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• W2068806064 abstract "We performed a randomized prospective trial comparing calcineurin inhibitor (CNI)-free to CNI-based immunosuppression to determine the impact on renal function, structure and gene expression. Sixty-one kidney recipients treated with basiliximab mycophenolate mofetil (MMF) and prednisone (P) were randomly assigned to concentration-controlled sirolimus or cyclosporine. Two years post-transplant 55 patients underwent renal function studies, 48 (87%) underwent transplant biopsies; all classified by Banff scoring and 41 by DNA microarrays. Comparing sirolimus/MMF/P to cyclosporine/MMF/P there was a significantly lower serum creatinine (1.35 vs. 1.81 mg/dL; p = 0.008), higher Cockroft-Gault glomerular filtration rate (GFR) (80.4 vs. 63.4 mL/min; p = 0.008), iothalamate GFR (60.6 vs. 49.2 mL/min; p = 0.018) and Banff 0 (normal) biopsies (66.6 vs. 20.8%; p = 0.013). Regression analysis of calculated GFRs from 1 to 36 months yielded a positive slope for sirolimus of 3.36 mL/min/year, and a negative slope for cyclosporine of −1.58 mL/min/year (p = 0.008). Gene expression profiles from kidneys with higher Banff chronic allograft nephropathy (CAN) scores confirmed significant up-regulation of genes responsible for immune/inflammation and fibrosis/tissue remodeling. At 2 years the sirolimus-treated recipients have better renal function, a diminished prevalence of CAN and down-regulated expression of genes responsible for progression of CAN. All may provide for an alternative natural history with improved graft survival. We performed a randomized prospective trial comparing calcineurin inhibitor (CNI)-free to CNI-based immunosuppression to determine the impact on renal function, structure and gene expression. Sixty-one kidney recipients treated with basiliximab mycophenolate mofetil (MMF) and prednisone (P) were randomly assigned to concentration-controlled sirolimus or cyclosporine. Two years post-transplant 55 patients underwent renal function studies, 48 (87%) underwent transplant biopsies; all classified by Banff scoring and 41 by DNA microarrays. Comparing sirolimus/MMF/P to cyclosporine/MMF/P there was a significantly lower serum creatinine (1.35 vs. 1.81 mg/dL; p = 0.008), higher Cockroft-Gault glomerular filtration rate (GFR) (80.4 vs. 63.4 mL/min; p = 0.008), iothalamate GFR (60.6 vs. 49.2 mL/min; p = 0.018) and Banff 0 (normal) biopsies (66.6 vs. 20.8%; p = 0.013). Regression analysis of calculated GFRs from 1 to 36 months yielded a positive slope for sirolimus of 3.36 mL/min/year, and a negative slope for cyclosporine of −1.58 mL/min/year (p = 0.008). Gene expression profiles from kidneys with higher Banff chronic allograft nephropathy (CAN) scores confirmed significant up-regulation of genes responsible for immune/inflammation and fibrosis/tissue remodeling. At 2 years the sirolimus-treated recipients have better renal function, a diminished prevalence of CAN and down-regulated expression of genes responsible for progression of CAN. All may provide for an alternative natural history with improved graft survival. Continued improvements in short-term graft survival for recipients of kidney transplants have driven the demand to unprecedented levels worldwide. However, commonly achieved 1-year graft survivals over 90%, rapidly fall to 65–70% at 5 years and under 50% at 10 years (1Services USDoHaH. Annual Report of the U.S. Scientific Registry for Transplant Recipients and the Organ Procurement and Transplantation Network, 2001; 133: 130–133.Google Scholar, 2Beveridge T Calne RY Cyclosporine (Sandimmun) in cadaveric renal transplantation. Ten-year follow-up of a multicenter trial. European Multicentre Trial Group.Transplantation. 1995; 59: 1568-1570Crossref PubMed Scopus (51) Google Scholar, 3Marcen R Pascual J Teruel JL et al.Outcome of cadaveric renal transplant patients treated for 10 years with cyclosporine: is chronic allograft nephropathy the major cause of late graft loss?.Transplantation. 