: The causes and clinical course of acute rejection vary, and it is not possible to predict graft outcome reliably on the basis of available clinical, pathological, and genetic markers. We hypothesized that previously unrecognized molecular heterogeneity might underlie some of the variability in the clinical course of acute renal allograft rejection and in its response to treatment. METHODS: We used DNA microarrays in a systematic study of gene-expression patterns in biopsy samples from normal and dysfunctional renal allografts. A combination of exploratory and supervised bioinformatic methods was used to analyze these profiles. : We found consistent differences among the gene-expression patterns associated with acute rejection, nephrotoxic effects of drugs, chronic allograft nephropathy, and normal kidneys. The gene-expression patterns associated with acute rejection suggested at least three possible distinct subtypes of acute rejection that, although indistinguishable by light microscopy, were marked by differences in immune activation and cellular proliferation. Since the gene-expression patterns pointed to substantial variation in the composition of immune infiltrates, we used immunohistochemical staining to define these subtypes further. This analysis revealed a striking association between dense CD20+ B-cell infiltrates and both clinical glucocorticoid resistance (P=0.01) and graft loss (P<0.001). CONCLUSIONS: Systematic analysis of gene-expression patterns provides a window on the biology and pathogenesis of renal allograft rejection. Biopsy samples from patients with acute rejection that are indistinguishable on conventional histologic analysis reveal extensive differences in gene expression, which are associated with differences in immunologic and cellular features and clinical course. The presence of dense clusters of B cells in a biopsy sample was strongly associated with severe graft rejection, suggesting a pivotal role of infiltrating B cells in acute rejection. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: normal vs disease Keywords: disease_state_design

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A coronin 1-dependent signaling axis in T cells essential for allograft rejection

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