Transcription profiling of human kidney and peripheral blood lymphocytes from kidney transplant patients
Ontology highlight
ABSTRACT: We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis; several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL
Project description:We focused on the major peripheral blood lymphocyte populations that may be involved in anti-tumor responses and negatively impacted by cancer, specifically CD8 T cells, CD4 T cells, B cells and CD56dim natural killer cells. The pure cell subsets were stringently sorted by flow cytometry from PBMC samples. Gene expression profiles of these cell populations from melanoma patients were compared to healthy controls. Experiment Overall Design: The raw data set contained 48 arrays: 6 healthy and 6 melanoma arrays for each of the 4 cell types. Two of the arrays had quality issues due to background noise and were excluded, leaving us with 46 arrays. Experiment Overall Design: On each array we used Cy3 to label a pool of two RNA samples from a pair of age and gender matched stage IV (American Joint Committee on Cancer) melanoma patients or from a pair of age and gender matched healthy donors. We used Cy5 to label the Total Lymphocyte Reference (TLR) RNA. The TLR is a common reference specifically created for this study using the total peripheral lymphocyte fraction from 20 healthy donors.
Project description:We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL Keywords = DNA microarrays, gene expression, kidney, rejection, transplant Keywords: other
Project description:Full title: Expression data from whole blood gene expression analysis of stable and acute rejection pediatric kidney transplant patients Tissues are often made up of multiple cell-types. Blood, for example, contains many different cell-types, each with its own functional attributes and molecular signature. In humans, because of its accessibility and immune functionality, blood cells have been used as a source for RNA-based biomarkers for many diseases. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity in gene expression studies of blood cells and great difficulty in identifying the cellular source of any perturbations. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive. This dataset is the validation dataset used to test the csSAM gene expression deconvolution algorithm as reported in the accompanying paper. Whole blood gene expression measurements for 24 pediatric renal transplant patients were analyzed on human specific HGU133V2.0 (+) whole genome expression arrays. Blood drawn using PaxGene Blood RNA Tubes (PreAnalytiX, Qiagen).
Project description:Background: We aimed to investigate the effects of intravenous immune globulin (IVIG) and rituximab desensitization treatment on kidney transplant rate and blood gene expression profiles by microrarrays. Methods: We enrolled patients with PRA levels >50% and on the deceased-donor waiting list for >5 years. Patients received IVIG (2.0 g/kg) on day 0 and 30; and rituximab (375 mg/m2) on day 15. The antibodies with mean fluorescence intensity (MFI) values > 5,000 were reported to UNET as unacceptable antigens. The gene expression profiles of blood samples collected in PAXGene tube were studied by Affymetrix HuGene 1.0 ST expression arrays. Results: 40 of the 415 patients (10%) on the waiting list were eligible for desensitization treatment and 11 completed the treatment. While 15 of the remaining 29 patients (52%) received a transplant without therapy, only 2 of the 11 desensitized patients (18%) received transplant during a median follow-up of 217 days. While there were no statistically significant difference in demographics, desensitized patients had higher cPRA values (97% vs. 77%, p=0.0005) and more number of unacceptable antigens (39 vs. 10, p=0.0001). There was no significant change in the mean number of unacceptable antigens (39 ± 22 versus 39 ± 23) or reduction in the mean MFI values (11,333 ± 3,133 vs 11,289 ± 3,386). Analysis of genes chosen as significantly differentially expressed revealed downregulation of genes involved in B cells and immune system (CD79a, B and T lymphocyte associated transcript, B cell scaffold protein, CD22, CXCR5, fas apoptotic inhibitory protein). Gene set enrichment analysis using Pathogenesis Based Transcripts created by Edmonton Group demonstrated significant downregulation of B cell associated (p=0.04) and immunoglobulin transcripts (p=0.03). Conclusion: Although, desensitization with IVIG and rituximab decreases the expression of B cell and immunoglobulin associated transcripts, it was not successful in increasing kidney transplant rate or in decreasing the number of unacceptable antigens. Total of 28 arrays included in this study, which corresponding to 9 individuals with paired pre/post treatment samples and an additional 10 untreated control individuals. pair_analysis_normData.txt for paired analysis of pre/post treatment; ordinary_analysis_normData.txt for non-paired analysis include all samples, except for 38 Pax V0 and 56 Pax V1, which shows technicial bias and lowest array quality, hence removed from analysis.
Project description:We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL Keywords = DNA microarrays, gene expression, kidney, rejection, transplant Keywords: other. This dataset is part of the TransQST collection.
Project description:There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.