The stability of the circulating human proteome to variations in sample collection and handling procedures measured with an aptamer-based proteomics array

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

Cold and Hungry: Heterothermy Is Associated with Low Leptin Levels in a Bulk Grazer during a Drought

AbstractReduced energy intake can compromise the ability of a mammal to maintain body temperature within a narrow 24-h range, leading to heterothermy. To investigate the main drivers of heterothermy in a bulk grazer, we compared abdominal temperature, body mass, body condition index, and serum leptin levels in 11 subadult Cape buffalo (Syncerus caffer caffer) during a drought year and a nondrought year. Low food availability during the drought year (as indexed by grass biomass, satellite imagery of vegetation greenness, and fecal chlorophyll) resulted in lower body condition index, lower body mass relative to that expected for an equivalent-aged buffalo, and lower leptin levels. The range of 24-h body temperature rhythm was 2°C during the nondrought year and more than double that during the drought year, and this was caused primarily by a lower minimum 24-h body temperature rhythm during the cool dry winter months. After rain fell and vegetation greenness increased, the minimum 24-h body temperature rhythm increased, and the range of 24-h body temperature rhythm was smaller than 2°C. In order of importance, poor body condition, low minimum 24-h air temperature, and low serum leptin levels were the best predictors of the increase in the range of 24-h body temperature rhythm. While the thermoregulatory role of leptin is not fully understood, the association between range of 24-h body temperature rhythm and serum leptin levels provides clues about the underlying mechanism behind the increased heterothermy in large mammals facing food restriction.

The protein corona from nanomedicine to environmental science

The protein corona spontaneously develops and evolves on the surface of nanoscale materials when they are exposed to biological environments, altering their physiochemical properties and affecting their subsequent interactions with biosystems. In this Review, we provide an overview of the current state of protein corona research in nanomedicine. We next discuss remaining challenges in the research methodology and characterization of the protein corona that slow the development of nanoparticle therapeutics and diagnostics, and we address how artificial intelligence can advance protein corona research as a complement to experimental research efforts. We then review emerging opportunities provided by the protein corona to address major issues in healthcare and environmental sciences. This Review details how mechanistic insights into nanoparticle protein corona formation can broadly address unmet clinical and environmental needs, as well as enhance the safety and efficacy of nanobiotechnology products.

Measurements of heterogeneity in proteomics analysis of the nanoparticle protein corona across core facilities

Robust characterization of the protein corona-the layer of proteins that spontaneously forms on the surface of nanoparticles immersed in biological fluids-is vital for prediction of the safety, biodistribution, and diagnostic/therapeutic efficacy of nanomedicines. Protein corona identity and abundance characterization is entirely dependent on liquid chromatography coupled to mass spectroscopy (LC-MS/MS), though the variability of this technique for the purpose of protein corona characterization remains poorly understood. Here we investigate the variability of LC-MS/MS workflows in analysis of identical aliquots of protein coronas by sending them to different proteomics core-facilities and analyzing the retrieved datasets. While the shared data between the cores correlate well, there is considerable heterogeneity in the data retrieved from different cores. Specifically, out of 4022 identified unique proteins, only 73 (1.8%) are shared across the core facilities providing semiquantitative analysis. These findings suggest that protein corona datasets cannot be easily compared across independent studies and more broadly compromise the interpretation of protein corona research, with implications in biomarker discovery as well as the safety and efficacy of our nanoscale biotechnologies.

Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.

Association between Circulating Protein C Levels and Incident Dementia: The Atherosclerosis Risk in Communities Study

INTRODUCTION

Hemostasis depends on the delicate balance between coagulants and anticoagulants. Higher levels of circulating coagulants have been associated with higher risk of cerebral infarctions and dementia. In contrast, higher levels of circulating protein C, an endogenous anticoagulant, have been associated with lower risk of cerebral infarctions, and the association between protein C levels and the risk of dementia is unknown. The goal of this study was to evaluate the association of circulating protein C levels in midlife and late life with incident dementia.

METHODS

Circulating protein C levels were measured using blood samples collected at the midlife baseline (1987-1989) and the late-life baseline (2011-2013) among 14,462 and 3,614 participants, respectively, in the Atherosclerosis Risk in Communities study. Protein C levels were measured using enzyme-linked immunosorbent assay at midlife and a modified aptamer-based assay at late life. Participants were followed up to 2013 from midlife and up to 2017 from late life. Incident dementia was ascertained during the follow-up periods using in-person cognitive and functional assessment, informant interviews, and International Classification of Diseases codes at hospitalization discharge and on death certificates. Cause-specific Cox regression models were used to evaluate the association between quintiles of circulating protein C and incident dementia.

RESULTS

From midlife (mean age of 54), 1,389 incident dementia events were observed over a median follow-up of 23 years. From late life (mean age of 75), 353 incident dementia events were observed over a median follow-up of 4.9 years. At both midlife and late life, circulating protein C had an inverse association with incident dementia after adjusting for demographic, vascular, and hemostatic risk factors, incident stroke as time-dependent covariate, and incorporating stabilized weights based on propensity scores (quintile 5 vs. quintile 1 as the reference, midlife hazard ratio 0.80, 95% confidence interval 0.66-0.96, p value for trend 0.04; late-life hazard ratio 0.84, 95% confidence interval: 0.55-1.28, p value for trend 0.04).