2001; 72: 57-62Crossref PubMed Scopus (57) Google Scholar). The leading cause of late graft loss among surviving recipients remains the non-specific process termed chronic allograft nephropathy (CAN). Clinically, this process describes the inexorable decline in renal function with time, often characterized histologically by renal interstitial fibrosis, tubular atrophy, vascular occlusive changes and glomerulosclerosis(4Racusen LC Solez K Colvin RB et al.The Banff 97 working classification of renal allograft pathology.Kidney Int. 1999; 55: 713-723Abstract Full Text Full Text PDF PubMed Scopus (2771) Google Scholar). Retrospective analysis in both single centers and registries have identified a number of risk factors that statistically associate with CAN, which include both immune and non-immune mechanisms (5Almond PS Matas A Gillingham K et al.Risk factors for chronic rejection in renal allograft recipients.Transplantation. 1993; 55 (discussion 756–757.): 752-756Crossref PubMed Scopus (637) Google Scholar, 6Flechner SM Modlin CS Serrano DP et al.Determinants of chronic renal allograft rejection in cyclosporine-treated recipients.Transplantation. 1996; 62: 1235-1241Crossref PubMed Scopus (108) Google Scholar). There is a strong association between CAN and the continuous use of the calcineurin inhibitors (CNI), cyclosporine (CsA) and tacrolimus, which have been known to be nephrotoxins since their initial clinical introduction (7Calne RY White DJ Thiru S et al.Cyclosporin A in patients receiving renal allografts from cadaver donors.Lancet. 1978; 2: 1323-1327Abstract PubMed Scopus (831) Google Scholar, 8Pascual M Swinford RD Ingelfinger JR Williams WW Cosimi AB Tolkoff-Rubin N Chronic rejection and chronic cyclosporin toxicity in renal allografts.Immunol Today. 1998; 19: 514-519Abstract Full Text Full Text PDF PubMed Scopus (69) Google Scholar, 9Remuzzi G Perico N Cyclosporine-induced renal dysfunction in experimental animals and humans.Kidney Int Suppl. 1995; 52: S70-S74PubMed Google Scholar, 10De Mattos AM Olyaei AJ Bennett WM Nephrotoxicity of immunosuppressive drugs: long-term consequences and challenges for the future.Am J Kidney Dis. 2000; 35: 333-346Abstract Full Text Full Text PDF PubMed Scopus (368) Google Scholar). The recent report of Nankivell et al. (11Nankivell BJ Borrows RJ Fung CL O'Connell PJ Allen RD Chapman JR The natural history of chronic allograft nephropathy.N Engl J Med. 2003; 349: 2326-2333Crossref PubMed Scopus (1663) Google Scholar), describing the longitudinal evolution of CAN over a 10-year period, confirms the ubiquitous scarring of kidneys that occurs with the continuous use of CNI drugs. In addition, Ojo et al. (12Ojo AO Held PJ Port FK et al.Chronic renal failure after transplantation of a nonrenal organ.N Engl J Med. 2003; 349: 931-940Crossref PubMed Scopus (1774) Google Scholar) have identified an alarming prevalence of renal insufficiency and permanent renal failure among extrarenal allograft recipients receiving continuous CNI therapy. The introduction of Target of Rapamycin (TOR) inhibitors, a new class of potent antirejection drugs, has provided opportunities to develop alternative immunosuppressive combinations (13Sehgal SN Rapamune (RAPA, rapamycin, sirolimus): mechanism of action immunosuppressive effect results from blockade of signal transduction and inhibition of cell cycle progression.Clin Biochem. 1998; 31: 335-340Crossref PubMed Scopus (621) Google Scholar). The initial use of the TOR inhibitor, sirolimus (SRL), in CNI-free regimens demonstrated improved kidney function at 1 year (14Groth CG Backman L Morales JM et al.Sirolimus (rapamycin)-based therapy in human renal transplantation: similar efficacy and different toxicity compared with cyclosporine. Sirolimus European Renal Transplant Study Group.Transplantation. 