Differential gene expression profiling of matched primary renal cell carcinoma and metastases reveals upregulation of extracellular matrix genes.

Background: The majority of renal cell carcinoma (RCC) studies analyze primary tumors, and the corresponding results are extrapolated to metastatic RCC tumors. However, it is unknown if gene expression profiles from primary RCC tumors differs from patient-matched metastatic tumors. Thus, we sought to identify differentially expressed genes between patient-matched primary and metastatic RCC tumors in order to understand the molecular mechanisms underlying the development of RCC metastases. Patients and methods: We compared gene expression profiles between patient-matched primary and metastatic RCC tumors using a two-stage design. First, we used Affymetrix microarrays on 15 pairs of primary RCC [14 clear cell RCC (ccRCC), 1 papillary] tumors and patient-matched pulmonary metastases. Second, we used a custom NanoString panel to validate seven candidate genes in an independent cohort of 114 ccRCC patients. Differential gene expression was evaluated using a mixed effect linear model; a random effect denoting patient was included to account for the paired data. Third, The Cancer Genome Atlas (TCGA) data were used to evaluate associations with metastasis-free and overall survival in primary ccRCC tumors. Results: We identified and validated up regulation of seven genes functionally involved in the formation of the extracellular matrix (ECM): DCN, SLIT2, LUM, LAMA2, ADAMTS12, CEACAM6 and LMO3. In primary ccRCC, CEACAM6 and LUM were significantly associated with metastasis-free and overall survival (P < 0.01). Conclusions: We evaluated gene expression profiles using the largest set to date, to our knowledge, of patient-matched primary and metastatic ccRCC tumors and identified up regulation of ECM genes in metastases. Our study implicates up regulation of ECM genes as a critical molecular event leading to visceral, bone and soft tissue metastases in ccRCC.

Experimental designs for array comparative genomic hybridization technology.

Array comparative genomic hybridization (aCGH) technology is commonly used to estimate genome-wide copy-number variation and to evaluate associations between copy number and disease. Although aCGH technology is well developed and there are numerous algorithms available for estimating copy number, little attention has been paid to the important issue of the statistical experimental design. Herein, we review classical statistical experimental designs and discuss their relevance to aCGH technology as well as their importance for downstream statistical analyses. Furthermore, we provide experimental design guidance for various study objectives.

Predictive scoring model of mortality in Gram-negative bloodstream infection.

Mortality is a well-recognized complication of Gram-negative bloodstream infection (BSI). The aim of this study was to develop a model to predict mortality in patients with Gram-negative BSI by using the Pitt bacteraemia score (PBS) and other clinical and laboratory variables. A cohort of 683 unique adult patients who were followed for at least 28 days after admission to Mayo Clinic Hospitals with Gram-negative BSI from 1 January 2001 to 31 October 2006 and who received clinically predefined appropriate empirical antimicrobial therapy was retrospectively identified. Multivariable logistic regression was used to identify independent risk factors for 28-day all-cause mortality. Regression coefficients from a multivariable model were used to develop a risk score to predict mortality following Gram-negative BSI. Malignancy (OR 3.48, 95% CI 1.94-6.22), liver cirrhosis (OR 5.42, 95% CI 2.52-11.65), source of BSI other than urinary tract or central venous catheter infection (OR 5.54, 95% CI 2.42-12.69), and PBS (OR 1.98, 95% CI 0.92-4.25 for PBS of 2-3 and OR 6.42, 95% CI 3.11-13.24 for PBS ≥4) were identified as independent risk factors for 28-day mortality in patients with Gram-negative BSI. A risk-score model was created by adding points for each independent risk factor, and had a c-statistic of 0.84. Patients with risk scores of 0, 4, 8, 12 and 16 had estimated 28-day mortality rates of approximately 0%, 3%, 14%, 45%, and 81%, respectively. The Gram-negative BSI risk score described herein estimated mortality risk with high discrimination in patients with Gram-negative BSI who received clinically adequate empirical antimicrobial therapy.

Impact of healthcare-associated acquisition on community-onset Gram-negative bloodstream infection: a population-based study: healthcare-associated Gram-negative BSI.