DISCUSSION/CONCLUSION

Circulating protein C has an inverse association with incident dementia independent of established risk factors, including stroke. Our results suggest studying anticoagulants in addition to coagulants can increase our understanding on the relationship between hemostasis and dementia.

DNA methylation during human adipogenesis and the impact of fructose

BACKGROUND

Increased adipogenesis and altered adipocyte function contribute to the development of obesity and associated comorbidities. Fructose modified adipocyte metabolism compared to glucose, but the regulatory mechanisms and consequences for obesity are unknown. Genome-wide methylation and global transcriptomics in SGBS pre-adipocytes exposed to 0, 2.5, 5, and 10 mM fructose, added to a 5-mM glucose-containing medium, were analyzed at 0, 24, 48, 96, 192, and 384 h following the induction of adipogenesis.

RESULTS

Time-dependent changes in DNA methylation compared to baseline (0 h) occurred during the final maturation of adipocytes, between 192 and 384 h. Larger percentages (0.1% at 192 h, 3.2% at 384 h) of differentially methylated regions (DMRs) were found in adipocytes differentiated in the glucose-containing control media compared to adipocytes differentiated in fructose-supplemented media (0.0006% for 10 mM, 0.001% for 5 mM, and 0.005% for 2.5 mM at 384 h). A total of 1437 DMRs were identified in 5237 differentially expressed genes at 384 h post-induction in glucose-containing (5 mM) control media. The majority of them inversely correlated with the gene expression, but 666 regions were positively correlated to the gene expression.

CONCLUSIONS

Our studies demonstrate that DNA methylation regulates or marks the transformation of morphologically differentiating adipocytes (seen at 192 h), to the more mature and metabolically robust adipocytes (as seen at 384 h) in a genome-wide manner. Lower (2.5 mM) concentrations of fructose have the most robust effects on methylation compared to higher concentrations (5 and 10 mM), suggesting that fructose may be playing a signaling/regulatory role at lower concentrations of fructose and as a substrate at higher concentrations.

Blood proteome profiling using aptamer-based technology for rejection biomarker discovery in transplantation

Face transplantation is a promising solution for patients with devastating facial injuries who lack other satisfactory treatment options. At the same time, this type of transplantation is accompanied with high risks of acute transplant rejection. The limitations of traditional skin biopsy and the need to frequently monitor the condition of face transplant call for less invasive biomarkers to better diagnose and treat acute rejection. Discovery of peripheral serum proteins accurately reflecting the transplant status would represent a reasonable solution to meet this demand. However, to date, there is no clinical data available to address the feasibility of this approach. In this study, we used the next generation aptamer-based SOMAscan proteomics platform to profile 1305 proteins of peripheral blood serum in twenty-four samples taken from 6 patients during no-rejection, nonsevere rejection, and severe rejection episodes. Also, we provide a detailed description of biosample processing and all steps to generate and analyze the SOMAscan dataset with hope it will assist in performing biomarker discovery in other transplantation centers using this platform.

Aptamer-based proteomics of serum and plasma in acquired aplastic anemia

Single-stranded oligonucleotides containing deoxyuridine are aptamers (SOMAmers) that can bind proteins with high specificity and affinity and slow dissociation rates. SOMAscan, an aptamer-based proteomic technology, allows measurement of more than 1,300 proteins simultaneously for the identification of new disease biomarkers. The aim of the present study was to identify new serum and plasma protein markers for diagnosis of acquired aplastic anemia (AA) and response to immunosuppressive therapies (IST). SOMAscan was used to screen 1,141 serum proteins in 28 AA patients before and after therapy and 1,317 plasma proteins in seven SAA patients treated with standard IST and a thrombopoietin receptor agonist. From our analysis, 19 serum and 28 plasma proteins were identified as possible candidate diagnostic and prognostic markers. A custom immunobead-based multiplex assay with five selected serum proteins (BMP-10, CCL17, DKK1, HGF, and SELL) was used for validation in a verification set (n = 65) of samples obtained before and after IST and in a blinded validation cohort at baseline (n = 16). After technical validation, four biomarkers were employed to predict diagnosis (accuracy, 88%) and long-term response to IST (accuracy, 79%). In conclusion, SOMAscan is a powerful tool for the identification of new biomarkers. We propose further larger studies to validate new candidate serum and plasma diagnostic and prognostic markers of AA.

Stability and reproducibility of proteomic profiles measured with an aptamer-based platform

The feasibility of SOMAscan, a multiplex, high sensitivity proteomics platform, for use in studies using archived plasma samples has not yet been assessed. We quantified 1,305 proteins from plasma samples donated by 16 Nurses' Health Study (NHS) participants, 40 NHSII participants, and 12 local volunteers. We assessed assay reproducibility using coefficients of variation (CV) from duplicate samples and intra-class correlation coefficients (ICC) and Spearman correlation coefficients (r) of samples processed (i.e., centrifuged and aliquoted into separate components) immediately, 24, and 48 hours after collection, as well as those of samples collected from the same individuals 1 year apart. CVs were <20% for 99% of proteins overall and <10% for 92% of proteins in heparin samples compared to 66% for EDTA samples. We observed ICC or Spearman r (comparing immediate vs. 24-hour delayed processing) ≥0.75 for 61% of proteins, with some variation by anticoagulant (56% for heparin and 70% for EDTA) and protein class (ranging from 49% among kinases to 83% among hormones). Within-person stability over 1 year was good (ICC or Spearman r ≥ 0.4) for 91% of proteins. These results demonstrate the feasibility of SOMAscan for analyses of archived plasma samples.