1999; 67: 1036-1042Crossref PubMed Scopus (857) Google Scholar, 15Kreis H Cisterne JM Land W et al.Sirolimus in association with mycophenolate mofetil induction for the prevention of acute graft rejection in renal allograft recipients.Transplantation. 2000; 69: 1252-1260Crossref PubMed Scopus (536) Google Scholar). Thus, it is possible that SRL in combination with the antiproliferative agent mycophenolate mofetil (MMF) and steroids will be a regime that provides good long-term immunosuppression and is less nephrotoxic. Secondly, it is possible that a CNI-free regime will prevent or delay the onset and progression of CAN by minimizing immune injury and drug-induced nephrotoxicity that in turn may drive a cycle of tissue injury, interstitial fibrosis, ischemia and pathological tissue remodeling (16Waller JR Nicholson ML Molecular mechanisms of renal allograft fibrosis.Br J Surg. 2001; 88: 1429-1441Crossref PubMed Scopus (53) Google Scholar, 17Jolicoeur EM Qi S Xu D Dumont L Daloze P Chen H Combination therapy of mycophenolate mofetil and rapamycin in prevention of chronic renal allograft rejection in the rat.Transplantation. 2003; 75: 54-59Crossref PubMed Scopus (61) Google Scholar, 18Shihab FS Bennett WM Yi H Choi SO Andoh TF Combination therapy with sirolimus and mycophenolate mofetil: Effects on the kidney and on transforming growth factor-beta1.Transplantation. 2004; 77: 683-686Crossref PubMed Scopus (28) Google Scholar). We performed a randomized, prospective trial comparing primary adult renal transplant recipients given either de novo cyclosporine-based or sirolimus-based CNI-free immunosuppression (19Flechner SM Goldfarb D Modlin C et al.Kidney transplantation without calcineurin inhibitor drugs: a prospective, randomized trial of sirolimus versus cyclosporine.Transplantation. 2002; 74: 1070-1076Crossref PubMed Scopus (375) Google Scholar). Herein, we present the results 2 years post-transplant of renal function tests, histological analysis by Banff criteria for CAN and gene expression studies using DNA microarrays and quantitative RT-PCR. The results are significant improvements in renal function matched by a significant reduction in CAN in the sirolimus-treated group. DNA microarrays successfully classified the patients with increased Banff CAN scores by biopsy histology and that correlated with the significant up-regulation of genes linked to known pathways of immune/inflammatory injury, fibrosis, ischemia and tissue remodeling. Between March 2000 and June 2001, 61 primary kidney-only adult allograft recipients (age 18–70 years) were enrolled. After informed consent was documented patients were randomized via computer-generated cards to one of the two experimental groups. Exclusion criteria included prior transplantation or immunosuppression, HLA identical sibling donors, cancer, pregnancy or weight >105 kg. All recipients had a negative complement-dependent and flow cytometry T-cell crossmatch, and marginal donor kidneys were avoided (age <3 or >65 years, prolonged warm or cold ischemia, etc.). Mean (range) donor age was 36.3 (6–61) years for sirolimus, and 38.3 (16–65) years for CsA patients (p = ns). As previously reported (19Flechner SM Goldfarb D Modlin C et al.Kidney transplantation without calcineurin inhibitor drugs: a prospective, randomized trial of sirolimus versus cyclosporine.Transplantation. 2002; 74: 1070-1076Crossref PubMed Scopus (375) Google Scholar), all patients received basiliximab (Simulect, Novartis, East Hanover, NJ) 20 mg induction; mycophenolate mofetil (MMF, Cellcept, Hoffman-LaRoche, Nutley, NJ) 1 gm b.i.d. orally unless side effects necessitated dose reduction; and the same steroid regimen consisting of methylprednisolone 500 mg intravenously day 0, tapered to a maintenance of 7.5 mg by 6 months. Group 1 patients began sirolimus (SRL, Rapamune, Wyeth, Collegeville, PA) orally within 48 h of surgery and then concentration-controlled to keep 24-h whole blood trough levels between 10–12 ng/mL (HPLC with Mass Spectroscopy detection) for 6 months, and then 5–10 ng/mL, thereafter. Group 2 patients were given