Analytical and Biological Variability of a Commercial Modified Aptamer Assay in Plasma Samples of Patients with Chronic Kidney Disease.

BACKGROUND: We carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD). METHODS: Plasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic. We also measured correlations of aptamer measurements with traditional biomarker assays. RESULTS: A total of 4656 unique proteins (4849 total aptamer measures) were analyzed in all samples. Median (interquartile range [IQR] intra-assay CV) was 3.7% (2.8-5.3) in CRIC and 5.0% (3.8-7.0) in Brigham samples. Median (IQR) biological CV among Brigham samples drawn from one individual on 2 occasions separated by median (IQR) 7 (4-14) days was 8.7% (6.2-14). CVs were independent of CKD stage, diabetes, or albuminuria but were higher in patients with systemic lupus erythematosus. Rho correlations between aptamer and traditional assays for biomarkers of interest were cystatin C = 0.942, kidney injury model-1 = 0.905, fibroblast growth factor-23 = 0.541, tumor necrosis factor receptors 1 = 0.781 and 2 = 0.843, P < 10-100 for all. CONCLUSIONS: Intra-assay and within-subject variability for SomaScan in the CKD setting was low and similar to assay variability reported from individuals without CKD. Intra-assay precision was excellent whether samples were collected in an optimal research protocol, as were CRIC samples, or in the clinical setting, as were the Brigham samples.

Assessing chromatin relocalization in 3D using the patient rule induction method.

Three-dimensional (3D) genome architecture is critical for numerous cellular processes, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Inferring 3D chromatin configurations has been advanced by the emergence of chromatin conformation capture assays, notably Hi-C, and attendant 3D reconstruction algorithms. These have enhanced understanding of chromatin spatial organization and afforded numerous downstream biological insights. Until recently, comparisons of 3D reconstructions between conditions and/or cell types were limited to prescribed structural features. However, multiMDS, a pioneering approach developed by Rieber and Mahony (2019). that performs joint reconstruction and alignment, enables quantification of all locus-specific differences between paired Hi-C data sets. By subsequently mapping these differences to the linear (1D) genome the identification of relocalization regions is facilitated through the use of peak calling in conjunction with continuous wavelet transformation. Here, we seek to refine this approach by performing the search for significant relocalization regions in terms of the 3D structures themselves, thereby retaining the benefits of 3D reconstruction and avoiding limitations associated with the 1D perspective. The search for (extreme) relocalization regions is conducted using the patient rule induction method (PRIM). Considerations surrounding orienting structures with respect to compartmental and principal component axes are discussed, as are approaches to inference and reconstruction accuracy assessment. The illustration makes recourse to comparisons between four different cell types.

Principal curve approaches for inferring 3D chromatin architecture.

Three-dimensional (3D) genome spatial organization is critical for numerous cellular processes, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Genome architecture had been notoriously difficult to elucidate, but the advent of the suite of chromatin conformation capture assays, notably Hi-C, has transformed understanding of chromatin structure and provided downstream biological insights. Although many findings have flowed from direct analysis of the pairwise proximity data produced by these assays, there is added value in generating corresponding 3D reconstructions deriving from superposing genomic features on the reconstruction. Accordingly, many methods for inferring 3D architecture from proximity data have been advanced. However, none of these approaches exploit the fact that single chromosome solutions constitute a one-dimensional (1D) curve in 3D. Rather, this aspect has either been addressed by imposition of constraints, which is both computationally burdensome and cell type specific, or ignored with contiguity imposed after the fact. Here, we target finding a 1D curve by extending principal curve methodology to the metric scaling problem. We illustrate how this approach yields a sequence of candidate solutions, indexed by an underlying smoothness or degrees-of-freedom parameter, and propose methods for selection from this sequence. We apply the methodology to Hi-C data obtained on IMR90 cells and so are positioned to evaluate reconstruction accuracy by referencing orthogonal imaging data. The results indicate the utility and reproducibility of our principal curve approach in the face of underlying structural variation.

Indoor Air Pollution and Susceptibility to Tuberculosis Infection in Urban Vietnamese Children.

