Reproducibility of mass spectrometry based protein profiles for diagnosis of breast cancer across clinical studies: a systematic review

Serum protein profiling by mass spectrometry has achieved attention as a promising technology in oncoproteomics. We performed a systematic review of published reports on protein profiling as a diagnostic tool for breast cancer. The MEDLINE, EMBASE, and COCHRANE databases were searched for original studies reporting discriminatory protein peaks for breast cancer as either protein identity or as m/ z values in the period from January 1995 to October 2006. To address the important aspect of reproducibility of mass spectrometry data across different clinical studies, we compared the published lists of potential discriminatory peaks with those peaks detected in an original MALDI MS protein profiling study performed by our own research group. A total of 20 protein/peptide profiling studies were eligible for inclusion in the systematic review. Only 3 reports included information on protein identity. Although the studies revealed a considerable heterogeneity in relation to experimental design, biological variation, preanalytical conditions, methods of computational data analysis, and analytical reproducibility of profiles, we found that 45% of peaks previously reported to correlate with breast cancer were also detected in our experimental study. Furthermore, 25% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility, we were able to demonstrate overlap in peaks between clinical studies indicating some convergence toward a set of common discriminating, reproducible peaks for breast cancer. These peaks should be further characterized for identification of the protein identity and validated as biomarkers for breast cancer.     

Proteomic technologies for identification of serum biomarkers of potential autoimmune demyelinating polyneuropathies

Time-of-flight MALDI mass spectrometry (MALDI-TOF MS) profiling of blood serum of patients with Guillain-Barré syndrome (GBS, 36 samples), chronic inflammatory demyelinating polyneuropathy (CIDP, 24 samples), and practically healthy donors (HD, 35 samples) was carried out in order to identify potential biomarkers of autoimmune demyelinating polyneuropathies (ADP). To simplify the peptide-protein mixture of serum prior to MALDI-TOF-MS analysis, samples were prefractionated on magnetic beads with a weak cation-exchange (MB-WCX) surface. Comparative analysis of mass spectrometric data using the classification algorithms (genetic and neural network-controlled) revealed a characteristic set of peaks and a correlating change area with a high specificity and sensitivity of the differentiated mass spectrometry profiles of the blood serum of patients with DPNP and healthy donors (for GBS, values of these characteristics reached 100 and 100%, and for CIDP, 94.1 and 100% respectively). Comparative analysis of mass spectrometric profiles of serum samples obtained from patients with GBS and CIDP allowed us to build a classification model to differentiate these diseases from each other, with a specificity of 88.9 and a sensitivity of 80%.     

Diagnostic application of serum proteomic patterns in gastric cancer patients by ProteinChip surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is one of thecurrently used techniques to identify biomarkers for cancers. This study was planned to establish a system to accurately distinguish gastric cancer patients by using SELDI-TOF-MS. A total of 100 serum samples obtained from 60 individuals with gastric cancer and 40 healthy individuals were screened. Protein expression profiles were expressed on CM10 ProteinChip arrays and analyzed. Peak intensities were analyzed with the Biomarker Wizard software to identify peaks showing significantly different intensities between normal and cancer groups. Classification analysis and construction of decision trees were done with the Biomarker Pattern software 5.0. Seventeen protein peaks showed significant differences between the two groups. The decision tree which gave the highest discrimination included four peaks at mass 5,919, 8,583, 10,286, and 13,758 as splitters. The sensitivity and specificity for classification of the decision tree were 96.7% (58/60) and 97.5% (39/40), respectively. When the protein biomarker pattern was tested on a blinded test set, it yielded a sensitivity of 93.3% (28/30) and a specificity of 90% (18/20). These results suggest that serum protein profiling by the SELDI system may distinguish gastric cancer patients from healthy controls with relatively high sensitivity and specificity.     

A well‐characterised peak identification list of MALDI MS profile peaks for human blood serum

MALDI MS profiling, using easily available body fluids such as blood serum, has attracted considerable interest for its potential in clinical applications. Despite the numerous reports on MALDI MS profiling of human serum, there is only scarce information on the identity of the species making up these profiles, particularly in the mass range of larger peptides. Here, we provide a list of more than 90 entries of MALDI MS profile peak identities up to 10 kDa obtained from human blood serum. Various modifications such as phosphorylation were detected among the peptide identifications. The overlap with the few other MALDI MS peak lists published so far was found to be limited and hence our list significantly extends the number of identified peaks commonly found in MALDI MS profiling of human blood serum.     