The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays

Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.

Impact of Preanalytical Variations in Blood-Derived Biospecimens on Omics Studies: Toward Precision Biobanking?

Research data and outcomes do vary across populations and persons, but this is not always due to experimental or true biological variation. Preanalytical components of experiments, be they biospecimen acquisition, preparation, storage, or transportation to the laboratory, may all contribute to apparent variability in research data, outcomes, and interpretation. The present review article and biobanking innovation analysis offer new insights with a summary of such preanalytical variables, for example, the type of blood collection tube, centrifugation conditions, long-term sample storage temperature, and duration, on output of omics analyses of blood-derived biospecimens: whole blood, serum, plasma, buffy coat, and peripheral blood mononuclear cells. Furthermore, we draw parallels from the field of precision medicine in this study, with a view to the future of "precision biobanking" wherein such preanalytical variations are carefully taken into consideration so as to minimize their influence on outcomes of omics data, analyses, and sensemaking, particularly in clinical omics applications. We underscore the need for using broadly framed, critical, independent, social and political science, and humanities research so as to understand the multiple possible future trajectories of, and the motivations and values embedded in, precision biobanking that is increasingly relevant in the current age of Big Data.

Clinical validation of a blood-based classifier for diagnostic evaluation of asymptomatic individuals with pulmonary nodules

BACKGROUND

The number of pulmonary nodules detected in the US is expected to increase substantially following recent recommendations for nationwide CT-based lung cancer screening. Given the low specificity of CT screening, non-invasive adjuvant methods are needed to differentiate cancerous lesions from benign nodules to help avoid unnecessary invasive procedures in the asymptomatic population. We have constructed a serum-based multi-biomarker panel and assessed its clinical accuracy in a retrospective analysis of samples collected from participants with suspicious radiographic findings in the Prostate, Lung, Chest and Ovarian (PLCO) cancer screening trial.

METHODS

Starting with a set of 9 candidate biomarkers, we identified 8 that exhibited limited pre-analytical variability with increasing clotting time, a key pre-analytical variable associated with the collection of serum. These 8 biomarkers were evaluated in a training study consisting of 95 stage I NSCLC patients and 186 smoker controls where a 5-biomarker pulmonary nodule classifier (PNC) was selected. The clinical accuracy of the PNC was determined in a blinded study of asymptomatic individuals comprising 119 confirmed malignant nodule cases and 119 benign nodule controls selected from the PLCO screening trial.

RESULTS

A PNC comprising 5 biomarkers: CEA, CYFRA 21-1, OPN, SCC, and TFPI, was selected in the training study. In an independent validation study, the PNC resolved lung cancer cases from benign nodule controls with an AUC of 0.653 (p < 0.0001). CEA and CYFRA 21-1, two of the markers included in the PNC, also accurately distinguished malignant lesions from benign controls.

CONCLUSIONS

A 5-biomarker blood test has been developed for the diagnostic evaluation of asymptomatic individuals with solitary pulmonary nodules.

Recommendations for clinical biomarker specimen preservation and stability assessments

With the wide use of biomarkers to enable critical drug-development decisions, there is a growing concern from scientific community on the need for a 'standardized process' for ensuring biomarker specimen stability and hence, a strong desire to share best practices on preserving the integrity of biomarker specimens in clinical trials and the design of studies to evaluate analyte stability. By leveraging representative industry experience, we have attempted to provide an overview of critical aspects of biomarker specimen stability commonly encountered during clinical development, including: planning of clinical sample collection procedures, clinical site training, selection of sample preservation buffers, shipping logistics, fit-for-purpose stability assessments in the analytical laboratory and presentation of case studies covering widely utilized biomarker specimen types.

A multi-component classifier for nonalcoholic fatty liver disease (NAFLD) based on genomic, proteomic, and phenomic data domains

Non-alcoholic fatty liver disease (NAFLD) represents a spectrum of conditions that include steatohepatitis and fibrosis that are thought to emanate from hepatic steatosis. Few robust biomarkers or diagnostic tests have been developed for hepatic steatosis in the setting of obesity. We have developed a multi-component classifier for hepatic steatosis comprised of phenotypic, genomic, and proteomic variables using data from 576 adults with extreme obesity who underwent bariatric surgery and intra-operative liver biopsy. Using a 443 patient training set, protein biomarker discovery was performed using the highly multiplexed SOMAscan^® proteomic assay, a set of 19 clinical variables, and the steatosis predisposing PNPLA3 rs738409 single nucleotide polymorphism genotype status. The most stable markers were selected using a stability selection algorithm with a L₁-regularized logistic regression kernel and were then fitted with logistic regression models to classify steatosis, that were then tested against a 133 sample blinded verification set. The highest area under the ROC curve (AUC) for steatosis of PNPLA3 rs738409 genotype, 8 proteins, or 19 phenotypic variables was 0.913, whereas the final classifier that included variables from all three domains had an AUC of 0.935. These data indicate that multi-domain modeling has better predictive power than comprehensive analysis of variables from a single domain.