cyclosporine (CsA, Neoral, Novartis, E. Hanover, NJ) 6–8 mg/kg in divided doses, and were concentration-controlled to C0 levels of 200 ng/mL the first year, and 150–175 ng/mL thereafter. (TDX monoclonal assay, Abbott Labs, Abbott Park, IL). At 2 years, all of the SRL patients were taking the drug, while 4 CsA patients had been switched (to tacrolimus in 3, SRL in 1). At 2 years, the SRL group was receiving 3.44 mg/day with a trough level of 7.2 ng/mL, and the CsA group was receiving 3.26 mg/kg/day with a trough level of 178 ng/mL. Each of the 55 patients alive with a functioning transplant at 2 years had their kidney function analyzed including a measured GFR utilizing iothalamate. After documented informed consent, 48 of 55 (87.2%) eligible patients underwent a percutaneous kidney transplant biopsy. The reason for non-biopsy included the need for coumadin therapy in 2, and patient refusal for various reasons in 5, evenly divided between the groups. Hospital Laboratory Tests: Blood and urine samples were tested for serum creatinine, calculated creatinine clearance (Cockroft-Gault Formula) normalized to current body weight and gender (20Cockcroft DW Gault MH Prediction of creatinine clearance from serum creatinine.Nephron. 1976; 16: 31-41Crossref PubMed Scopus (13131) Google Scholar), and 24-h urine collection for protein excretion.Dynamic Slope Analysis: Random coefficient regression analysis was used to evaluate trends in calculated GFRs over 1–36 months. Individual estimates (intercept and slope) were made for all patients, and expressed as the mean by treatment group (21Rutter CM Elashoff RM Analysis of longitudinal data: random coefficient regression modelling.Stat Med. 1994; 13: 1211-1231Crossref PubMed Scopus (75) Google Scholar).Measured Glomerular Filtration Rate: The clearance of 125I-sodium iothalamate (Questcor Pharmaceuticals, Inc., Union City, CA) was determined during an induced diuresis after subcutaneous injection of 25 microCuries and subsequent collection of plasma and urine samples. The formula GFR = UV/P, where U = counts/min in the urine collection, V = rate of urine flow in mL/min and P = counts/min in the plasma sample was used. Results were then corrected to standard body surface area (22Israelit AH Long DL White MG Hull AR Measurement of glomerular filtration rate utilizing a single subcutaneous injection of 125I-iothalamate.Kidney Int. 1973; 4: 346-349Abstract Full Text PDF PubMed Scopus (131) Google Scholar). Transplant biopsies comprised three cores obtained with 15-gauge needles (ASAP Automatic Biopsy, Microvasive, Watertown, MA); two for light microscopy, one for DNA microarrays. Cores for microarrays went immediately into 1.5 mL of RNALater (Ambion, Austin, TX), and −80°C within 4 h. Paraffin sections were stained with hematoxylin-eosin, trichrome and periodic acid-Schiff. Biopsies were read by one pathologist (KS) blinded to all identifiers and graded by Banff 1997 classification(4Racusen LC Solez K Colvin RB et al.The Banff 97 working classification of renal allograft pathology.Kidney Int. 1999; 55: 713-723Abstract Full Text Full Text PDF PubMed Scopus (2771) Google Scholar). Each sample had at least 10 glomeruli and adequate cortical tissue for analysis. A Banff chronic allograft nephropathy (CAN) score was generated representing the sum of the averages of five individual lesion scores: glomerulopathy, interstitial fibrosis, tubular atrophy, increased mesangial matrix and vascular intimal thickening. Biopsy specimens were homogenized in 1 mL of Trizol (Invitrogen, Carlsbad, CA). Total RNA was further purified using an RNeasy column (Qiagen, Valencia, CA) and quality confirmed by Agilent 2100 BioAnalyzer (Palo Alto, CA). Average total RNA yields from 15-guage-needle biopsy cores were 14.9 ± 3.9 μg. RNA labeling and hybridization Standard Affymetrix GeneChip (Santa Clara, CA) protocols were used (23http://www.affymetrix.com/support/technical/manual/expression_manual.affx.Google Scholar). All labeled samples were hybridized to HG-U133A GeneChip arrays containing 22 283 probe sets representing over 14 500 human genes. GeneChip data were analyzed using Microarray Suite 5.0 (MAS 5.0, Affymetrix) and Robust Multichip Average (RMA) (24Bolstad BM Irizarry RA Astrand M Speed TP A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.Bioinformatics. 