Proteomic technologies for identification of serum potential biomarkers of autoimmune demyelinating polyneuropathies

Time-of-flight MALDI mass spectrometry (MALDI-TOF-MS) profiling of blood serum of patients with Guillain-Barré syndrome (GBS, 36 samples), chronic inflammatory demyelinating polyneuropathy (CIDP, 24 samples) and practically healthy donors (HD) (35 samples) was carried out in order to identify potential biomarkers of autoimmune demyelinating polyneuropathies (ADP). To simplify the peptide-protein mixture of serum prior to MALDI-TOF-MS analysis samples were pre-fractionated on magnetic microparticles with a weak cation-exchange (MB-WCX) surface. Comparative analysis of mass spectrometric data using the classification algorithms (genetic and neural network-controlled) revealed a characteristic set of peaks, agreed change area with a high specificity and sensitivity of the differentiated mass spectrometry profiles of the blood serum of patients with DPNP and healthy donors (for GBS values of these characteristics reached 100 and 100, and for CIDP 94.1 and 100% respectively). Comparative analysis of mass spectrometric profiles of serum samples obtained from patients with GBS and CIDP, allowed to build a classification model to differentiate these diseases from each other, with a specificity of 88.9 and a sensitivity of 80%.     

Identification of the thrombin light chain a as the single best mass for differentiation of gastric cancer patients from individuals with dyspepsia by proteome analysis

Gastric cancer mortality is second only to lung cancer, and its prognosis is dismal. Using surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry, we previously identified a single best mass, which could separate gastric cancer from patients without cancer, with a sensitivity of 89.9% and a specificity of 90%. Using protein liquid chromatography systems with various chromatography media and MS/MS analysis, we were able to identify thrombin light chain A, a proteolytic fragment of prothrombin, as the single best mass for early detection of gastric cancer patients. These findings indicate that disturbances in the coagulation-system are early events in gastric cancer biology and that a decrease or loss of thrombin light chain A, which we termed negative serum protein profiling, may contribute to the diagnosis of cancer patients.     

Tissue profiling by mass spectrometry: a review of methodology and applications

Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) has become a valuable tool to address a broad range of questions in many areas of biomedical research. One such application allows spectra to be obtained directly from intact tissues, termed "profiling" (low resolution) and "imaging" (high resolution). In light of the fact that MALDI tissue profiling allows over a thousand peptides and proteins to be rapidly detected from a variety of tissues, its application to disease processes is of special interest. For example, protein profiles from tumors may allow accurate prediction of tumor behavior, diagnosis, and prognosis and uncover etiologies underlying idiopathic diseases. MALDI MS, in conjunction with laser capture microdissection, is able to produce protein expression profiles from a relatively small number of cells from specific regions of heterogeneous tissue architectures. Imaging mass spectrometry enables the investigator to assess the spatial distribution of proteins, drugs, and their metabolites in intact tissues. This article provides an overview of several tissue profiling and imaging applications performed by MALDI MS, including sample preparation, matrix selection and application, histological staining prior to MALDI analysis, tissue profiling, imaging, and data analysis. Several applications represent direct translation of this technology to clinically relevant problems.     

Mass spectrometry imaging and profiling of single cells

Mass spectrometry imaging and profiling of individual cells and subcellular structures provide unique analytical capabilities for biological and biomedical research, including determination of the biochemical heterogeneity of cellular populations and intracellular localization of pharmaceuticals. Two mass spectrometry technologies-secondary ion mass spectrometry (SIMS) and matrix assisted laser desorption/ionization mass spectrometry (MALDI MS)-are most often used in micro-bioanalytical investigations. Recent advances in ion probe technologies have increased the dynamic range and sensitivity of analyte detection by SIMS, allowing two- and three-dimensional localization of analytes in a variety of cells. SIMS operating in the mass spectrometry imaging (MSI) mode can routinely reach spatial resolutions at the submicron level; therefore, it is frequently used in studies of the chemical composition of subcellular structures. MALDI MS offers a large mass range and high sensitivity of analyte detection. It has been successfully applied in a variety of single-cell and organelle profiling studies. Innovative instrumentation such as scanning microprobe MALDI and mass microscope spectrometers enables new subcellular MSI measurements. Other approaches for MS-based chemical imaging and profiling include those based on near-field laser ablation and inductively-coupled plasma MS analysis, which offer complementary capabilities for subcellular chemical imaging and profiling.     