We performed a population-based study to examine the influence of healthcare-associated acquisition on pathogen distribution, antimicrobial resistance, short- and long-term mortality of community-onset Gram-negative bloodstream infections (BSI). We identified 733 unique patients with community-onset Gram-negative BSI (306 healthcare-associated and 427 community-acquired) among Olmsted County, Minnesota, residents from 1 January 1998 to 31 December 2007. Multivariate logistic regression was used to examine the association between healthcare-associated acquisition and microbiological etiology and antimicrobial resistance. Multivariate Cox proportional hazards regression was used to evaluate the influence of the site of acquisition on mortality. Healthcare-associated acquisition was predictive of Pseudomonas aeruginosa (odds ratio [OR] 3.14, 95% confidence intervals [CI]: 1.59-6.57) and the group of Enterobacter, Citrobacter, and Serratia species (OR 2.23, 95% CI: 1.21-4.21) as causative pathogens of community-onset Gram-negative BSI. Healthcare-associated acquisition was also predictive of fluoroquinolone resistance among community-onset Gram-negative bloodstream isolates (OR 2.27, 95% CI: 1.18-4.53). Healthcare-associated acquisition of BSI was independently associated with higher 28-day (hazard ratio [HR] 3.73, 95% CI: 2.13-6.93) and 1-year mortality (HR 3.60, 95% CI: 2.57-5.15). Because of differences in pathogen distribution, antimicrobial resistance, and outcomes between healthcare-associated and community-acquired Gram-negative BSI, identification of patients with healthcare-associated acquisition of BSI is essential to optimize empiric antimicrobial therapy.

Influence of referral bias on the clinical characteristics of patients with Gram-negative bloodstream infection.

Referral bias can influence the results of studies performed at tertiary-care centres. In this study, we evaluated demographic and microbiological factors that influenced referral of patients with Gram-negative bloodstream infection (BSI). We identified 2919 and 846 unique patients with Gram-negative BSI in a referral cohort of patients treated at Mayo Clinic Hospitals and a population-based cohort of Olmsted County, Minnesota, residents between 1 January 1998 and 31 December 2007, respectively. Multivariable logistic regression analysis was used to determine factors associated with referral. Elderly patients aged ≥80 years with Gram-negative BSI were less likely to be referred than younger patients [odds ratio (OR) 0·43, 95% confidence intervals (CI) 0·30-0·62] as were females (OR 0·63, 95% CI 0·53-0·74). After adjusting for age and gender, bloodstream isolates of Escherichia coli (OR 0·50, 95% CI 0·43-0·58) and Proteus mirabilis (OR 0·49, 95% CI 0·30-0·82) were underrepresented in the referral cohort; and Pseudomonas aeruginosa (OR 2·26, 95% CI 1·70-3·06), Enterobacter cloacae (OR 2·31, 95% CI 1·53-3·66), Serratia marcescens (OR 2·34, 95% CI 1·33-4·52) and Stenotrophomonas maltophilia (OR 17·94, 95% CI 3·98-314·43) were overrepresented in the referral cohort. We demonstrated that demographic and microbiological characteristics of patients with Gram-negative BSI had an influence on referral patterns. These factors should be considered when interpreting results of investigations performed at tertiary-care centres.

Epidemiology and outcome of Gram-negative bloodstream infection in children: a population-based study.

Population-based studies of Gram-negative bloodstream infection (BSI) in children are lacking. Therefore, we performed this population-based investigation in Olmsted County, Minnesota, to determine the incidence rate, site of acquisition, and outcome of Gram-negative BSI in children aged ⩽18 years. We used Kaplan-Meier method and Cox proportional hazard regression for mortality analysis. We identified 56 unique children with Gram-negative BSI during the past decade. The gender-adjusted incidence rate of Gram-negative BSI per 100 000 person-years was 129·7 [95% confidence interval (CI) 77·8-181·6]) in infants, with a sharp decline to 14·6 (95% CI 6·0-23·2) and 7·6 (95% CI 4·3-10·9) in children aged 1-4 and 5-18 years, respectively. The urinary tract was the most commonly identified source of infection (34%) and Escherichia coli was the most common pathogen isolated (38%). Over two-thirds (68%) of children had underlying medical conditions that predisposed to Gram-negative BSI. The overall 28-day and 1-year all-cause mortality rates were 11% (95% CI 3-18) and 18% (95% CI 8-28), respectively. Younger age and number of underlying medical conditions were associated with 28-day and 1-year mortality, respectively. Nosocomial or healthcare-associated acquisition was associated with both 28-day and 1-year mortality.

Temporal trends in Enterobacter species bloodstream infection: a population-based study from 1998-2007.