2003; 19: 185-193Crossref PubMed Scopus (6417) Google Scholar). RMA used all Affymetrix .CEL files from this study as a training set. Probe sets absent in all chips by Present/Absent calls (MAS 5.0) were not analyzed. BRB ArrayTools (http://linus.nci.nih.gov/BRB-ArrayTools.html) was used to perform class comparisons between the two drug treatment or Banff score-defined biopsy groups. Differentially expressed genes in biopsies of CsA and SRL-treated patients were generated by class comparison of 6682 genes called as Present in >90% of at least one of the two groups (p < 0.001). Gene lists comparing Banff 0 and combined Banff 2 and 3 biopsies were created using 15 572 genes called Present on at least one chip in the data set. The user-defined alpha level (false positive rate) was set at p < 0.001 or p < 0.01 for these lists. Heat maps were generated using Cluster and TreeView programs (25Eisen MB Spellman PT Brown PO Botstein D Cluster analysis and display of genome-wide expression patterns.Proc Natl Acad Sci U S A. 1998; 95: 14863-14868Crossref PubMed Scopus (13218) Google Scholar). Groups were compared using unpaired t-tests for continuous variables (two-sided), which were assumed to be approximately normally distributed, and compared using the chi-square or Fisher's exact test for categorical variables. Results were considered statistically significant if the p-value was less than or equal to 0.05. Q-PCR was performed on RNA from nine biopsy samples for 11 genes (Assays-on-Demand Genomic Assays, Applied Biosystems, Foster City, CA). Based on a literature review for genes associated with CAN, 8 genes were selected from the differentially expressed genes in the class comparison analysis between Banff 0 and the combined Banff 2 and 3 data. Three genes were selected only from the review. The signal intensities on the GeneChips for all 11 genes validated by Q-PCR were grouped by Banff scores and compared within each class. Sample selection bias was excluded by Student's t-test. There were no significant differences between signal intensities of the 11 genes for samples analyzed by Q-PCR and those that were not. Briefly, cDNA was transcribed from 100 ng total RNA (cDNA Archive kit, Applied Biosystems). Reactions were done in 20 μL containing 2 units of Amplitaq Gold® (Applied Biosystems) in an ABI Prism 7900HT. All amplifications were done in triplicate and threshold cycle (Ct) scores were averaged for relative expression values. The Ct scores for candidate genes were normalized against Ct scores for endogenous 18S rRNA. Fold-change was determined by the following calculation (26User Bulletin #2 ABI PRISM 7700 Sequence Detection System. Document 4303859B 777802-002. Relative Quantitation of Gene Expression, 1997.Google Scholar): Fold-change = 2-ΔΔ, where ΔΔ Ct= (Δt of experimental group) - (ΔCt of calibrator group).(1) We used the t distribution rather than z because our estimates of variance are based upon our sample values rather than a known population(27Simon RM Dobbin K Experimental design of DNA microarray experiments.Biotechniques. 2003; 34: S16-S21Crossref Scopus (67) Google Scholar). n=4(tα/2+tβ)2/(δ/s)2(2) The equation for tβ was solved as follows: n = sample size. The degrees of freedom (ν) was 36 by Welch's approximate t value using Student's t degrees of freedom (28Zar JH. Biostatistical Analysis. Prentice Hall, Upper Saddle River , NJ , 1999.Google Scholar). The value for δ= 1 because our calculations are based upon log2 RMA values and 1 represents a minimum detectable difference of 2-fold using the median standard deviation across all chips per sample by gene as an indicator of the detection level for that group. The median standard deviations were s = 0.212 for the CsA group (n = 21) and s = 0.241 for the SRL group (n = 19). The α term = 0.001, defining a false positive rate of 1 in 1000 genes. There were no statistically significant demographic differences between the groups (19Flechner SM Goldfarb D Modlin C et al.Kidney transplantation without calcineurin inhibitor drugs: a prospective, randomized trial of sirolimus versus cyclosporine.Transplantation. 