Mesoporous silica chip: enabled peptide profiling as an effective platform for controlling bio-sample quality and optimizing handling procedure

Background

High quality clinical samples are critical for meaningful interpretation of data obtained in both basic and translational medicine. More specifically, optimized pre-analysis handling to bio-sample is crucial for avoiding biased analysis in a clinical setting. A universally applicable method for the evaluation of sample quality and pre-analysis handling is therefore in great demand.

Methods

The fingerprint pattern of low molecular weight (LMW) peptides in sera is directly associated with sample quality and handling process. Previous studies for enrichment/isolation of LMW peptides have shown that LMW peptides can be enriched by silica meso-porous material in a sensitive and high-throughput manner. Here, a peptide profile approach utilizing mesoporous silica chip-based sample preparation combined with MALDI MS analysis was used as a new platform for evaluation of bio-sample quality. Rat sera were selected as model sample and analyzed according to their LMW peptide fingerprint spectra.

Results

This novel method can complete the entire sample preparation procedure in a short period of time (<40 min), requires minimum amounts of sample (<10 µL), is of high sensitivity (LOD 10 ng/mL) as well as high reproducibility (CV% < 15%). According to the acquired LMW peptide spectra, we were able to distinguish the serum samples processed under different conditions (including different storage temperature, time, and freezing/thaw cycles) with the help of bioinformatics tools (principle composition analysis and significant difference analysis), and identify the samples that had significantly changed due to the inappropriate processing. Based on the percentage of significantly changed peaks in LMW peptide mass spectrum after handling, a judgment standard was established that can be used to evaluate the status of preservation of a biological sample. In addition, our principle study established recommendations for storage time, storage temperature and freeze/thaw conditions.

Conclusion

Our novel method for analysis of bio-samples allows for effective identification of variations in composition within samples, and provides a cost-effective tool for simple sample manipulation in a clinical setting.

Use of aptamers in immunoassays

Aptamers, short single-chain DNA or RNA oligonucleotides, react specifically with small molecules, as well as with proteins. Unlike antibodies, they may be obtained relatively easily. Aptamers are now widely employed in immunological studies and could replace antibodies in immunoassays. In this short review, methods for immobilizing aptamers on various insoluble materials (so-called apta-sorbents) are described. Recent findings on their use in the detection and isolation of immunoglobulins and their application in various immunoassays are also discussed.

Exploring phlebotomy technique as a pre-analytical factor in proteomic analyses by mass spectrometry

Multiple reaction monitoring mass spectrometry (MRM-MS) is an emerging technology for blood biomarker verification and validation; however, the results may be influenced by pre-analytical factors. This exploratory study was designed to determine if differences in phlebotomy techniques would significantly affect the abundance of plasma proteins in an upcoming biomarker development study. Blood was drawn from 10 healthy participants using four techniques: (1) a 20-gauge IV with vacutainer, (2) a 21-gauge direct vacutainer, (3) an 18-gauge butterfly with vacutainer, and (4) an 18-gauge butterfly with syringe draw. The abundances of a panel of 122 proteins (117 proteins, plus 5 matrix metalloproteinase (MMP) proteins) were targeted by LC/MRM-MS. In addition, complete blood count (CBC) data were also compared across the four techniques. Phlebotomy technique significantly affected 2 of the 11 CBC parameters (red blood cell count, p = 0.010; hemoglobin concentration, p = 0.035) and only 12 of the targeted 117 proteins (p < 0.05). Of the five MMP proteins, only MMP7 was detectable and its concentration was not significantly affected by different techniques. Overall, most proteins in this exploratory study were not significantly influenced by phlebotomy technique; however, a larger study with additional patients will be required for confirmation.

Systems vaccinology: a promise for the young and the poor

As a child, the risk of suffering and dying from infection is higher the younger you are; and higher, the less developed a region you are born in. Childhood vaccination programmes have greatly reduced mortality around the world, but least so for the very young among the very poor of the world. This appears partly owing to suboptimal vaccine effectiveness. Unfortunately, although most vaccines are administered to the newborn and very young infant (less than or equal to two months), we know the least about their host response to vaccination. We thus currently lack the knowledge to guide efforts aimed at improving vaccine effectiveness in this vulnerable population. Systems vaccinology, the study of molecular networks activated by immunization, has begun to provide unprecedented insights into mechanisms leading to vaccine-induced protection from infection or disease. However, all published reports of systems vaccinology have focused on either adults or at most children and older infants, not those most in need, i.e. newborns and very young infants. Given that the tools of systems vaccinology work perfectly well with very small sample volumes, it is time we deliver the promise that systems vaccinology holds for those most in need of vaccine-mediated protection from infection.

Phenotype-Driven Plasma Biobanking Strategies and Methods

Biobank development and integration with clinical data from electronic medical record (EMR) databases have enabled recent strides in genomic research and personalized medicine. BioVU, Vanderbilt's DNA biorepository linked to de-identified clinical EMRs, has proven fruitful in its capacity to extensively appeal to numerous areas of biomedical and clinical research, supporting the discovery of genotype-phenotype interactions. Expanding on experiences in BioVU creation and development, we have recently embarked on a parallel effort to collect plasma in addition to DNA from blood specimens leftover after routine clinical testing at Vanderbilt. This initiative offers expanded utility of BioVU by combining proteomic and metabolomic approaches with genomics and/or clinical outcomes, widening the breadth for potential research and subsequent future impact on clinical care. Here, we describe the considerations and components involved in implementing a plasma biobank program from a feasibility assessment through pilot sample collection.