Enterobacter species are the fourth most common cause of Gram-negative bloodstream infection (BSI). We examined temporal changes and seasonal variation in the incidence rate of Enterobacter spp. BSI, estimated 28-day and 1-year mortality, and determined in vitro antimicrobial resistance rates of Enterobacter spp. bloodstream isolates in Olmsted County, Minnesota, from 1 January 1998 to 31 December 2007. Multivariable Poisson regression was used to examine temporal changes and seasonal variation in incidence rate and Kaplan-Meier method was used to estimate 28-day and 1-year mortality. The median age of patients with Enterobacter spp. BSI was 58 years and 53% were female. The overall age- and gender-adjusted incidence rate of Enterobacter spp. BSI was 3.3 per 100,000 person-years (95% CI 2.3-4.4). There was a linear trend of increasing incidence rate from 0.8 (95% CI 0-1.9) to 6.2 (95% CI 3.0-9.3) per 100,000 person-years between 1998 and 2007 (p 0.002). There was no significant difference in the incidence rate of Enterobacter spp. BSI during the warmest 4 months compared to the remainder of the year (incidence rate ratio 1.06; 95% CI 0.47-2.01). The overall 28-day and 1-year mortality rates of Enterobacter spp. BSI were 21% (95% CI 8-34%) and 38% (95% CI 22-53%), respectively. Up to 13% of Enterobacter spp. bloodstream isolates were resistant to third-generation cephalosporins. To our knowledge, this is the first population-based study to describe the epidemiology and outcome of Enterobacter spp. BSI. The increase in incidence rate of Enterobacter spp. BSI over the past decade, coupled with its associated antimicrobial resistance, dictate the need for further investigation of this syndrome.

Efficacy and safety of rifampin containing regimen for staphylococcal prosthetic joint infections treated with debridement and retention.

The aim of this study was to evaluate the efficacy and safety of rifampin for Staphylococcus aureus (SA) or coagulase negative staphylococci (CNS) prosthetic joint infection (PJI) treated with debridement and retention (D/R). We calculated the treatment failure cumulative incidence (TF) of a cohort of 101 patients with SA or CNS PJI treated with D/R and antimicrobial therapy. The effect of the use of a rifampin-based regimen was evaluated. Cox proportional hazards regression evaluated the association between treatment and time-to-TF controlling for the propensity to treat with rifampin and temporal confounders. Seven percent (1/14) of the prospective rifampin-treated patients, 32% (10/31) of the historical rifampin-treated patients and 38% (21/56) of the historical non-rifampin treated patients developed TF. After controlling for the propensity to treat with rifampin and American Society of Anesthesia scores, patients in the prospective cohort had a lower risk of TF compared to patients in the historical cohort not treated with rifampin (HR 0.11; 95%CI 0.01-0.84). None (0/14) of the patients in the prospective study developed hepatotoxicity. The outcome of staphylococcal PJI treated with D/R and rifampin-based regimens was better when compared with a historical cohort treated without rifampin.

Seasonal variation in Escherichia coli bloodstream infection: a population-based study.

Seasonal variation in the rates of infection with certain Gram-negative organisms has been previously examined in tertiary-care centres. We performed a population-based investigation to evaluate the seasonal variation in Escherichia coli bloodstream infection (BSI). We identified 461 unique patients in Olmsted County, Minnesota, from 1 January 1998 to 31 December 2007, with E. coli BSI. Incidence rates (IR) and IR ratios were calculated using Rochester Epidemiology Project tools. Multivariable Poisson regression was used to examine the association between the IR of E. coli BSI and average temperature. The age- and gender-adjusted IR of E. coli BSI per 100 000 person-years was 50.2 (95% CI 42.9-57.5) during the warmest 4 months (June through September) compared with 37.1 (95% CI 32.7-41.5) during the remainder of the year, resulting in a 35% (95% CI 12-66%) increase in IR during the warmest 4 months. The average temperature was predictive of increasing IR of E. coli BSI (p 0.004); there was a 7% (95% CI 2-12%) increase in the IR for each 10-degree Fahrenheit (c. 5.5 degrees C) increase in average temperature. To our knowledge, this is the first study to demonstrate seasonal variation in E. coli BSI, with a higher IR during the warmest 4 months than during the remainder of the year.

Kinetics of interferon-gamma producing cytomegalovirus (CMV)-specific CD4+ and CD8+ T lymphocytes and the risk of subsequent CMV viremia after allogeneic hematopoietic stem cell transplantation.

