Multiplexed MRM‐based quantitation of candidate cancer biomarker proteins in undepleted and non‐enriched human plasma

An emerging approach for multiplexed targeted proteomics involves bottom‐up LC‐MRM‐MS, with stable isotope‐labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer‐biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM‐based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom‐up workflow) for the 27 biomarker proteins (represented by 57 interference‐free peptides). The linear dynamic range for the MRM assays spanned four orders‐of‐magnitude, with 25 assays covering a 10³–10⁴ range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin‐like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer‐associated protein biomarker panels in human plasma, prior to clinical use.     

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.     

Clinical translation of MS-based,quantitative plasma proteomics: status,challenges, requirements,and potential

Introduction: Aided by the advent of advanced mass spectrometry (MS)-based technologies and methodologies, quantitative proteomics has emerged as a viable technique to capture meaningful data for candidate biomarker evaluation. To aid clinical translation, these methods generally utilize a bottom-up strategy with isotopically labeled standards and a targeted form of MS measurement.

Areas covered: This article reviews the status, challenges, requirements, and potential of translating current, MS-based methods to the clinical laboratory. The described methods are discussed and contrasted within a fit-for-purpose approach, while different resources for quality control, quantitative analysis, and data interpretation are additionally provided.

Expert commentary: Although great strides have been made over the past five years in developing reliable quantitative assays for plasma protein biomarkers, it is crucial for investigators to have an understanding of the clinical validation process, a major roadblock in translational research. Continued progress in method design and validation of protein assays is necessary to ultimately achieve widespread adoption and regulatory approval.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

Phospholipid capture combined with non-linear chromatographic correction for improved serum metabolite profiling

Serum analysis with LC/MS can yield thousands of potential metabolites. However, in metabolomics, biomarkers of interest will often be of low abundance, and ionization suppression from high abundance endogenous metabolites such as phospholipids may prevent the detection of these metabolites. Here a cerium-modified column and methyl-tert-butyl-ether (MTBE) liquid–liquid extraction were employed to remove phospholipids from serum in order to obtain a more comprehensive metabolite profile. XCMS, an in-house developed data analysis software platform, showed that the intensity of existing endogenous metabolites increased, and that new metabolites were observed. This application of phospholipid capture in combination with XCMS non-linear data processing has enormous potential in metabolite profiling, for biomarker detection and quantitation.     

Mass spectrometry analysis of glycoprotein biomarkers in human blood of hepatocellular carcinoma

Introduction: Diagnosis of hepatocellular carcinoma (HCC) is important for improving the survival rate and selecting the optimum therapeutic option. However, some patients with HCC are not diagnosed until after symptoms appear, when the tumor is already advanced. Thus, biomarkers associated with HCC and novel diagnostic methods are required to improve the diagnosis of HCC. Mass spectrometry (MS) is one of the most widely used analytical tools in proteomic research. Furthermore, tandem MS (MS/MS) has been applied for the discovery and verification of protein biomarkers for clinical use.

Areas covered: We review candidate glycoprotein biomarkers, including their aberrant glycosylation discovered by MS-based proteomics techniques and their diagnostic strategies using human blood samples. Finally, we discuss the limitations and prospects of MS-based approaches for clinical applications.

Expert commentary: The development of biomarkers with high sensitivity and specificity is essential for optimizing the management of HCC. Various glycoprotein biomarkers of HCC have been identified using MS-based techniques. MS-based assays will continue to play an important role in clinical applications for discovery and verification of biomarkers. Furthermore, combination of multibiomarker, improvements in sample enrichment and the development of highly sensitive MS methods will facilitate more rapid adoption of MS for the diagnosis of HCC.     

Development of a Chip/Chip/SRM platform using digital chip isoelectric focusing and LC-Chip mass spectrometry for enrichment and quantitation of low abundance protein biomarkers in human plasma

Protein biomarkers are critical for diagnosis, prognosis, and treatment of disease. The transition from protein biomarker discovery to verification can be a rate limiting step in clinical development of new diagnostics. Liquid chromatography-selected reaction monitoring mass spectrometry (LC-SRM MS) is becoming an important tool for biomarker verification studies in highly complex biological samples. Analyte enrichment or sample fractionation is often necessary to reduce sample complexity and improve sensitivity of SRM for quantitation of clinically relevant biomarker candidates present at the low ng/mL range in blood. In this paper, we describe an alternative method for sample preparation for LC-SRM MS, which does not rely on availability of antibodies. This new platform is based on selective enrichment of proteotypic peptides from complex biological peptide mixtures via isoelectric focusing (IEF) on a digital ProteomeChip (dPC) for SRM quantitation using a triple quadrupole (QQQ) instrument with an LC-Chip (Chip/Chip/SRM). To demonstrate the value of this approach, the optimization of the Chip/Chip/SRM platform was performed using prostate specific antigen (PSA) added to female plasma as a model system. The combination of immunodepletion of albumin and IgG with peptide fractionation on the dPC, followed by SRM analysis, resulted in a limit of quantitation of PSA added to female plasma at the level of ～1-2.5 ng/mL with a CV of ～13%. The optimized platform was applied to measure levels of PSA in plasma of a small cohort of male patients with prostate cancer (PCa) and healthy matched controls with concentrations ranging from 1.5 to 25 ng/mL. A good correlation (r(2) = 0.9459) was observed between standard clinical ELISA tests and the SRM-based assay. Our data demonstrate that the combination of IEF on the dPC and SRM (Chip/Chip/SRM) can be successfully applied for verification of low abundance protein biomarkers in complex samples.     