Rationale: The Southeast Asian tuberculosis burden is high, and it remains unclear if urban indoor air pollution in this setting is exacerbating the epidemic. Objectives: To determine the associations of latent tuberculosis with common urban indoor air pollution sources (secondhand smoke, indoor motorcycle emissions, and cooking) in Southeast Asia. Methods: We enrolled child household contacts of patients with microbiologically confirmed active tuberculosis in Vietnam, from July 2017 to December 2019. We tested children for latent tuberculosis and evaluated air pollution exposures with questionnaires and personal aerosol sampling. We tested hypotheses using generalized estimating equations. Measurements and Main Results: We enrolled 72 patients with tuberculosis (27% with cavitary disease) and 109 of their child household contacts. Latent tuberculosis was diagnosed in 58 (53%) household contacts at baseline visit. Children experienced a 2.56-fold increased odds of latent tuberculosis for each additional household member who smoked (95% confidence interval, 1.27-5.16). Odds were highest among children exposed to indoor smokers and children <5 years old exposed to household smokers. Each residential floor above street-level pollution decreased the odds of latent tuberculosis by 36% (adjusted odds ratio, 0.64; 95% confidence interval, 0.42-0.96). Motorcycles parked inside children's homes and cooking with liquid petroleum gas compared with electricity increased the odds of latent tuberculosis, whereas kitchen ventilation decreased the effect, but these findings were not statistically significant. Conclusions: Common urban indoor air pollution sources were associated with increased odds of latent tuberculosis infection in child household contacts of patients with active tuberculosis.

Composition and origin of lung fluid proteome in premature infants and relationship to respiratory outcome.

BACKGROUND: Infants born at extremely low gestational age are at high risk for bronchopulmonary dysplasia and continuing lung disease. There are no early clinical biomarkers for pulmonary outcome and limited therapeutic interventions. OBJECTIVES: We performed global proteomics of premature infant tracheal aspirate (TA) and plasma to determine the composition and source of lung fluid proteins and to identify potential biomarkers of respiratory outcome. METHODS: TA samples were collected from intubated infants in the TOLSURF cohort before and after nitric oxide treatment, and plasma was collected from NO CLD infants. Protein abundance was assayed by HPLC/tandem mass spectrometry and Protein Prospector software. mRNA abundance in mid-gestation fetal lung was assessed by RNA sequencing. Pulmonary morbidity was defined as a need for ventilatory support at term and during the first year. RESULTS: Abundant TA proteins included albumin, hemoglobin, and actin-related proteins. 96 of 137 detected plasma proteins were present in TA (r = 0.69, p<0.00001). Based on lung RNAseq data, ~88% of detected TA proteins in injured infant lung are derived at least in part from lung epithelium with overrepresentation in categories of cell membrane/secretion and stress/inflammation. Comparing 37 infants at study enrollment (7-14 days) who did or did not develop persistent pulmonary morbidity, candidate biomarkers of both lung (eg., annexin A5) and plasma (eg., vitamin D-binding protein) origin were identified. Notably, levels of free hemoglobin were 2.9-fold (p = 0.03) higher in infants with pulmonary morbidity. In time course studies, hemoglobin decreased markedly in most infants after enrollment coincident with initiation of inhaled nitric oxide treatment. CONCLUSIONS: We conclude that both lung epithelium and plasma contribute to the lung fluid proteome in premature infants with lung injury. Early postnatal elevation of free hemoglobin and heme, which are both pro-oxidants, may contribute to persistent lung disease by depleting nitric oxide and increasing oxidative/nitrative stress.

Assessing stationary distributions derived from chromatin contact maps.