New Technologies Provide Quantum Changes in the Scale, Speed, and Success of SELEX Methods and Aptamer Characterization

Single-stranded oligonucleotide aptamers have attracted great attention in the past decade because of their diagnostic and therapeutic potential. These versatile, high affinity and specificity reagents are selected by an iterative in vitro process called SELEX, Systematic Evolution of Ligands by Exponential Enrichment. Numerous SELEX methods have been developed for aptamer selections; some that are simple and straightforward, and some that are specialized and complicated. The method of SELEX is crucial for selection of an aptamer with desired properties; however, success also depends on the starting aptamer library, the target molecule, aptamer enrichment monitoring assays, and finally, the analysis and characterization of selected aptamers. Here, we summarize key recent developments in aptamer selection methods, as well as other aspects of aptamer selection that have significant impact on the outcome. We discuss potential pitfalls and limitations in the selection process with an eye to aid researchers in the choice of a proper SELEX strategy, and we highlight areas where further developments and improvements are desired. We believe carefully designed multiplexed selection methods, when complemented with high-throughput downstream analysis and characterization assays, will yield numerous high-affinity aptamers to protein and small molecule targets, and thereby generate a vast array of reagents for probing basic biological mechanisms and implementing new diagnostic and therapeutic applications in the near future.

Validation of a blood protein signature for non-small cell lung cancer

Background

CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Results

Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n = 363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n = 138 in the first validation and n = 135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.

Conclusions

Selecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.

Design and establishment of a biobank in a multicenter prospective cohort study of elderly patients with venous thromboembolism (SWITCO65+)

In the field of thrombosis and haemostasis, many preanalytical variables influence the results of coagulation assays and measures to limit potential results variations should be taken. To our knowledge, no paper describing the development and maintenance of a haemostasis biobank has been previously published. Our description of the biobank of the Swiss cohort of elderly patients with venous thromboembolism (SWITCO65+) is intended to facilitate the set-up of other biobanks in the field of thrombosis and haemostasis. SWITCO65+ is a multicentre cohort that prospectively enrolled consecutive patients aged ≥65 years with venous thromboembolism at nine Swiss hospitals from 09/2009 to 03/2012. Patients will be followed up until December 2013. The cohort includes a biobank with biological material from each participant taken at baseline and after 12 months of follow-up. Whole blood from all participants is assayed with a standard haematology panel, for which fresh samples are required. Two buffy coat vials, one PAXgene Blood RNA System tube and one EDTA-whole blood sample are also collected at baseline for RNA/DNA extraction. Blood samples are processed and vialed within 1 h of collection and transported in batches to a central laboratory where they are stored in ultra-low temperature archives. All analyses of the same type are performed in the same laboratory in batches. Using multiple core laboratories increased the speed of sample analyses and reduced storage time. After recruiting, processing and analyzing the blood of more than 1,000 patients, we determined that the adopted methods and technologies were fit-for-purpose and robust.

Genetic associations with micronutrient levels identified in immune and gastrointestinal networks

The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6–14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein–protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene–nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.

Methylation potential associated with diet, genotype, protein, and metabolite levels in the Delta Obesity Vitamin Study

Micronutrient research typically focuses on analyzing the effects of single or a few nutrients on health by analyzing a limited number of biomarkers. The observational study described here analyzed micronutrients, plasma proteins, dietary intakes, and genotype using a systems approach. Participants attended a community-based summer day program for 6-14 year old in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, eight micronutrients (vitamins A, D, E, thiamin, folic acid, riboflavin, pyridoxal, and pyridoxine) and 3 one-carbon metabolites [homocysteine (Hcy), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH)], and 1,129 plasma proteins were analyzed as a function of diet at metabolite level, plasma protein level, age, and sex. Cluster analysis identified two groups differing in SAM/SAH and differing in dietary intake patterns indicating that SAM/SAH was a potential marker of nutritional status. The approach used to analyze genetic association with the SAM/SAH metabolites is called middle-out: SNPs in 275 genes involved in the one-carbon pathway (folate, pyridoxal/pyridoxine, thiamin) or were correlated with SAM/SAH (vitamin A, E, Hcy) were analyzed instead of the entire 1M SNP data set. This procedure identified 46 SNPs in 25 genes associated with SAM/SAH demonstrating a genetic contribution to the methylation potential. Individual plasma metabolites correlated with 99 plasma proteins. Fourteen proteins correlated with body mass index, 49 with group age, and 30 with sex. The analytical strategy described here identified subgroups for targeted nutritional interventions.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

Beyond antibodies: new affinity reagents to unlock the proteome

Antibodies have been the workhorse reagents of protein capture and quantification since their 1959 debut in the RIAs developed by Yalow and Berson. However, there are technical challenges to the use of antibodies in highly multiplexed arrays aimed at measuring hundreds or even thousands of proteins at one time. We describe here a recently developed class of synthetic protein-binding reagents (slow off-rate modified aptamer). We discuss the chemical makeup and protein binding specifications of slow off-rate modified aptamer reagents, compare them to traditional aptamers and antibodies, briefly describe the novel proteomic assay that takes advantage of their unique properties, and provide several examples of their multiple applications to biomarker discovery and validation across a range of biomedical science questions.

Aptamer-based proteomic signature of intensive phase treatment response in pulmonary tuberculosis

BACKGROUND

New drug regimens of greater efficacy and shorter duration are needed for tuberculosis (TB) treatment. The identification of accurate, quantitative, non-culture based markers of treatment response would improve the efficiency of Phase 2 TB drug testing.