BACKGROUND: Deficiencies in cytomegalovirus (CMV)-specific T lymphocytes impair the immunologic response against CMV reactivation after allogeneic hematopoietic stem cell transplantation (HSCT). METHODS: A time-dependent analysis was conducted to determine the association between the percentages and kinetics of interferon-gamma-producing CMV-specific CD4+ and CD8+ T lymphocytes and CMV viremia among 30 allogeneic HSCT recipients. RESULTS: Higher percentages of CD4+ T lymphocytes activated with CMVpp65 (hazard ratio [HR]: 2.06; 95% confidence interval [95% CI]: 1.18-3.6; P=0.011) and CMV lysate (HR: 1.18; 95% CI: 0.99-1.42; P=0.072), and higher percentages of CD8+ T lymphocytes activated by CMV immediate early-1 (HR: 1.2; 95% CI: 1.01-1.43; P=0.038) and CMVpp65 (HR: 1.12; 95% CI: 1.0-1.27; P=0.060) were associated with time-to-CMV viremia. Furthermore, a higher degree in the decline of CMV lysate-activated CD4+ T lymphocytes (HR: 1.14; 95% CI: 0.96-1.36; P=0.125) and CMVpp65-activated CD8+ T lymphocytes (HR: 1.36; 95% CI: 1.03-1.78; P=0.031) was suggestive of or significantly associated with time-to-CMV viremia. CONCLUSIONS: Higher levels of CMV-specific CD4+ and CD8+ T lymphocytes were associated with subsequent CMV viremia after HSCT. The association between CMV viremia and the degree of decline in CMV-specific T lymphocytes suggests that severe disruption in homeostatic CMV-specific immune environment contributes to the immunopathogenesis of CMV after allogeneic HSCT.

Incidence rate and outcome of Gram-negative bloodstream infection in solid organ transplant recipients.

Bacterial infections are common complications of solid organ transplantation (SOT). In this study, we defined the incidence, mortality and in vitro antimicrobial resistance rates of Gram-negative bloodstream infection (BSI) in SOT recipients. We identified 223 patients who developed Gram-negative BSI among a cohort of 3367 SOT recipients who were prospectively followed at the Mayo Clinic (Rochester, MN) from January 1, 1996 to December 31, 2007. The highest incidence rate (IR) of Gram-negative BSI was observed within the first month following SOT (210.3/1000 person-years [95% confidence interval (CI): 159.3-268.3]), with a sharp decline to 25.7 (95% CI: 20.1-32.1) and 8.2 (95% CI: 6.7-10.0) per 1000 person-years between 2 and 12 months and more than 12 months following SOT, respectively. Kidney recipients were more likely to develop Gram-negative BSI after 12 months following transplantation than were liver recipients (10.3 [95% CI: 7.9-13.1] vs. 5.2 [95% CI: 3.1-7.8] per 1000 person-years). The overall unadjusted 28-day all-cause mortality of Gram-negative BSI was 4.9% and was lower in kidney than in liver recipients (1.6% vs. 13.2%, p < 0.001). We observed a linear trend of increasing resistance among Escherichia coli isolates to fluoroquinolone antibiotics from 0% to 44% (p = 0.002) throughout the study period. This increase in antimicrobial resistance may influence the choice of empiric therapy.

An insight into high-resolution mass-spectrometry data.

Mass spectrometry is a powerful tool with much promise in global proteomic studies. The discipline of statistics offers robust methodologies to extract and interpret high-dimensional mass-spectrometry data and will be a valuable contributor to the field. Here, we describe the process by which data are produced, characteristics of the data, and the analytical preprocessing steps that are taken in order to interpret the data and use it in downstream statistical analyses. Because of the complexity of data acquisition, statistical methods developed for gene expression microarray data are not directly applicable to proteomic data. Areas in need of statistical research for proteomic data include alignment, experimental design, abundance normalization, and statistical analysis.

Regression analysis for comparing protein samples with 16O/18O stable-isotope labeled mass spectrometry.

MOTIVATION: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for (16)O/(18)O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of (16)O/(18)O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies.

Protocols for the assurance of microarray data quality and process control.

Microarrays represent a powerful technology that provides the ability to simultaneously measure the expression of thousands of genes. However, it is a multi-step process with numerous potential sources of variation that can compromise data analysis and interpretation if left uncontrolled, necessitating the development of quality control protocols to ensure assay consistency and high-quality data. In response to emerging standards, such as the minimum information about a microarray experiment standard, tools are required to ascertain the quality and reproducibility of results within and across studies. To this end, an intralaboratory quality control protocol for two color, spotted microarrays was developed using cDNA microarrays from in vivo and in vitro dose-response and time-course studies. The protocol combines: (i) diagnostic plots monitoring the degree of feature saturation, global feature and background intensities, and feature misalignments with (ii) plots monitoring the intensity distributions within arrays with (iii) a support vector machine (SVM) model. The protocol is applicable to any laboratory with sufficient datasets to establish historical high- and low-quality data.