BACKGROUND: The spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation, while architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Thus, eliciting chromatin conformation is important, yet challenging due to compaction, dynamics and scale. However, a variety of recent assays, in particular Hi-C, have generated new details of chromatin structure, spawning a number of novel biological findings. Many findings have resulted from analyses on the level of native contact data as generated by the assays. Alternatively, reconstruction based approaches often proceed by first converting contact frequencies into distances, then generating a three dimensional (3D) chromatin configuration that best recapitulates these distances. Subsequent analyses can enrich contact level analyses via superposition of genomic attributes on the reconstruction. But, such advantages depend on the accuracy of the reconstruction which, absent gold standards, is inherently difficult to assess. Attempts at accuracy evaluation have relied on simulation and/or FISH imaging that typically features a handful of low resolution probes. While newly advanced multiplexed FISH imaging offers possibilities for refined 3D reconstruction accuracy evaluation, availability of such data is limited due to assay complexity and the resolution thereof is appreciably lower than the reconstructions being assessed. Accordingly, there is demand for new methods of reconstruction accuracy appraisal. RESULTS: Here we explore the potential of recently proposed stationary distributions, hereafter StatDns, derived from Hi-C contact matrices, to serve as a basis for reconstruction accuracy assessment. Current usage of such StatDns has focussed on the identification of highly interactive regions (HIRs): computationally defined regions of the genome purportedly involved in numerous long-range intra-chromosomal contacts. Consistent identification of HIRs would be informative with respect to inferred 3D architecture since the corresponding regions of the reconstruction would have an elevated number of k nearest neighbors (kNNs). More generally, we anticipate a monotone decreasing relationship between StatDn values and kNN distances. After initially evaluating the reproducibility of StatDns across replicate Hi-C data sets, we use this implied StatDn - kNN relationship to gauge the utility of StatDns for reconstruction validation, making recourse to both real and simulated examples. CONCLUSIONS: Our analyses demonstrate that, as constructed, StatDns do not provide a suitable measure for assessing the accuracy of 3D genome reconstructions. Whether this is attributable to specific choices surrounding normalization in defining StatDns or to the logic underlying their very formulation remains to be determined.

Surfactant status and respiratory outcome in premature infants receiving late surfactant treatment.

BACKGROUND: Many premature infants with respiratory failure are deficient in surfactant, but the relationship to occurrence of bronchopulmonary dysplasia (BPD) is uncertain. METHODS: Tracheal aspirates were collected from 209 treated and control infants enrolled at 7-14 days in the Trial of Late Surfactant. The content of phospholipid, surfactant protein B, and total protein were determined in large aggregate (active) surfactant. RESULTS: At 24 h, surfactant treatment transiently increased surfactant protein B content (70%, p < 0.01), but did not affect recovered airway surfactant or total protein/phospholipid. The level of recovered surfactant during dosing was directly associated with content of surfactant protein B (r = 0.50, p < 0.00001) and inversely related to total protein (r = 0.39, p < 0.0001). For all infants, occurrence of BPD was associated with lower levels of recovered large aggregate surfactant, higher protein content, and lower SP-B levels. Tracheal aspirates with lower amounts of recovered surfactant had an increased proportion of small vesicle (inactive) surfactant. CONCLUSIONS: We conclude that many intubated premature infants are deficient in active surfactant, in part due to increased intra-alveolar metabolism, low SP-B content, and protein inhibition, and that the severity of this deficit is predictive of BPD. Late surfactant treatment at the frequency used did not provide a sustained increase in airway surfactant.

Improved accuracy assessment for 3D genome reconstructions.

BACKGROUND: Three dimensional (3D) genome spatial organization is critical for numerous cellular functions, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Genome conformation had been difficult to elucidate but the advent chromatin conformation capture assays, notably Hi-C, has transformed understanding of chromatin architecture and yielded numerous biological insights. Although most of these findings have flowed from analysis of proximity data produced by these assays, added value in generating 3D reconstructions has been demonstrated, deriving, in part, from superposing genomic features on the reconstruction. However, advantages of 3D structure-based analyses are clearly conditional on the accuracy of the attendant reconstructions, which is difficult to assess. Proponents of competing reconstruction algorithms have evaluated their accuracy by recourse to simulation of toy structures and/or limited fluorescence in situ hybridization (FISH) imaging that features a handful of low resolution probes. Accordingly, new methods of reconstruction accuracy assessment are needed. RESULTS: Here we utilize two recently devised assays to develop methodology for assessing 3D reconstruction accuracy. Multiplex FISH increases the number of probes by an order of magnitude and hence the number of inter-probe distances by two orders, providing sufficient information for structure-level evaluation via mean-squared deviations (MSD). Crucially, underscoring multiplex FISH applications are large numbers of coordinate-system aligned replicates that provide the basis for a referent distribution for MSD statistics. Using this system we show that reconstructions based on Hi-C data for IMR90 cells are accurate for some chromosomes but not others. The second new assay, genome architecture mapping, utilizes large numbers of thin cryosections to obtain a measure of proximity. We exploit the planarity of the cryosections - not used in inferring proximity - to obtain measures of reconstruction accuracy, with referents provided via resampling. Application to mouse embryonic stem cells shows reconstruction accuracies that vary by chromosome. CONCLUSIONS: We have developed methods for assessing the accuracy of 3D genome reconstructions that exploit features of recently advanced multiplex FISH and genome architecture mapping assays. These approaches can help overcome the absence of gold standards for making such assessments which are important in view of the considerable uncertainties surrounding 3D genome reconstruction.