METHODS

In an unbiased biomarker discovery approach, we applied a highly multiplexed, aptamer-based, proteomic technology to analyze serum samples collected at baseline and after 8 weeks of treatment from 39 patients with pulmonary TB from Kampala, Uganda enrolled in a Centers for Disease Control and Prevention (CDC) TB Trials Consortium Phase 2B treatment trial.

RESULTS

We identified protein expression differences associated with 8-week culture status, including Coagulation Factor V, SAA, XPNPEP1, PSME1, IL-11 Rα, HSP70, Galectin-8, α2-Antiplasmin, ECM1, YES, IGFBP-1, CATZ, BGN, LYNB, and IL-7. Markers noted to have differential changes between responders and slow-responders included nectin-like protein 2, EphA1 (Ephrin type-A receptor 1), gp130, CNDP1, TGF-b RIII, MRC2, ADAM9, and CDON. A logistic regression model combining markers associated with 8-week culture status revealed an ROC curve with AUC = 0.96, sensitivity = 0.95 and specificity = 0.90. Additional markers showed differential changes between responders and slow-responders (nectin-like protein), or correlated with time-to-culture-conversion (KLRK1).

CONCLUSIONS

Serum proteins involved in the coagulation cascade, neutrophil activity, immunity, inflammation, and tissue remodeling were found to be associated with TB treatment response. A quantitative, non-culture based, five-marker signature predictive of 8-week culture status was identified in this pilot study.

Pre-analytical and analytical variability in absolute quantitative MRM-based plasma proteomic studies

Quantitative plasma proteomics, through the use of targeted MRM-MS and isotopically labeled standards, is emerging as a popular technique to address biological- and biomedical-centered queries. High precision and accuracy are essential in such measurements, particularly in protein biomarker research where translation to the clinic is sought. Standardized procedures and routine performance evaluation of all stages of the workflow (both pre-analytical and analytical) are therefore imperative to satisfy these requisites and enable high inter-laboratory reproducibility and transferability. In this review, we first discuss the pre-analytical and analytical variables that can affect the precision and accuracy of ‘absolute’ quantitative plasma proteomic measurements. Proposed strategies to limit such variability will then be highlighted and unmet needs for future exploration will be noted. Although there is no way to conduct a truly comprehensive review on this broad, rapidly changing topic, we have highlighted key aspects and included references to review articles on various sub-topics.

Profiling post-centrifugation delay of serum and plasma with antibody bead arrays

Several biobanking initiatives have emerged to create extensive collections of specimen for biomedical studies and various analytical platforms. An affinity proteomic analysis with antibody suspension bead arrays was conducted to investigate the influence of the pre-analytical time and temperature conditions on blood derived samples. Serum and EDTA plasma prepared from 16 individuals was centrifuged and aliquots were kept either at 4°C or in ambient temperature for 1h and up to 36h prior to first storage. Multiplexed protein profiles of post-centrifugation delay were generated in 384 biotinylated samples using 373 antibodies that targeted 343 unique proteins. Very few profiles were observed as significantly altered by the studied temperature and time intervals. Single binder and sandwich assays revealed decreasing levels of caldesmon 1 (CALD1) related to EDTA standard tubes and prolonged post-centrifugation delay of 36h. Indications from changes in CALD1 levels require further confirmation in independent material, but the current data suggests that samples should preferentially be frozen during the day of collection when to be profiled with antibody arrays selected for this study.

BIOLOGICAL SIGNIFICANCE

Affinity-based profiling of serum and plasma by microarray assays can provide unique opportunities for the discovery of biomarkers. It is though often not known how differences in sample handling after collection influence the downstream analysis. By profiling three types of blood preparations for alterations in protein profiles with respect to time and temperature post centrifugation, we addressed an important component in the analysis and of such specimen. We believe that this analysis adds valuable information to be considered when biobanking blood derived samples. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics.

Elucidating novel serum biomarkers associated with pulmonary tuberculosis treatment

In an unbiased approach to biomarker discovery, we applied a highly multiplexed proteomic technology (SOMAscan, SomaLogic, Inc, Boulder, CO) to understand changes in proteins from paired serum samples at enrollment and after 8 weeks of TB treatment from 39 patients with pulmonary TB from Kampala, Uganda enrolled in the Center for Disease Control and Prevention's Tuberculosis Trials Consortium (TBTC) Study 29. This work represents the first large-scale proteomic analysis employing modified DNA aptamers in a study of active tuberculosis (TB). We identified multiple proteins that exhibit significant expression differences during the intensive phase of TB therapy. There was enrichment for proteins in conserved networks of biological processes and function including antimicrobial defense, tissue healing and remodeling, acute phase response, pattern recognition, protease/anti-proteases, complement and coagulation cascade, apoptosis, immunity and inflammation pathways. Members of cytokine pathways such as interferon-gamma, while present, were not as highly represented as might have been predicted. The top proteins that changed between baseline and 8 weeks of therapy were TSP4, TIMP-2, SEPR, MRC-2, Antithrombin III, SAA, CRP, NPS-PLA2, LEAP-1, and LBP. The novel proteins elucidated in this work may provide new insights for understanding TB disease, its treatment and subsequent healing processes that occur in response to effective therapy.