14-3-3 and enolase abundances in the CSF of Prion diseased rats

ABSTRACT

Creutzfeldt-Jakob disease (CJD) is characterized by an extended asymptomatic preclinical phase followed by rapid neurodegeneration. There are no effective treatments. CJD diagnosis is initially suspected based upon the clinical presentation of the disease and the exclusion of other etiologies. Neurologic symptoms are assessed in combination with results from cerebrospinal fluid (CSF) biomarker abundances, electroencephalography (EEG), magnetic resonance imaging (MRI), and in some countries, real-time quaking-induced conversion (RT-QuIC). Inconsistencies in sensitivities and specificities of prion disease biomarker abundance in CSF have been described, which can affect diagnostic certainty, but the utility of biomarkers for prognosis has not been fully explored. The clinical presentation of CJD is variable, and factors such as prion protein polymorphic variants, prion strain, and other genetic or environmental contributions may affect the disease progression, confounding the appearance or abundance of biomarkers in the CSF. These same factors may also affect the appearance or abundance of biomarkers, further confounding diagnosis. In this study, we controlled for many of these variables through the analysis of serial samples of CSF from prion-infected and control rats. Prion disease in laboratory rodents follows a defined disease course as the infection route and time, prion strain, genotype, and environmental conditions are all controlled. We measured the relative abundance of 14-3-3 and neuron-specific enolase (NSE) in CSF during the course of prion infection in rats. Even when disease-related, environmental and genetic variables were controlled, CSF 14-3-3 and NSE abundances were variable. Our study emphasizes the considerable diagnostic and prognostic limitations of these prion biomarkers.     

Utilizing human blood plasma for proteomic biomarker discovery

Candidate proteomic biomarker discovery from human plasma holds both incredible clinical potential as well as significant challenges. The dynamic range of proteins within plasma is known to exceed 10(10), and many potential biomarkers are likely present at lower protein abundances. At present, proteomic based MS analyses provide a dynamic range typically not exceeding approximately 10(3) in a single spectrum, and approximately 10(4)-10(6) when combined with on-line separations (e.g., reversed-phase gradient liquid chromatography), and thus are generally insufficient for low level biomarker detection directly from human plasma. This limitation is providing an impetus for the development of experimental methodologies and strategies to increase the possible number of detections within this biofluid. Discussed is the diversity of available approaches currently used by our laboratory and others to utilize human plasma as a viable medium for biomarker discovery. Various separation, depletion, enrichment, and quantitative efforts as well as recent improvements in MS capabilities have resulted in measurable improvements in the detection and identification of lower abundance proteins (by approximately 10-10(2)). Despite these improvements, further advances are needed to provide a basis for discovery of candidate biomarkers at very low levels. Continued development of depletion and enrichment techniques, coupled with improved pre-MS separations (both at the protein and peptide level) holds promise in extending the dynamic range of proteomic analysis.     

A new versatile peptide-based size exclusion chromatography platform for global profiling and quantitation of candidate biomarkers in hepatocellular carcinoma specimens

Disease biomarkers are predicted to be in low abundance; thus, the most crucial step of biomarker discovery is the efficient fractionation of clinical samples into protein sets that define disease stages and/or predict disease development. For this purpose, we developed a new platform that uses peptide-based size exclusion chromatography (pep-SEC) to quantify disease biomarker candidates. This new platform has many advantages over previously described biomarker profiling platforms, including short run time, high resolution, and good reproducibility, which make it suitable for large-scale analysis. We combined this platform with isotope labeling and label-free methods to identify and quantitate differentially expressed proteins in hepatocellular carcinoma (HCC) tissues. When we combined pep-SEC with a gas phase fractionation method, which broadens precursor ion selection, the protein coverage was significantly increased, which is critical for the global profiling of HCC specimens. Furthermore, pep-SEC-LC-MS/MS analysis enhanced the detection of low-abundance proteins (e.g. insulin receptor substrate 2 and carboxylesterase 1) and glycopeptides in HCC plasma. Thus, our pep-SEC platform is an efficient and versatile pre-fractionation system for the large-scale profiling and quantitation of candidate biomarkers in complex disease proteomes.     