Factors Associated with Frailty and Its Trajectory among Patients on Hemodialysis.

BACKGROUND AND OBJECTIVES: Frailty is common among patients on hemodialysis and associated with adverse outcomes. However, little is known about changes in frailty over time and the factors associated with those changes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: To address these questions, we examined 762 participants in the A Cohort to Investigate the Value of Exercise/Analyses Designed to Investigate the Paradox of Obesity and Survival in ESRD cohort study, among whom frailty was assessed at baseline and 12 and 24 months. We used ordinal generalized estimating equations analyses and modeled frailty (on a scale from zero to five possible components) and death during follow-up. RESULTS: The mean frailty score at baseline was 1.9, and the distribution of frailty scores was similar at each evaluation. However, most participants' scores changed, with patients improving almost as often as worsening (overall change, 0.2 points per year; 95% confidence interval, 0.1 to 0.3). Hispanic ethnicity (0.6 points per year; 95% confidence interval, 0.0 to 1.1) and diabetes (0.7 points per year; 95% confidence interval, 0.3 to 1.0) were associated with higher frailty scores and higher serum albumin concentration with lower frailty scores (-1.1 points per g/dl; 95% confidence interval, -1.5 to -0.7). In addition, patients whose serum albumin increased over time were less likely to become frail, with each 1-g/dl increase in albumin associated with a 0.4-point reduction in frailty score (95% confidence interval, -0.80 to -0.05). To examine the underpinnings of the association between serum albumin and frailty, we included serum IL-6, normalized protein catabolic rate, and patient self-report of hospitalization within the last year in a second model. Higher IL-6 and hospitalization were statistically significantly associated with worse frailty at any point and worsening frailty over time, whereas normalized protein catabolic rate was not independently associated with frailty. CONCLUSIONS: There was substantial year to year variability in frailty scores, with approximately equal numbers of patients improving and worsening. Markers of inflammation and hospitalization were independently associated with worsening frailty. Studies should examine whether interventions to address inflammation or posthospitalization rehabilitation can improve the trajectory of frailty.

Antiinflammatory Effects of Budesonide in Human Fetal Lung.

Lung inflammation in premature infants contributes to the development of bronchopulmonary dysplasia (BPD), a chronic lung disease with long-term sequelae. Pilot studies administering budesonide suspended in surfactant have found reduced BPD without the apparent adverse effects that occur with systemic dexamethasone therapy. Our objective was to determine budesonide potency, stability, and antiinflammatory effects in human fetal lung. We cultured explants of second-trimester fetal lung with budesonide or dexamethasone and used microscopy, immunoassays, RNA sequencing, liquid chromatography/tandem mass spectrometry, and pulsating bubble surfactometry. Budesonide suppressed secreted chemokines IL-8 and CCL2 (MCP-1) within 4 hours, reaching a 90% decrease at 12 hours, which was fully reversed 72 hours after removal of the steroid. Half-maximal effects occurred at 0.04-0.05 nM, representing a fivefold greater potency than for dexamethasone. Budesonide significantly induced 3.6% and repressed 2.8% of 14,500 sequenced mRNAs by 1.6- to 95-fold, including 119 genes that contribute to the glucocorticoid inflammatory transcriptome; some are known targets of nuclear factor-κB. By global proteomics, 22 secreted inflammatory proteins were hormonally regulated. Two glucocorticoid-regulated genes of interest because of their association with lung disease are CHI3L1 and IL1RL1. Budesonide retained activity in the presence of surfactant and did not alter its surface properties. There was some formation of palmitate-budesonide in lung tissue but no detectable metabolism to inactive 16α-hydroxy prednisolone. We concluded that budesonide is a potent and stable antiinflammatory glucocorticoid in human fetal lung in vitro, supporting a beneficial antiinflammatory response to lung-targeted budesonide:surfactant treatment of infants for the prevention of BPD.