2002; 74: 1070-1076Crossref PubMed Scopus (375) Google Scholar) with a mean follow-up of 36.4 ± 9.1 months for SRL-treated and 37.3 ± 7.4 months for CsA-treated. The 2-year actual patient survival, graft survival and biopsy-confirmed acute rejection rates for the two groups were not significantly different (SRL group: 93.5%, 93.5% and 6.5%; CsA group: 100%, 93.3% and 16.6%). In the CsA group, there have been no deaths, but two grafts were lost at 9 and 14 months due to recurrent rejection, and 1 patient was switched to sirolimus. In the SRL group 2 recipients died with graft function, and 1 dropped out at 3 weeks for personal reasons. Thus, 55 patients were available for analysis. Comparing the CsA to the SRL group at 2 years, there was a significant increase in mean serum creatinine (1.81 ± 0.86 vs. 1.35 ± 0.41 mg/dL, p = 0.008), a decrease in the Cockroft-Gault calculated GFR (63.4 ± 19.4 vs. 80.4 ± 6.2 mL/min, p = 0.008) (Table 1) and a decrease in iothalamate clearance (CsA = 49.2 ± 17.8; SRL = 60.6 ± 18.9 mL/min; p = 0.018) (Figure 1). There was no significant difference in the 24-h urinary protein excretion comparing the CsA to the SRL group (0.88 ± 1.31 vs. 0.55 ± 0.71 g/24 h). A comparison of the random coefficients regression analysis of the Cockroft-Gault-calculated GFRs for the two groups (Figure 2) demonstrated a negative slope of −1.58 mL/min/year for the CsA group (95% CI − 4.096–0.929) and a positive slope of 3.36 mL/min/year for the SRL group (95% CI 0.8412–5.874). The calculated difference between the two slopes was 4.94 mL/min/year (p = 0.008).Table 1Post-transplant renal function comparing CsA-treated and SRL-treated groupsTime post-transplant/patients (n)CsA/MMF/P1Cyclosporine (CsA).SRL/MMF/P2Sirolimus (SRL), mycophenolate mofetil (MMF), prednisone (P).p-valuesSerum creatinine3Serum creatinine expressed as mg/dL, Mean ± SD. 4Not significant.12 months (n = 29 and 29)1.78 ± 0.761.32 ± 0.330.00418 months (n = 28 and 27)1.76 ± 0.691.33 ± 0.340.00524 months (n = 28 and 27)1.81 ± 0.861.35 ± 0.410.00830 months (n = 28 and 26)1.91 ± 0.801.37 ± 0.550.00536 months (n = 20 and 21)2.14 ± 1.301.30 ± 0.410.002Cockroft-Gault GFR5Glomerular filtration rate (GFR) expressed as mL/min, Mean ± SD.12 months (n = 29 and 29)60.8 ± 14.481.1 ± 240.00818 months (n = 28 and 27)63.1 ± 17.979.6 ± 27.20.00624 months (n = 28 and 27)63.4 ± 19.680.4 ± 26.20.00830 months (n = 28 and 26)62.8 ± 20.080.1 ± 27.40.00536 months (n = 20 and 21)59.7 ± 21.783.6 ± 27.80.0021 Cyclosporine (CsA).2 Sirolimus (SRL), mycophenolate mofetil (MMF), prednisone (P).3 Serum creatinine expressed as mg/dL, Mean ± SD. 4Not significant.5 Glomerular filtration rate (GFR) expressed as mL/min, Mean ± SD. Open table in a new tab Figure 2Random coefficients regression (slope) analysis using Cockroft-Gault-calculated glomerular filtration rate values between 1 and 36 months post-transplant.