Cells employ error-free or error-prone postreplication repair (PRR) processes to tolerate DNA damage. Here, we present a genome-wide screen for sensitivity to 0.001% methyl methanesulfonate (MMS). This relatively low dose is of particular interest because wild-type cells exhibit no discernible phenotypes in response to treatment, yet PRR mutants are unique among repair mutants in their exquisite sensitivity to 0.001% MMS; thus, low-dose MMS treatment provides a distinctive opportunity to study postreplication repair processes. We show that upon exposure to low-dose MMS, a PRR-defective rad18Δ mutant stalls into a lengthy G2 arrest associated with the accumulation of single-stranded DNA (ssDNA) gaps. Consistent with previous results following UV-induced damage, reactivation of Rad18, even after prolonged G2 arrest, restores viability and genome integrity. We further show that PRR pathway preference in 0.001% MMS depends on timing and context; cells preferentially employ the error-free pathway in S phase and do not require MEC1-dependent checkpoint activation for survival. However, when PRR is restricted to the G2 phase, cells utilize REV3-dependent translesion synthesis, which requires a MEC1-dependent delay and results in significant hypermutability.
Access to a wider range of quantitative protein assays would significantly impact the number and use of tissue markers in guiding disease treatment. Quantitative mass spectrometry-based peptide and protein assays, such as immuno-SRM assays, have seen tremendous growth in recent years in application to protein quantification in biological fluids such as plasma or urine. Here, we extend the capability of the technique by demonstrating the application of a multiplexed immuno-SRM assay for quantification of estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) levels in cell line lysates and human surgical specimens. The performance of the assay was characterized using peptide response curves, with linear ranges covering approximately 4 orders of magnitude and limits of detection in the low fmol/mg lysate range. Reproducibility was acceptable with median coefficients of variation of approximately 10%. We applied the assay to measurements of ER and HER2 in well-characterized cell line lysates with good discernment based on ER/HER2 status. Finally, the proteins were measured in surgically resected breast cancers, and the results showed good correlation with ER/HER2 status determined by clinical assays. This is the first implementation of the peptide-based immuno-SRM assay technology in cell lysates and human surgical specimens.
Estrogen receptor; HER2/Neu; immunoaffinity; peptides; tissue
The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) is applying latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biological insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods.
Gene Expression; Cancer Proteomics; Protein Phosphorylation; Mass Spectrometry; Cancer Genome Atlas
The successful application of MRM in biological specimens raises the exciting possibility that assays can be configured to measure all human proteins, resulting in an assay resource that would promote advances in biomedical research. We report the results of a pilot study designed to test the feasibility of a large-scale, international effort in MRM assay generation. We have configured, validated across three laboratories, and made publicly available as a resource to the community 645 novel MRM assays representing 319 proteins expressed in human breast cancer. Assays were multiplexed in groups of >150 peptides and deployed to quantify endogenous analyte in a panel of breast cancer-related cell lines. Median assay precision was 5.4%, with high inter-laboratory correlation (R2 >0.96). Peptide measurements in breast cancer cell lines were able to discriminate amongst molecular subtypes and identify genome-driven changes in the cancer proteome. These results establish the feasibility of a scaled, international effort.
We generated extensive transcriptional and proteomic profiles from a Her2-driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens.
Twelve datasets are available, encompassing 841 LC-MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias.
In total, 18,880 unique peptides were identified (PeptideProphet peptide error rate ≤1%), with 3884 and 1659 non-redundant protein groups identified in plasma and tissue datasets, respectively. Sixty-one of these protein groups overlapped between cancer plasma and cancer tissue.
Conclusions and clinical relevance
These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for MRM-MS. The availability of these datasets will contribute positively to clinical proteomics.