Identification of Discrete Prognostic Groups in Ewing Sarcoma.

BACKGROUND: Although multiple prognostic variables have been proposed for Ewing sarcoma (EWS), little work has been done to further categorize these variables into prognostic groups for risk classification. PROCEDURE: We derived initial prognostic groups from 2,124 patients with EWS in the SEER database. We constructed a multivariable recursive partitioning model of overall survival using the following covariates: age; stage; race/ethnicity; sex; axial primary; pelvic primary; and bone or soft tissue primary. Based on this model, we identified risk groups and estimated 5-year overall survival for each group using Kaplan-Meier methods. We then applied these groups to 1,680 patients enrolled on COG clinical trials. RESULTS: A multivariable model identified five prognostic groups with significantly different overall survival: (i) localized, age <18 years, non-pelvic primary; (ii) localized, age <18, pelvic primary or localized, age ≥18, white, non-Hispanic; (iii) localized, age ≥18, all races/ethnicities other than white, non-Hispanic; (iv) metastatic, age <18; and (v) metastatic, age ≥18. These five groups were applied to the COG dataset and showed significantly different overall and event-free survival based upon this classification system (P < 0.0001). A sub-analysis of COG patients treated with ifosfamide and etoposide as a component of therapy evaluated these findings in patients receiving contemporary therapy. CONCLUSIONS: Recursive partitioning analysis yields discrete prognostic groups in EWS that provide valuable information for patients and clinicians in determining an individual patient's risk of death. These groups may enable future clinical trials to adjust EWS treatment according to individualized risk.

Reconstruction of 3D genome architecture via a two-stage algorithm.

BACKGROUND: The three-dimensional (3D) configuration of chromosomes within the eukaryote nucleus is an important factor for several cellular functions, including gene expression regulation, and has also been linked with cancer-causing translocation events. While visualization of such architecture remains limited to low resolutions, the ability to infer structures at increasing resolutions has been enabled by recently-devised chromosome conformation capture techniques. In particular, when coupled with next generation sequencing, such methods yield an inventory of genome-wide chromatin contacts or interactions. Various algorithms have been advanced to operate on such contact data to produce reconstructed 3D configurations. Studies have shown that these reconstructions can provide added value over raw interaction data with respect to downstream biological insights. However, only limited, low-resolution reconstructions have been realized for mammals due to computational bottlenecks. RESULTS: Here we propose a two-stage algorithm to partially overcome these computational barriers. The central idea is to initially utilize existing reconstruction techniques on an individual chromosome basis, using intra-chromosomal contacts, and then to relatively position these chromosome-level reconstructions using inter-chromosomal contacts. This two-stage strategy represents a natural approach in view of the within- versus between- chromosome distribution of contacts. It can increase resolution ≈ 20 fold for mouse and human. After describing the algorithm we present 3D architectures for mouse embryonic stem cells and human lymphoblastoid cells. We evaluate the impact of several factors on reconstruction reproducibility and explore a variety of sampling schemes. We further analyze replicate data at differing resolutions obtained from recently devised in situ Hi-C assays. In all instances we demonstrate insensitivity of the whole-genome 3D reconstruction obtained by the two-stage algorithm to the sampling strategy used. CONCLUSIONS: Our two-stage algorithm has the potential to significantly increase the resolution of 3D genome reconstructions. The improvements are such that we can progress from 1 Mb resolution to 100 kb resolution, notable since this latter value has been identified as critical to inferring topological domains in analyses performed on the contact (rather than 3D) level.

Reproducibility of 3D chromatin configuration reconstructions.