Diagnostic function of the neuroinflammatory biomarker YKL-40 in Alzheimer’s disease and other neurodegenerative diseases

Introduction: Neuroinflammation is a crucial mechanism in the pathophysiology of neurodegenerative diseases pathophysiology. Cerebrospinal fluid (CSF) YKL-40 – an indicator of microglial activation ? has recently been identified by proteomic studies as a candidate biomarker for Alzheimer’s disease (AD).

Areas covered: We review the impact of CSF YKL-40 as a pathophysiological biomarker for AD and other neurodegenerative diseases. CSF YKL-40 concentrations have been shown to predict progression from prodromal mild cognitive impairment to AD dementia. Moreover, a positive association between CSF YKL-40 and other biomarkers of neurodegeneration – particularly total tau protein ? has been reported during the asymptomatic preclinical stage of AD and other neurodegenerative diseases. Albeit preliminary, current data do not support an association between APOE-ε4 status and CSF YKL-40 concentrations. When interpreting the diagnostic/prognostic significance of CSF YKL-40 concentrations in neurodegenerative diseases, potential confounders – including age, metabolic and cardiovascular risk factors, diagnostic criteria for selecting cases/controls – need to be considered.

Expert opinion/commentary: CSF YKL-40 represents a pathophysiological biomarker reflecting immune/inflammatory mechanisms in neurodegenerative diseases, associated with tau protein pathology. Besides being associated with tau pathology, CSF YKL-40 adds to the growing array of biomarkers reflecting distinct molecular brain mechanisms potentially useful for stratifying individuals for biomarker-guided, targeted anti-inflammatory therapies emerging from precision medicine.     

Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

Selected reaction monitoring (SRM) - also known as multiple reaction monitoring (MRM) - has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for, e.g. detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein, we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications, as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low- to sub-ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.     

Prospective applications of ultrahigh resolution proteomics in clinical mass spectrometry

Introduction: Advances in mass spectrometry (MS)-based proteomic strategies have resulted in robust protein biomarker discovery studies often performed on high resolution accurate mass (HRAM) platforms. For successful translation of promising protein biomarkers into useful clinical tests, trans-sector networks and collaboration among stakeholders involved in the biomarker pipeline are urgently needed.

Areas covered: In this perspective, literature- and empirical evidence is combined with author’s opinions to discuss the progress of ultrahigh resolution MS and provide insight in its potential for validation and development of clinical tests.

Expert commentary: Thus far two ‘low resolution’ MS strategies have been implemented in the clinic: quantification of proteins using triple quadrupole instruments and identification of unknown microorganisms using comparative analysis with spectral libraries on MALDI-TOF instruments. The rise of HRAM technology further boosts the potential of MS-based tests for detection and quantitation of disease-specific biomarkers which meet the analytical performance specifications needed for clinical assays.     

Systemic sclerosis biomarkers discovered using mass-spectrometry-based proteomics: a systematic review

Abstract

Context: Systemic sclerosis (SSc) is an autoimmune disease with incompletely known physiopathology. There is a great challenge to predict its course and therapeutic response using biomarkers.

Objective: To critically review proteomic biomarkers discovered from biological specimens from systemic sclerosis patients using mass spectrometry technologies.

Methods: Medline and Embase databases were searched in February 2014.

Results: Out of the 199 records retrieved, a total of 20 records were included, identifying 116 candidate proteomic biomarkers.

Conclusion: Research in SSc proteomic biomarkers should focus on biomarker validation, as there are valuable mass-spectrometry proteomics studies in the literature.     

Candidate proteomic biomarkers for non-alcoholic fatty liver disease (steatosis and non-alcoholic steatohepatitis) discovered with mass-spectrometry: a systematic review

Context: Non-alcoholic fatty liver disease (NAFLD) is characterized by lipid accumulation in the liver which is accompanied by a series of metabolic deregulations. There are sustained research efforts focusing upon biomarker discovery for NAFLD diagnosis and its prognosis in order investigate and follow-up patients as minimally invasive as possible.

Objective: The objective of this study is to critically review proteomic studies that used mass spectrometry techniques and summarize relevant proteomic NAFLD candidate biomarkers.

Methods: Medline and Embase databases were searched from inception to December 2014.

Results: A final number of 22 records were included that identified 251 candidate proteomic biomarkers. Thirty-three biomarkers were confirmed – 14 were found in liver samples, 21 in serum samples, and two from both serum and liver samples.

