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Dive into the research topics where Paul A. Rudnick is active.

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Featured researches published by Paul A. Rudnick.


Nature Biotechnology | 2009

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Terri Addona; Susan E. Abbatiello; Birgit Schilling; Steven J. Skates; D. R. Mani; David M. Bunk; Clifford H. Spiegelman; Lisa J. Zimmerman; Amy-Joan L. Ham; Hasmik Keshishian; Steven C. Hall; Simon Allen; Ronald K. Blackman; Christoph H. Borchers; Charles Buck; Michael P. Cusack; Nathan G. Dodder; Bradford W. Gibson; Jason M. Held; Tara Hiltke; Angela M. Jackson; Eric B. Johansen; Christopher R. Kinsinger; Jing Li; Mehdi Mesri; Thomas A. Neubert; Richard K. Niles; Trenton Pulsipher; David F. Ransohoff; Henry Rodriguez

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low μg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.


Nature | 2014

Proteogenomic characterization of human colon and rectal cancer

Bing Zhang; Jing Wang; Xiaojing Wang; Jing Zhu; Qi Liu; Zhiao Shi; Matthew C. Chambers; Lisa J. Zimmerman; Kent Shaddox; Sangtae Kim; Sherri R. Davies; Sean Wang; Pei Wang; Christopher R. Kinsinger; Robert Rivers; Henry Rodriguez; R. Reid Townsend; Matthew J. Ellis; Steven A. Carr; David L. Tabb; Robert J. Coffey; Robbert J. C. Slebos; Daniel C. Liebler; Michael A. Gillette; Karl R. Klauser; Eric Kuhn; D. R. Mani; Philipp Mertins; Karen A. Ketchum; Amanda G. Paulovich

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.


Journal of Proteome Research | 2010

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography−Tandem Mass Spectrometry

David L. Tabb; Lorenzo Vega-Montoto; Paul A. Rudnick; Asokan Mulayath Variyath; Amy-Joan L. Ham; David M. Bunk; Lisa E. Kilpatrick; Dean Billheimer; Ronald K. Blackman; Steven A. Carr; Karl R. Clauser; Jacob D. Jaffe; Kevin A. Kowalski; Thomas A. Neubert; Fred E. Regnier; Birgit Schilling; Tony Tegeler; Mu Wang; Pei Wang; Jeffrey R. Whiteaker; Lisa J. Zimmerman; Susan J. Fisher; Bradford W. Gibson; Christopher R. Kinsinger; Mehdi Mesri; Henry Rodriguez; Stephen E. Stein; Paul Tempst; Amanda G. Paulovich; Daniel C. Liebler

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.


Journal of Proteome Research | 2010

Depletion of Abundant Plasma Proteins and Limitations of Plasma Proteomics

Chengjian Tu; Paul A. Rudnick; Misti Y. Martinez; Kristin L. Cheek; Stephen E. Stein; Robbert J. C. Slebos; Daniel C. Liebler

Immunoaffinity depletion with antibodies to the top 7 or top 14 high-abundance plasma proteins is used to enhance detection of lower abundance proteins in both shotgun and targeted proteomic analyses. We evaluated the effects of top 7/top 14 immunodepletion on the shotgun proteomic analysis of human plasma. Our goal was to evaluate the impact of immunodepletion on detection of proteins across detectable ranges of abundance. The depletion columns afforded highly repeatable and efficient plasma protein fractionation. Relatively few nontargeted proteins were captured by the depletion columns. Analyses of unfractionated and immunodepleted plasma by peptide isoelectric focusing (IEF), followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), demonstrated enrichment of nontargeted plasma proteins by an average of 4-fold, as assessed by MS/MS spectral counting. Either top 7 or top 14 immunodepletion resulted in a 25% increase in identified proteins compared to unfractionated plasma. Although 23 low-abundance (<10 ng mL(-1)) plasma proteins were detected, they accounted for only 5-6% of total protein identifications in immunodepleted plasma. In both unfractionated and immunodepleted plasma, the 50 most abundant plasma proteins accounted for 90% of cumulative spectral counts and precursor ion intensities, leaving little capacity to sample lower abundance proteins. Untargeted proteomic analyses using current LC-MS/MS platforms-even with immunodepletion-cannot be expected to efficiently discover low-abundance, disease-specific biomarkers in plasma.


Cell | 2016

Integrated proteogenomic characterization of human high-grade serous ovarian cancer

Hui Zhang; Tao Liu; Zhen Zhang; Samuel H. Payne; Bai Zhang; Jason E. McDermott; Jian-Ying Zhou; Vladislav A. Petyuk; Li Chen; Debjit Ray; Shisheng Sun; Feng Yang; Lijun Chen; Jing Wang; Punit Shah; Seong Won Cha; Paul Aiyetan; Sunghee Woo; Yuan Tian; Marina A. Gritsenko; Therese R. Clauss; Caitlin H. Choi; Matthew E. Monroe; Stefani N. Thomas; Song Nie; Chaochao Wu; Ronald J. Moore; Kun-Hsing Yu; David L. Tabb; David Fenyö

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.