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The number of patients biopsied at 2 years was similar in each group and represented 48 of 55 (87.2%) of those eligible. The mean creatinine values (mg/dL) at the time of biopsy were 1.83 ± 0.89 for the CsA patients and 1.35 ± 0.38 for the SRL patients (Table 2). The creatinines of the un-biopsied patients were lower for each group. The SRL group had a significantly higher frequency of the 2-year protocol biopsies read as normal (Banff grade 0) as compared to the CsA group (66.6% vs. 20.8%; p = 0.007). Not surprisingly, 16.6% of the CsA group demonstrated specific features of CNI drug nephrotoxicity, whereas none of the SRL-treated patients demonstrated these findings. Features included hyaline arteriolar changes, tubular vacuolization and/or interstitial calcification. The net Banff CAN scores comprised individual scores for interstitial fibrosis, tubular atrophy, mesangial matrix, glomerulopathy and intimal thickening and were also significantly different between the CsA and SRL groups (3.17 ± 0.62 vs. 1.48 ± 0.27; p < 0.00001). The higher net Banff CAN scores in the CsA group were primarily due to differences in tubular atrophy and interstitial fibrosis (Figure 3). In addition, higher Banff CAN scores of grade II and III were more frequently observed in the CsA group than in the SRL group (37.5% vs. 12.5%; p = 0.013) (Figure 4).Table 2Histopathologic findings in protocol renal biopsies at 2-years: CsA/MMF/P vs. SRL/MMF/P1CsA = cyclosporine, MMF = mycophenolate mofetil, P = prednisone, SRL = sirolimus.SRL/MMF/PCsA/MMF/PPatientsEntered3130Eligible2827Biopsied (%)24 (85.7)24 (88.8)DNA Microarrays (%)19 (79)22 (92)1-yr Acute Rejection (%)2 (6.4)5 (16.6)Scr2Serum creatinine (Scr; mg/dL). biopsied group1.35 ± 0.381.83 ± 0.893Standard deviation.Scr not biopsied group1.27 ± 0.341.51 ± 0.54Normal histology (%)16 (66.6)5 (20.8)Acute rejection00Allograft nephropathy (%)8 (33.3)17 (79.2)Drug nephrotoxicity4Defined by hyaline arteriolar change, tubular vacuolization or Ca++ deposition. (%)0 (0)4 (16.6)1 CsA = cyclosporine, MMF = mycophenolate mofetil, P = prednisone, SRL = sirolimus.2 Serum creatinine (Scr; mg/dL).3 Standard deviation.4 Defined by hyaline arteriolar change, tubular vacuolization or Ca++ deposition. Open table in a new tab Figure 4Sums of the 5 individual histological features that comprise the Banff chronic allograft nephropathy (CAN) scores. Values reported as mean ± SD for the sirolimus/MMF/P vs. the cyclosporine/MMF/P groups. The differences between the two groups are primarily due to scores for interstitial fibrosis and tubular atrophy.View Large Image Figure ViewerDownload Hi-res image Download (PPT) High-density DNA microarrays were used to determine a series of gene expression profiles with the objective of making two different class comparisons. The first class comparison between the biopsies of patients treated with CNI-based immunosuppression (CsA/MMF/P) and the sirolimus group (SRL/MMF/P) yielded 379 differentially expressed genes (p < 0.001). Importantly, 97% of the genes are up-regulated in the CsA-treated patient biopsies (Table 3). Functional classifications of these genes based on the Gene Ontology (GO) database and published literature identified 32 groups of which the top 6 comprised gene candidates involved in pathways for regulation of transcription (35; 9.7%), fibrosis/tissue remodeling (27; 7.1%), immunity/inflammation (25; 6.6%), intracellular protein transport (23; 6.1%), signal transduction (23; 6.1%) and cell growth (18; 4.7%).Table 3Biological function based on gene ontology (GO) database for class comparison of CsA/MMF/P vs. SRL/MMF/PNumber of genes1There were 379 differentially expressed genes (p < 0.001), 97% were up-regulated (CsA vs. SRL). The top six of 32 functional classification groups are listed.PercentageTranscription regulation/DNA binding359.7Fibrosis/tissue remodeling277.1Immune/inflammatory responses256.6Intracellular protein transport236.1Signal transduction236.1Cellular growth184.71 There were 379 differentially expressed genes (p < 0.001), 97% were up-regulated (CsA vs. SRL). The top six of 32 functional classification groups are listed. Open table in a new tab The second class comparison was done to compare gene expression profiles of biopsies from patients with Banff CAN 0 scores (normal histology; n = 18) and those with Banff CAN scores of 2 and 3 (CAN; n = 9). We set the alpha error term at p < 0.001 such that the estimated false positive error would be 1 gene call per 1000 profiled, yielding 130 