Breast cancer; Her2; mouse; proteome; transcriptome
There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in quantitation, are associated with a high cost, long lead time, and are fraught with drawbacks (e.g. heterophilic antibodies, autoantibody interference, 'hook-effect').1 An alternative technique is affinity enrichment of peptides coupled with quantitative mass spectrometry, commonly referred to as SISCAPA (Stable Isotope Standards and Capture by Anti-Peptide Antibodies).2 In this technique, affinity enrichment of peptides with stable isotope dilution and detection by selected/multiple reaction monitoring mass spectrometry (SRM/MRM-MS) provides quantitative measurement of peptides as surrogates for their respective proteins. SRM/MRM-MS is well established for accurate quantitation of small molecules 3, 4 and more recently has been adapted to measure the concentrations of proteins in plasma and cell lysates.5-7 To achieve quantitation of proteins, these larger molecules are digested to component peptides using an enzyme such as trypsin. One or more selected peptides whose sequence is unique to the target protein in that species (i.e. "proteotypic" peptides) are then enriched from the sample using anti-peptide antibodies and measured as quantitative stoichiometric surrogates for protein concentration in the sample. Hence, coupled to stable isotope dilution (SID) methods (i.e. a spiked-in stable isotope labeled peptide standard), SRM/MRM can be used to measure concentrations of proteotypic peptides as surrogates for quantification of proteins in complex biological matrices. The assays have several advantages compared to traditional immunoassays. The reagents are relatively less expensive to generate, the specificity for the analyte is excellent, the assays can be highly multiplexed, enrichment can be performed from neat plasma (no depletion required), and the technique is amenable to a wide array of proteins or modifications of interest.8-13 In this video we demonstrate the basic protocol as adapted to a magnetic bead platform.
In Saccharomyces cerevisiae, a DNA damage checkpoint in the S phase is responsible for delaying DNA replication in response to genotoxic stress. This pathway is partially regulated by the checkpoint proteins Rad9, Rad17 and Rad24. Here, we describe a novel hypermutable phenotype for rad9Δ, rad17Δ and rad24Δ cells in response to a chronic 0.01% dose of the DNA alkylating agent MMS. We report that this hypermutability results from DNA damage introduction during the S phase and is dependent on a functional translesion synthesis pathway. In addition, we performed a genetic screen for interactions with rad9Δ that confer sensitivity to 0.01% MMS. We report and quantify 25 genetic interactions with rad9Δ, many of which involve the post-replication repair machinery. From these data, we conclude that defects in S phase checkpoint regulation lead to increased reliance on mutagenic translesion synthesis, and we describe a novel role for members of the S-phase DNA damage checkpoint in suppressing mutagenic post-replicative repair in response to sublethal MMS treatment.
Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) utilizes antibodies to enrich peptides from complex matrices for quantitation by stable isotope dilution mass spectrometry. SISCAPA improves sensitivity and limits the sample handling required for plasma-based analysis. Thus far, SISCAPA assays have been performed using polyclonal antibodies, yet monoclonal antibodies are an attractive alternative since they provide exquisite specificity, a renewable resource, and the potential for isolation of clones with very high affinities (10-9 M or better). The selection of a good monoclonal antibody out of hundreds-to-thousands of clones presents a challenge, since the screening assay should ideally be in the format of the final SISCAPA assay, but performing the assays manually is labor- and time-intensive. In this manuscript, we demonstrate that monoclonal antibodies can be used in SISCAPA assays, and we describe an automated high-throughput SISCAPA method that makes screening of large numbers of hybridomas feasible while conserving time and resources.
SISCAPA; anti-peptide antibody; monoclonal antibody screening; selected reaction monitoring-mass spectrometry; automation; ELISA
The application of “omics” technologies to biological samples generates hundreds to thousands of biomarker candidates; however, a discouragingly small number make it through the pipeline to clinical use. This is in large part due to the incredible mismatch between the large numbers of biomarker candidates and the paucity of reliable assays and methods for validation studies. We desperately need a pipeline that relieves this bottleneck between biomarker discovery and validation. This paper reviews the requirements for technologies to adequately credential biomarker candidates for costly clinical validation and proposes methods and systems to verify biomarker candidates. Models involving pooling of clinical samples, where appropriate, are discussed. We conclude that current proteomic technologies are on the cusp of significantly affecting translation of molecular diagnostics into the clinic.
Biomarker verification; Multiple reaction monitoring; Targeted proteomics
Although the field of mass spectrometry-based proteomics is still in its infancy, recent developments in targeted proteomic techniques have left the field poised to impact the clinical protein biomarker pipeline now more than at any other time in history. For proteomics to meet its potential for finding biomarkers, clinicians, statisticians, epidemiologists and chemists must work together in an interdisciplinary approach. These interdisciplinary efforts will have the greatest chance for success if participants from each discipline have a basic working knowledge of the other disciplines. To that end, the purpose of this review is to provide a nontechnical overview of the emerging/evolving roles that mass spectrometry (especially targeted modes of mass spectrometry) can play in the biomarker pipeline, in hope of making the technology more accessible to the broader community for biomarker discovery efforts. Additionally, the technologies discussed are broadly applicable to proteomic studies, and are not restricted to biomarker discovery.