Molecular & Cellular Proteomics | 2010

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses

Paul A. Rudnick; Karl R. Clauser; Lisa E. Kilpatrick; Dmitrii V. Tchekhovskoi; P. Neta; Nikša Blonder; Dean Billheimer; Ronald K. Blackman; David M. Bunk; Amy-Joan L. Ham; Jacob D. Jaffe; Christopher R. Kinsinger; Mehdi Mesri; Thomas A. Neubert; Birgit Schilling; David L. Tabb; Tony Tegeler; Lorenzo Vega-Montoto; Asokan Mulayath Variyath; Mu Wang; Pei Wang; Jeffrey R. Whiteaker; Lisa J. Zimmerman; Steven A. Carr; Susan J. Fisher; Bradford W. Gibson; Amanda G. Paulovich; Fred E. Regnier; Henry Rodriguez; Cliff Spiegelman

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.


Molecular & Cellular Proteomics | 2010

Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance

Amanda G. Paulovich; Dean Billheimer; Amy-Joan L. Ham; Lorenzo Vega-Montoto; Paul A. Rudnick; David L. Tabb; Pei Wang; Ronald K. Blackman; David M. Bunk; Karl R. Clauser; Christopher R. Kinsinger; Birgit Schilling; Tony Tegeler; Asokan Mulayath Variyath; Mu Wang; Jeffrey R. Whiteaker; Lisa J. Zimmerman; David Fenyö; Steven A. Carr; Susan J. Fisher; Bradford W. Gibson; Mehdi Mesri; Thomas A. Neubert; Fred E. Regnier; Henry Rodriguez; Cliff Spiegelman; Stephen E. Stein; Paul Tempst; Daniel C. Liebler

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize preanalytical and analytical variation in comparative proteomics experiments.


Journal of Histochemistry and Cytochemistry | 2007

Proteome Analysis of Microdissected Formalin-fixed and Paraffin-embedded Tissue Specimens:

Tong Guo; Weijie Wang; Paul A. Rudnick; Tao Song; Jie Li; Zhengping Zhuang; Robert J. Weil; Don L. DeVoe; Cheng S. Lee; Brian M. Balgley

Targeted proteomics research, based on the enrichment of disease-relevant proteins from isolated cell populations selected from high-quality tissue specimens, offers great potential for the identification of diagnostic, prognostic, and predictive biological markers for use in the clinical setting and during preclinical testing and clinical trials, as well as for the discovery and validation of new protein drug targets. Formalin-fixed and paraffin-embedded (FFPE) tissue collections, with attached clinical and outcome information, are invaluable resources for conducting retrospective protein biomarker investigations and performing translational studies of cancer and other diseases. Combined capillary isoelectric focusing/nano-reversed-phase liquid chromatography separations equipped with nano-electrospray ionization-tandem mass spectrometry are employed for the studies of proteins extracted from microdissected FFPE glioblastoma tissues using a heat-induced antigen retrieval (AR) technique. A total of 14,478 distinct peptides are identified, leading to the identification of 2733 non-redundant SwissProt protein entries. Eighty-three percent of identified FFPE tissue proteins overlap with those obtained from the pellet fraction of fresh-frozen tissue of the same patient. This large degree of protein overlapping is attributed to the application of detergent-based protein extraction in both the cell pellet preparation protocol and the AR technique.


Molecular & Cellular Proteomics | 2015

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma

Susan E. Abbatiello; Birgit Schilling; D. R. Mani; Lisa J. Zimmerman; Steven C. Hall; Brendan MacLean; Matthew E. Albertolle; Simon Allen; Michael Burgess; Michael P. Cusack; Mousumi Gosh; Victoria Hedrick; Jason M. Held; H. Dorota Inerowicz; Angela M. Jackson; Hasmik Keshishian; Christopher R. Kinsinger; John S. Lyssand; Lee Makowski; Mehdi Mesri; Henry Rodriguez; Paul A. Rudnick; Pawel Sadowski; Nell Sedransk; Kent Shaddox; Stephen J. Skates; Eric Kuhn; Derek Smith; Jeffery R. Whiteaker; Corbin A. Whitwell

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.


Molecular & Cellular Proteomics | 2013

Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS)

Susan E. Abbatiello; D. R. Mani; Birgit Schilling; Brendan MacLean; Lisa J. Zimmerman; Xingdong Feng; Michael P. Cusack; Nell Sedransk; Steven C. Hall; Terri Addona; Simon Allen; Nathan G. Dodder; Mousumi Ghosh; Jason M. Held; Victoria Hedrick; H. Dorota Inerowicz; Angela M. Jackson; Hasmik Keshishian; Jong Won Kim; John S. Lyssand; C. Paige Riley; Paul A. Rudnick; Pawel Sadowski; Kent Shaddox; Derek Smith; Daniela M. Tomazela; Åsa Wahlander; Sofia Waldemarson; Corbin A. Whitwell; Jinsam You

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

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Birgit Schilling

Buck Institute for Research on Aging

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Henry Rodriguez

National Institutes of Health

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Stephen E. Stein

National Institute of Standards and Technology

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Mehdi Mesri

National Institutes of Health

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D. R. Mani

Massachusetts Institute of Technology

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David M. Bunk

National Institute of Standards and Technology

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Jason M. Held

Washington University in St. Louis

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