It is widely recognized that the three-dimensional (3D) architecture of eukaryotic chromatin plays an important role in processes such as gene regulation and cancer-driving gene fusions. Observing or inferring this 3D structure at even modest resolutions had been problematic, since genomes are highly condensed and traditional assays are coarse. However, recently devised high-throughput molecular techniques have changed this situation. Notably, the development of a suite of chromatin conformation capture (CCC) assays has enabled elicitation of contacts-spatially close chromosomal loci-which have provided insights into chromatin architecture. Most analysis of CCC data has focused on the contact level, with less effort directed toward obtaining 3D reconstructions and evaluating the accuracy and reproducibility thereof. While questions of accuracy must be addressed experimentally, questions of reproducibility can be addressed statistically-the purpose of this paper. We use a constrained optimization technique to reconstruct chromatin configurations for a number of closely related yeast datasets and assess reproducibility using four metrics that measure the distance between 3D configurations. The first of these, Procrustes fitting, measures configuration closeness after applying reflection, rotation, translation, and scaling-based alignment of the structures. The others base comparisons on the within-configuration inter-point distance matrix. Inferential results for these metrics rely on suitable permutation approaches. Results indicate that distance matrix-based approaches are preferable to Procrustes analysis, not because of the metrics per se but rather on account of the ability to customize permutation schemes to handle within-chromosome contiguity. It has recently been emphasized that the use of constrained optimization approaches to 3D architecture reconstruction are prone to being trapped in local minima. Our methods of reproducibility assessment provide a means for comparing 3D reconstruction solutions so that we can discern between local and global optima by contrasting solutions under perturbed inputs.

13C NMR metabolomic evaluation of immediate and delayed mild hypothermia in cerebrocortical slices after oxygen-glucose deprivation.

BACKGROUND: Mild brain hypothermia (32°-34°C) after human neonatal asphyxia improves neurodevelopmental outcomes. Astrocytes but not neurons have pyruvate carboxylase and an acetate uptake transporter. C nuclear magnetic resonance spectroscopy of rodent brain extracts after administering [1-C]glucose and [1,2-C]acetate can distinguish metabolic differences between glia and neurons, and tricarboxylic acid cycle entry via pyruvate dehydrogenase and pyruvate carboxylase. METHODS: Neonatal rat cerebrocortical slices receiving a C-acetate/glucose mixture underwent a 45-min asphyxia simulation via oxygen-glucose-deprivation followed by 6 h of recovery. Protocols in three groups of N=3 experiments were identical except for temperature management. The three temperature groups were: normothermia (37°C), hypothermia (32°C for 3.75 h beginning at oxygen--glucose deprivation start), and delayed hypothermia (32°C for 3.75 h, beginning 15 min after oxygen-glucose deprivation start). Multivariate analysis of nuclear magnetic resonance metabolite quantifications included principal component analyses and the L1-penalized regularized regression algorithm known as the least absolute shrinkage and selection operator. RESULTS: The most significant metabolite difference (P<0.0056) was [2-C]glutamine's higher final/control ratio for the hypothermia group (1.75±0.12) compared with ratios for the delayed (1.12±0.12) and normothermia group (0.94±0.06), implying a higher pyruvate carboxylase/pyruvate dehydrogenase ratio for glutamine formation. Least Absolute Shrinkage and Selection Operator found the most important metabolites associated with adenosine triphosphate preservation: [3,4-C]glutamate-produced via pyruvate dehydrogenase entry, [2-C]taurine-an important osmolyte and antioxidant, and phosphocreatine. Final principal component analyses scores plots suggested separate cluster formation for the hypothermia group, but with insufficient data for statistical significance. CONCLUSIONS: Starting mild hypothermia simultaneously with oxygen-glucose deprivation, compared with delayed starting or no hypothermia, has higher pyruvate carboxylase throughput, suggesting that better glial integrity is one important neuroprotection mechanism of earlier hypothermia.

Analytical validation of a practical molecular assay prognostic of survival in nonsquamous non-small cell lung cancer.