candidate genes. Based on annotation of gene function (Tables 3 and 4), we found that the largest group of classified genes was immune/inflammatory responses (23; 17.3%), consistent with the same pattern of gene expression in the CsA-treated group in which more Banff 2 and 3 biopsies are also found. The second largest groups are genes linked to pathways of cell adhesion and extracellular matrix (15; 11.3%) and genes involved in protein synthesis, modification and proteolysis (20; 15%). The results of both class comparisons are consistent with the literature demonstrating that genes linked to pathways of both immune/inflammatory and fibrosis/tissue remodeling are involved in the pathogenesis of CAN.Table 4Biological function based on gene ontology (GO) database for class comparison of Banff CAN 0 vs. Banff CAN 2 + 3Number of genes1Total of 85 of the 133 genes in the class comparison based on showing all groups with 5 or more genes.PercentageImmune/inflammatory responses2317.3Cell adhesion/extracellular matrix1511.3Protein synthesis, modification & proteolysis2015.0Transcription regulation/DNA binding53.8Cellular metabolism1612.0EST and hypothetical proteins64.51 Total of 85 of the 133 genes in the class comparison based on showing all groups with 5 or more genes. Open table in a new tab Based on a literature review we identified 11 genes putatively involved in CAN (Table 5), only 4 of which were included in the initial class comparison. Setting the alpha term (false posi" @default.
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• W2068806064 date "2004-11-01" @default.
• W2068806064 modified "2023-09-27" @default.
• W2068806064 title "De Novo Kidney Transplantation Without Use of Calcineurin Inhibitors Preserves Renal Structure and Function at Two Years" @default.
• W2068806064 cites W1550111394 @default.
• W2068806064 cites W1900562057 @default.
• W2068806064 cites W1964421080 @default.
• W2068806064 cites W1979468409 @default.
• W2068806064 cites W1985282047 @default.
• W2068806064 cites W1986540696 @default.
• W2068806064 cites W1991100846 @default.
• W2068806064 cites W1995791071 @default.
• W2068806064 cites W1996741735 @default.
• W2068806064 cites W2003799149 @default.
• W2068806064 cites W2011010559 @default.
• W2068806064 cites W2018403460 @default.
• W2068806064 cites W2023688475 @default.
• W2068806064 cites W2026351725 @default.
• W2068806064 cites W2029046028 @default.
• W2068806064 cites W2029805256 @default.
• W2068806064 cites W2033660326 @default.
• W2068806064 cites W2048571115 @default.
• W2068806064 cites W2050340337 @default.
• W2068806064 cites W2055126700 @default.
• W2068806064 cites W2056140215 @default.
• W2068806064 cites W2060741577 @default.
• W2068806064 cites W2060818620 @default.
• W2068806064 cites W2067681815 @default.
• W2068806064 cites W2071307134 @default.
• W2068806064 cites W2075528627 @default.
• W2068806064 cites W2077736762 @default.
• W2068806064 cites W2081212981 @default.
• W2068806064 cites W2084126045 @default.
• W2068806064 cites W2089137362 @default.
• W2068806064 cites W2092484100 @default.
• W2068806064 cites W2092711749 @default.
• W2068806064 cites W2093603781 @default.
• W2068806064 cites W2093607033 @default.
• W2068806064 cites W2094320316 @default.
• W2068806064 cites W2098173664 @default.
• W2068806064 cites W2098974363 @default.
• W2068806064 cites W2120865735 @default.
• W2068806064 cites W2123940335 @default.
• W2068806064 cites W2130280946 @default.
• W2068806064 cites W2134672034 @default.
• W2068806064 cites W2137872564 @default.
• W2068806064 cites W2139609632 @default.
• W2068806064 cites W2150926065 @default.
• W2068806064 cites W2152294840 @default.
• W2068806064 cites W2169639894 @default.
• W2068806064 cites W2172088174 @default.
• W2068806064 cites W2334661099 @default.
• W2068806064 cites W2462440902 @default.
• W2068806064 cites W2464998030 @default.
• W2068806064 cites W2048755805 @default.
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