Taking measure of personalized medicine: the proteome

Good medicine begins, by and large, with measurements. For medicine to become truly personalized, it is critical that the right measurements are made and interpreted. Although genomics holds great promise for deepening our understanding of biology, we believe that a perhaps more critical and transformative measurement for medicine is proteomics, which has lagged behind genomics for largely technological reasons. Proteins uniquely provide a real-time, clinically relevant measure of individual patients. We describe here an entirely new proteomics technology that makes the measure of proteins from biological samples as straightforward as measuring genes, and list some of the applications that have already been performed.

Early detection of malignant pleural mesothelioma in asbestos-exposed individuals with a noninvasive proteomics-based surveillance tool

BACKGROUND

Malignant pleural mesothelioma (MM) is an aggressive, asbestos-related pulmonary cancer that is increasing in incidence. Because diagnosis is difficult and the disease is relatively rare, most patients present at a clinically advanced stage where possibility of cure is minimal. To improve surveillance and detection of MM in the high-risk population, we completed a series of clinical studies to develop a noninvasive test for early detection.

METHODOLOGY/PRINCIPAL FINDINGS

We conducted multi-center case-control studies in serum from 117 MM cases and 142 asbestos-exposed control individuals. Biomarker discovery, verification, and validation were performed using SOMAmer proteomic technology, which simultaneously measures over 1000 proteins in unfractionated biologic samples. Using univariate and multivariate approaches we discovered 64 candidate protein biomarkers and derived a 13-marker random forest classifier with an AUC of 0.99±0.01 in training, 0.98±0.04 in independent blinded verification and 0.95±0.04 in blinded validation studies. Sensitivity and specificity at our pre-specified decision threshold were 97%/92% in training and 90%/95% in blinded verification. This classifier accuracy was maintained in a second blinded validation set with a sensitivity/specificity of 90%/89% and combined accuracy of 92%. Sensitivity correlated with pathologic stage; 77% of Stage I, 93% of Stage II, 96% of Stage III and 96% of Stage IV cases were detected. An alternative decision threshold in the validation study yielding 98% specificity would still detect 60% of MM cases. In a paired sample set the classifier AUC of 0.99 and 91%/94% sensitivity/specificity was superior to that of mesothelin with an AUC of 0.82 and 66%/88% sensitivity/specificity. The candidate biomarker panel consists of both inflammatory and proliferative proteins, processes strongly associated with asbestos-induced malignancy.

SIGNIFICANCE

The SOMAmer biomarker panel discovered and validated in these studies provides a solid foundation for surveillance and diagnosis of MM in those at highest risk for this disease.

Life's simple measures: unlocking the proteome

Using modified nucleotides and selecting for slow off-rates in the SELEX procedure, we have evolved a special class of aptamers, called SOMAmers (slow off-rate modified aptamers), which bind tightly and specifically to proteins in body fluids. We use these in a novel assay that yields 1:1 complexes of the SOMAmers with their cognate proteins in body fluids. Measuring the SOMAmer concentrations of the resultant complexes reflects the concentration of the proteins in the fluids. This is simply done by hybridization to complementary sequences on solid supports, but it can also be done by any other DNA quantification technology (including NexGen sequencing). We use measurements of over 1000 proteins in under 100 μL of serum or plasma to answer important medical questions, two of which are reviewed here. A number of bioinformatics methods have guided our discoveries, including principal component analysis. We use various methods to evaluate sample handling procedures in our clinical samples and can identify many parameters that corrupt proteomics analysis.

Aptamers and the RNA world, past and present

Aptamers and the SELEX process were discovered over two decades ago. These discoveries have spawned a productive academic and commercial industry. The collective results provide insights into biology, past and present, through an in vitro evolutionary exploration of the nature of nucleic acids and their potential roles in ancient life. Aptamers have helped usher in an RNA renaissance. Here we explore some of the evolution of the aptamer field and the insights it has provided for conceptualizing an RNA world, from its nascence to our current endeavor employing aptamers in human proteomics to discover biomarkers of health and disease.

Translational research in pediatrics: tissue sampling and biobanking

Translational research is expanding and has become a focus of National Research funding agencies, touted as the primary avenue to improve health care practice. The use of human tissues for research on disease etiology is a pillar of translational research, particularly with innovations in research technologies to investigate the building blocks of disease. In pediatrics, translational research using human tissues has been hindered by the many practical and ethical considerations associated with tissue procurement from children and also by a limited population base for study, by the increasing complexities in conducting clinical research, and by a lack of dedicated child-health research funding. Given these obstacles, pediatric translational research can be enhanced by developing strategic and efficient biobanks that will provide scientists with quality tissue specimens to render accurate and reproducible research results. Indeed, tissue sampling and biobanking within pediatric academic settings has potential to impact child health by promoting bidirectional interaction between clinicians and scientists, helping to maximize research productivity, and providing a competitive edge for attracting and maintaining high-quality personnel. The authors of this review outline key issues and practical solutions to optimize pediatric tissue sampling and biobanking for translational research, activities that will ultimately reduce the burden of childhood disease.