A molecular assay prognostic of survival in resected nonsquamous non-small cell lung cancer designed to meet the need for improved risk stratification in early-stage disease has recently been described. This assay measures the expression levels of 14 genes using RNA extracted from formalin-fixed, paraffin-embedded (FFPE) tissues. The assay underwent blinded clinical validation in 2 large international cohorts involving approximately 1500 patients; the analytical precision and reproducibility of this assay, however, have not yet been reported. For each of the 14 TaqMan quantitative polymerase chain reaction (PCR) primer and probe sets used in the molecular prognostic assay, the linear range, PCR efficiency, limits of blank, limits of quantitation, and quantitative bias were determined using serial dilutions of pooled RNA extracted from FFPE samples. The reproducibility of the entire molecular assay was determined by performing repeat testing of FFPE samples over multiple days. The linear range of individual quantitative TaqMan PCR primer and probe sets was between 2(10)- and 2(15)-fold input RNA. The median C(T) of the quantitative PCR primer and probe sets at 10 ng of input RNA was 24.3; the median efficiency was 91.2%. The median quantitative bias across all quantitative PCR primer and probe sets was 0.75% (range, 0.32% to 1.32%). In repeat testing, the mean SD of the risk score (scaled from 1 to 100) was 2.18, with a mean coefficient of variation of 0.08. The molecular prognostic assay presented in this study demonstrates high precision and reproducibility, validating its clinical utility as a reliable prognostic tool that can contribute to the management of patients with early-stage disease.

Querying genomic databases: refining the connectivity map.

The advent of high-throughput biotechnologies, which can efficiently measure gene expression on a global basis, has led to the creation and population of correspondingly rich databases and compendia. Such repositories have the potential to add enormous scientific value beyond that provided by individual studies which, due largely to cost considerations, are typified by small sample sizes. Accordingly, substantial effort has been invested in devising analysis schemes for utilizing gene-expression repositories. Here, we focus on one such scheme, the Connectivity Map (cmap), that was developed with the express purpose of identifying drugs with putative efficacy against a given disease, where the disease in question is characterized by a (differential) gene-expression signature. Initial claims surrounding cmap intimated that such tools might lead to new, previously unanticipated applications of existing drugs. However, further application suggests that its primary utility is in connecting a disease condition whose biology is largely unknown to a drug whose mechanisms of action are well understood, making cmap a tool for enhancing biological knowledge.The success of the Connectivity Map is belied by its simplicity. The aforementioned signature serves as an unordered query which is applied to a customized database of (differential) gene-expression experiments designed to elicit response to a wide range of drugs, across of spectrum of concentrations, durations, and cell lines. Such application is effected by computing a per experiment score that measures "closeness" between the signature and the experiment. Top-scoring experiments, and the attendant drug(s), are then deemed relevant to the disease underlying the query. Inference supporting such elicitations is pursued via re-sampling. In this paper, we revisit two key aspects of the Connectivity Map implementation. Firstly, we develop new approaches to measuring closeness for the common scenario wherein the query constitutes an ordered list. These involve using metrics proposed for analyzing partially ranked data, these being of interest in their own right and not widely used. Secondly, we advance an alternate inferential approach based on generating empirical null distributions that exploit the scope, and capture dependencies, embodied by the database. Using these refinements we undertake a comprehensive re-evaluation of Connectivity Map findings that, in general terms, reveal that accommodating ordered queries is less critical than the mode of inference.

A practical molecular assay to predict survival in resected non-squamous, non-small-cell lung cancer: development and international validation studies.