targeted proteomics; multiple reaction monitoring; selected reaction monitoring; biomarker; mass spectrometry
Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do not contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments and the experimental evidence needed to establish that the assays they develop work as intended and are achieving the required levels of performance. Using this “fit-for-purpose” approach, the group defined three tiers of assays distinguished by their performance and extent of analytical characterization. Computational and statistical tools useful for the analysis of targeted MS results were described. Participants also detailed the information that authors need to provide in their manuscripts to enable reviewers and readers to clearly understand what procedures were performed and to evaluate the reliability of the peptide or protein quantification measurements reported. This paper presents a summary of the meeting and recommendations.
Quantitative protein assays are needed in a wide range of biological studies. Traditional immunoassays are not available for a large number of proteins and development of new immunoassays requires a significant investment in time and money. The development of assays using peptide immunoaffinity enrichment coupled with targeted mass spectrometry has many advantages including versatility in design, ease of use, enhanced specificity, and good performance characteristics. This review presents recent developments in the characterization and implementation of immuno-SRM assays.
quantitative proteomics; selected reaction monitoring; stable isotope dilution; SISCAPA; immuno-SRM; immuno-mass spectrometry
The structural maintenance of chromosome 1 (Smc1) protein is a member of the highly conserved cohesin complex and is involved in sister chromatid cohesion. In response to ionizing radiation, Smc1 is phosphorylated at two sites, Ser-957 and Ser-966, and these phosphorylation events are dependent on the ATM protein kinase. In this study, we describe the generation of two novel ELISAs for quantifying phospho-Smc1Ser-957 and phospho-Smc1Ser-966. Using these novel assays, we quantify the kinetic and biodosimetric responses of human cells of hematological origin, including immortalized cells, as well as both quiescent and cycling primary human PBMC. Additionally, we demonstrate a robust in vivo response for phospho-Smc1Ser-957 and phospho-Smc1Ser-966 in lymphocytes of human patients after therapeutic exposure to ionizing radiation, including total-body irradiation, partial-body irradiation, and internal exposure to 131I. These assays are useful for quantifying the DNA damage response in experimental systems and potentially for the identification of individuals exposed to radiation after a radiological incident.
High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.
Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool (http://proteome.gs.washington.edu/software/skyline).
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.
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.
Activation of the DNA damage response pathway is a hallmark for early tumorigenesis, while loss of pathway activity is associated with disease progression. Thus we hypothesized that a gene expression signature associated with the DNA damage response may serve as a prognostic signature for outcome in cancer patients. We identified ionizing radiation-responsive transcripts in human lymphoblast cells derived from 12 individuals and used this signature to screen a panel of cancer data sets for the ability to predict long-term survival of cancer patients. We demonstrate that gene sets induced or repressed by ionizing radiation can predict clinical outcome in two independent breast cancer data sets, and we compare the radiation signature to previously described gene expression-based outcome predictors. While genes repressed in response to radiation likely represent the well-characterized proliferation signature predictive of breast cancer outcome, genes induced by radiation likely encode additional information representing other deregulated biological properties of tumors such as checkpoint or apoptotic responses.
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.
In an effort to identify proteomic changes that may be useful for radiation biodosimetry, human cells of hematological origin were treated with ionizing radiation or mock-irradiated and then harvested at different times after treatment. Protein lysates were generated from these cells and evaluated by Western blotting using a panel of 301 commercially available antibodies targeting 161 unique proteins. From this screen, we identified 55 ionizing radiation-responsive proteins, including 14 proteins not previously reported to be radiation-responsive at the protein level. The data from this large-scale screen have been assembled into a public website (http://labs.fhcrc.org/paulovich/biodose_index.html) that may be of value to the radiation community both as a source of putative biomarkers for biodosimetry and also as a source of validation data on commercially available antibodies that detect radiation-responsive proteins. Using a panel of candidate radiation biomarkers in human cell lines, we demonstrate the feasibility of assembling a complementary panel of radiation-responsive proteins. Furthermore, we demonstrate the feasibility of using blood cell-based proteomic changes for biodosimetry by demonstrating detection of protein changes in circulating cells after total-body irradiation in a canine model.