Advances in human proteomics at high scale with the SOMAscan proteomics platform

In 1997, while still working at NeXstar Pharmaceuticals, several of us made a proteomic bet. We thought then, and continue to think, that proteomics offers a chance to identify disease-specific biomarkers and improve healthcare. However, interrogating proteins turned out to be a much harder problem than interrogating nucleic acids. Consequently, the 'omics' revolution has been fueled largely by genomics. High-scale proteomics promises to transform medicine with personalized diagnostics, prevention, and treatment. We have now reached into the human proteome to quantify more than 1000 proteins in any human matrix - serum, plasma, CSF, BAL, and also tissue extracts - with our new SOMAmer-based proteomics platform. The surprising and pleasant news is that we have made unbiased protein biomarker discovery a routine and fast exercise. The downstream implications of the platform are substantial.

Genotypic characterization of non-O157 Shiga toxin-producing Escherichia coli in beef abattoirs of Argentina

The non-O157 Shiga toxin-producing Escherichia coli (STEC) contamination in carcasses and feces of 811 bovines in nine beef abattoirs from Argentina was analyzed during a period of 17 months. The feces of 181 (22.3%) bovines were positive for non-O157 STEC, while 73 (9.0%) of the carcasses showed non-O157 STEC contamination. Non-O157 STEC strains isolated from feces (227) and carcasses (80) were characterized. The main serotypes identified were O178:H19, O8:H19, O130:H11, and O113:H21, all of which have produced sporadic cases of hemolytic-uremic syndrome in Argentina and worldwide. Twenty-two (7.2%) strains carried a fully virulent stx/eae/ehxA genotype. Among them, strains of serotypes O103:[H2], O145:NM, and O111:NM represented 4.8% of the isolates. Xba I pulsed-field gel electrophoresis pattern analysis showed 234 different patterns, with 76 strains grouped in 30 clusters. Nine of the clusters grouped strains isolated from feces and from carcasses of the same or different bovines in a lot, while three clusters were comprised of strains distributed in more than one abattoir. Patterns AREXSX01.0157, AREXBX01.0015, and AREXPX01.0013 were identified as 100% compatible with the patterns of one strain isolated from a hemolytic-uremic syndrome case and two strains previously isolated from beef medallions, included in the Argentine PulseNet Database. In this survey, 4.8% (39 of 811) of the bovine carcasses appeared to be contaminated with nonO157 STEC strains potentially capable of producing sporadic human disease, and a lower proportion (0.25%) with strains able to produce outbreaks of severe disease.

High-content affinity-based proteomics: unlocking protein biomarker discovery

Single protein biomarkers measured with antibody-based affinity assays are the basis of molecular diagnostics in clinical practice today. There is great hope in discovering new protein biomarkers and combinations of protein biomarkers for advancing medicine through monitoring health, diagnosing disease, guiding treatment, and developing new therapeutics. The goal of high-content proteomics is to unlock protein biomarker discovery by measuring many (thousands) or all (∼23,000) proteins in the human proteome in an unbiased, data-driven approach. High-content proteomics has proven technically difficult due to the diversity of proteins, the complexity of relevant biological samples, such as blood and tissue, and large concentration ranges (in the order of 10(12) in blood). Mass spectrometry and affinity methods based on antibodies have dominated approaches to high-content proteomics. For technical reasons, neither has achieved adequate simultaneous performance and high-content. Here we review antibody-based protein measurement, multiplexed antibody-based protein measurement, and limitations of antibodies for high-content proteomics due to their inherent cross-reactivity. Finally, we review a new affinity-based proteomic technology developed from the ground up to solve the problem of high content with high sensitivity and specificity. Based on a new generation of slow off-rate modified aptamers (SOMAmers), this technology is unlocking biomarker discovery.

Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead

Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.

Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer

Background

Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease.

Methodology/Principal Findings

We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES) that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC.

Conclusions/Significance

This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels. Separate verification of classifier performance provides evidence against over-fitting and is encouraging for the next development phase, independent validation. This careful study provides a solid foundation to develop tests sorely needed to identify early stage lung cancer.

Escherichia coli O157:H7: animal reservoir and sources of human infection

This review surveys the literature on carriage and transmission of enterohemorrhagic Escherichia coli (EHEC) O157:H7 in the context of virulence factors and sampling/culture technique. EHEC of the O157:H7 serotype are worldwide zoonotic pathogens responsible for the majority of severe cases of human EHEC disease. EHEC O157:H7 strains are carried primarily by healthy cattle and other ruminants, but most of the bovine strains are not transmitted to people, and do not exhibit virulence factors associated with human disease. Prevalence of EHEC O157:H7 is probably underestimated. Carriage of EHEC O157:H7 by individual animals is typically short-lived, but pen and farm prevalence of specific isolates may extend for months or years and some carriers, designated as supershedders, may harbor high intestinal numbers of the pathogen for extended periods. The prevalence of EHEC O157:H7 in cattle peaks in the summer and is higher in postweaned calves and heifers than in younger and older animals. Virulent strains of EHEC O157:H7 are rarely harbored by pigs or chickens, but are found in turkeys. The bacteria rarely occur in wildlife with the exception of deer and are only sporadically carried by domestic animals and synanthropic rodents and birds. EHEC O157:H7 occur in amphibian, fish, and invertebrate carriers, and can colonize plant surfaces and tissues via attachment mechanisms different from those mediating intestinal attachment. Strains of EHEC O157:H7 exhibit high genetic variability but typically a small number of genetic types predominate in groups of cattle and a farm environment. Transmission to people occurs primarily via ingestion of inadequately processed contaminated food or water and less frequently through contact with manure, animals, or infected people.