BACKGROUND: The frequent recurrence of early-stage non-small-cell lung cancer (NSCLC) is generally attributable to metastatic disease undetected at complete resection. Management of such patients depends on prognostic staging to identify the individuals most likely to have occult disease. We aimed to develop and validate a practical, reliable assay that improves risk stratification compared with conventional staging. METHODS: A 14-gene expression assay that uses quantitative PCR, runs on formalin-fixed paraffin-embedded tissue samples, and differentiates patients with heterogeneous statistical prognoses was developed in a cohort of 361 patients with non-squamous NSCLC resected at the University of California, San Francisco. The assay was then independently validated by the Kaiser Permanente Division of Research in a masked cohort of 433 patients with stage I non-squamous NSCLC resected at Kaiser Permanente Northern California hospitals, and on a cohort of 1006 patients with stage I-III non-squamous NSCLC resected in several leading Chinese cancer centres that are part of the China Clinical Trials Consortium (CCTC). FINDINGS: Kaplan-Meier analysis of the Kaiser validation cohort showed 5 year overall survival of 71·4% (95% CI 60·5-80·0) in low-risk, 58·3% (48·9-66·6) in intermediate-risk, and 49·2% (42·2-55·8) in high-risk patients (p(trend)=0·0003). Similar analysis of the CCTC cohort indicated 5 year overall survivals of 74·1% (66·0-80·6) in low-risk, 57·4% (48·3-65·5) in intermediate-risk, and 44·6% (40·2-48·9) in high-risk patients (p(trend)<0·0001). Multivariate analysis in both cohorts indicated that no standard clinical risk factors could account for, or provide, the prognostic information derived from tumour gene expression. The assay improved prognostic accuracy beyond National Comprehensive Cancer Network criteria for stage I high-risk tumours (p<0·0001), and differentiated low-risk, intermediate-risk, and high-risk patients within all disease stages. INTERPRETATION: Our practical, quantitative-PCR-based assay reliably identified patients with early-stage non-squamous NSCLC at high risk for mortality after surgical resection. FUNDING: UCSF Thoracic Oncology Laboratory and Pinpoint Genomics.

Metabolomics of oxidative stress in recent studies of endogenous and exogenously administered intermediate metabolites.

Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites-pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate-whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing "omics"-based, diagnostic tests to help influence therapies.

Outcome-related metabolomic patterns from 1H/31P NMR after mild hypothermia treatments of oxygen-glucose deprivation in a neonatal brain slice model of asphyxia.

Human clinical trials using 72 hours of mild hypothermia (32°C-34°C) after neonatal asphyxia have found substantially improved neurologic outcomes. As temperature changes differently modulate numerous metabolite fluxes and concentrations, we hypothesized that (1)H/(31)P nuclear magnetic resonance (NMR) spectroscopy of intracellular metabolites can distinguish different insults, treatments, and recovery stages. Three groups of superfused neonatal rat brain slices underwent 45 minutes oxygen-glucose deprivation (OGD) and then were: treated for 3 hours with mild hypothermia (32°C) that began with OGD, or similarly treated with hypothermia after a 15-minute delay, or not treated (normothermic control group, 37°C). Hypothermia was followed by 3 hours of normothermic recovery. Slices collected at different predetermined times were processed, respectively, for 14.1 Tesla NMR analysis, enzyme-linked immunosorbent assay (ELISA) cell-death quantification, and superoxide production. Forty-nine NMR-observable metabolites underwent a multivariate analysis. Separated clustering in scores plots was found for treatment and outcome groups. Final ATP (adenosine triphosphate) levels, severely decreased at normothermia, were restored equally by immediate and delayed hypothermia. Cell death was decreased by immediate hypothermia, but was equally substantially greater with normothermia and delayed hypothermia. Potentially important biomarkers in the (1)H spectra included PCr-(1)H (phosphocreatine in the (1)H spectrum), ATP-(1)H (adenosine triphosphate in the (1)H spectrum), and ADP-(1)H (adenosine diphosphate in the (1)H spectrum). The findings suggest a potential role for metabolomic monitoring during therapeutic hypothermia.

Clustering with exclusion zones: genomic applications.

Methods for formally evaluating the clustering of events in space or time, notably the scan statistic, have been richly developed and widely applied. In order to utilize the scan statistic and related approaches, it is necessary to know the extent of the spatial or temporal domains wherein the events arise. Implicit in their usage is that these domains have no "holes"-hereafter "exclusion zones"-regions in which events a priori cannot occur. However, in many contexts, this requirement is not met. When the exclusion zones are known, it is straightforward to correct the scan statistic for their occurrence by simply adjusting the extent of the domain. Here, we tackle the more ambitious objective of formally evaluating clustering in the presence of "unknown" exclusion zones. We develop an algorithm for estimating total exclusion zone extent, the quantity needed to correct scan statistic-based inference, using distributional properties of "spacings," and show how bias correction for this estimator can be effected. Performance of the algorithm is assessed via simulation study. We showcase applications to genomic settings for differing marker (event) types-binding sites, housekeeping genes, and microRNAs-wherein exclusion zones can arise through a variety of mechanisms. In several instances, dramatic changes to unadjusted inference that does not accommodate exclusions are evidenced.