Conclusion: Some of the biomarkers identified have already been extensively studied regarding their diagnostic and prognostic capacity. However, there are also more potential biomarkers that still need to be addressed in future studies.     

Proteomic profiling of the cancer cell secretome: informing clinical research

Introduction: Cancer represents one of the major causes of human deaths. Identification of proteins as biomarkers for early detection of cancer and therapeutic targets for cancer treatment are important issues in precision medicine. Secretome of cancer cells represents the collection of proteins secreted or shed from cancer cells. Proteomic profiling of the cancer cell secretome has been proven to be a convenient and efficient way to discover cancer biomarker and/or therapeutic targets.

Areas covered: There have been numerous reviews describing the history and application of secretome analysis in cancer biomarker/therapeutic target research. The present review focuses on the technological advancement for profiling low-molecular-mass proteins in secretome, the latest information regarding the new candidate biomarkers and molecular mechanisms discovered on the basis of cancer cell secretome analysis, as well as the previously discovered candidate biomarkers that enter into clinical trials.

Expert commentary: Current technologies for protein sample preparation/separation and MS-based protein identification have allowed in-depth analysis of cancer cell secretome. Future efforts should focus on the comprehensiveness of cancer cell secretome, meta-analysis of different secretome datasets and integrated analysis via combining other omics datasets, as well as the incorporation of MS-based biomarker verification pipeline into both preclinical studies and clinical trials.     

Is cerebrospinal fluid obtained for diagnostic purpose a good material for biomarker studies in amyotrophic lateral sclerosis?

Abstract

The cerebrospinal fluid (CSF) used for identification of molecular biomarkers in amyotrophic lateral sclerosis (ALS) is mainly obtained from lumbar puncture (LP) performed to exclude other causes of motor neuron damage.

Aim: The aim of the study was to analyze whether CSF of ALS patients obtained for diagnostic purposes is suitable for biomarker studies in the entire ALS population.

Material and methods: We analyzed the medical data, LP frequency and CSF parameters in 568 ALS patients.

Results: LP was performed in 34% of cases. Patients who underwent LP were significantly younger and more frequently presented limb onset ALS, there were no differences in the clinical phenotypes.

Conclusion: CSF obtained for diagnostic purposes can be used for biomarkers studies in ALS.     

High abundance proteins depletion vs low abundance proteins enrichment: comparison of methods to reduce the plasma proteome complexity

Background

To date, the complexity of the plasma proteome exceeds the analytical capacity of conventional approaches to isolate lower abundance proteins that may prove to be informative biomarkers. Only complex multistep separation strategies have been able to detect a substantial number of low abundance proteins (<100 ng/ml). The first step of these protocols is generally the depletion of high abundance proteins by the use of immunoaffinity columns or, alternatively, the enrichment of by the use of solid phase hexapeptides ligand libraries.

Methodology/Principal Findings

Here we present a direct comparison of these two approaches. Following either approach, the plasma sample was further fractionated by SCX chromatography and analyzed by RP-LC-MS/MS with a Q-TOF mass spectrometer. The depletion of the 20 most abundant plasma proteins allowed the identification of about 25% more proteins than those detectable following low abundance proteins enrichment. The two datasets are partially overlapping and the identified proteins belong to the same order of magnitude in terms of plasma concentration.

Conclusions/Significance

Our results show that the two approaches give complementary results. However, the enrichment of low abundance proteins has the great advantage of obtaining much larger amount of material that can be used for further fractionations and analyses and emerges also as a cheaper and technically simpler approach. Collectively, these data indicate that the enrichment approach seems more suitable as the first stage of a complex multi-step fractionation protocol.     

Application of proteomics to graft-versus-host disease: from biomarker discovery to potential clinical applications

Introduction: Graft-versus-host disease (GVHD) is a frequent and potentially life-threatening complication that occurs in many patients who undergo hematopoietic stem cell transplantation. In an effort to develop blood and tissue-based biochemical assays for GVHD diagnosis, high throughput proteomic platforms have been widely utilized for the identification and validation of disease biomarkers for both acute and chronic GVHD.

Areas covered: This article reviews biomarker research findings on acute and chronic GVHD ascertained by studying peripheral blood, urine and saliva that gives biological information on systemic or localized disease. While the primary focus of GVHD biomarker discovery has been on identification and validation of prognostic and predictive biomarkers that might allow stratification of disease risk, molecular biomarkers that might aid patient diagnosis and/or response to treatment have also been reported.

Expert commentary: Unbiased as well as targeted proteomic studies of acute and chronic GVHD have identified some distinguishing features of the two diseases especially the role of certain immune cell populations. A combination of patient risk stratification using panels of biomarkers and the application of novel targeted therapeutics should help to reduce the burden of GVHD, and hence improve the quality of life for patients following hematopoietic stem cell transplantation.