Reproducibility of mass spectrometry based protein profiles for diagnosis of ovarian cancer across clinical studies: A systematic review

The focus of this systematic review is to give an overview of the current status of clinical protein profiling studies using MALDI and SELDI MS platforms in the search for ovarian cancer biomarkers. A total of 34 profiling studies were qualified for inclusion in the review. Comparative analysis of published discriminatory peaks to peaks found in an original MALDI MS protein profiling study was made to address the key question of reproducibility across studies. An overlap was found despite substantial heterogeneity between studies relating to study design, biological material, pre-analytical treatment, and data analysis. About 47% of the peaks reported to be associated to ovarian cancer were also represented in our experimental study, and 34% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility an overlap in peaks between clinical studies was demonstrated, which indicate convergence toward a set of common discriminating, reproducible peaks for ovarian cancer. The potential of the discriminating protein peaks for clinical use as ovarian cancer biomarkers will be discussed and evaluated. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

From proteomic multimarker profiling to interesting proteins: thymosin-β(4) and kininogen-1 as new potential biomarkers for inflammatory hepatic lesions

Despite tremendous efforts in disclosing the pathophysiological and epidemiological factors associated with liver fibrogenesis, non-invasive diagnostic measures to estimate the clinical outcome and progression of liver fibrogenesis are presently limited. Therefore, there is a mandatory need for methodologies allowing the reasonable and reliable assessment of the severity and/or progression of hepatic fibrogenesis. We here performed proteomic serum profiling by matrix-assisted laser desorption ionization time-of-flight mass spectrometry in 179 samples of patients chronically infected with hepatitis C virus and 195 control sera. Multidimensional analysis of spectra allowed the definition of algorithms capable to distinguish class-specific protein expression profiles in serum samples. Overall about 100 peaks could be detected per single spectrum. Different algorithms including protein peaks in the range of 2000 and 10,000 Da were generated after pre-fractionation on a weak cation exchange surface. A specificity of 93% with a sensitivity of 86% as mean of the test set results was found, respectively. The nature of three of these protein peaks that belonged to kininogen-1 and thymosin-β(4) was further analysed by tandem mass spectrometry (MS)/MS. We further found that kininogen-1 mRNA was significantly down-regulated in cirrhotic livers. We have identified kininogen-1 and thymosin-β(4) as potential new biomarkers for human chronic hepatitis C and conclude that serum profiling is a reliable technique to identify hepatitis-associated expression patterns. Based on the high throughput capability, the identified differential protein panel may serve as a diagnostic marker and warrants further validation in larger cohorts.     

Optimization of MALDI-TOF MS detection for enhanced sensitivity of affinity-captured proteins spanning a 100 kDa mass range

Analysis of complex biological samples by MALDI-TOF mass spectrometry has been generally limited to the detection of low-mass protein (or protein fragment) peaks. We have extended the mass range of MALDI-TOF high-sensitivity detection by an order of magnitude through the combined optimization of instrument parameters, data processing, and sample preparation procedures for affinity capture. WCX, C3, and IMAC magnetic beads were determined to be complementary and most favorable for broad mass range protein profiling. Key instrument parameters for extending mass range included adjustment of the ADC offset and preamplifier filter values of the TOF detector. Data processing was improved by a combination of constant and quadratic down-sampling, preceded by exponential baseline subtraction, to increase sensitivity of signal peaks. This enhancement in broad mass range detection of protein signals will be of direct benefit in MS expression profiling studies requiring full linear range mass detection.     

Exploring proteins in Anopheles gambiae male and female antennae through MALDI mass spectrometry profiling

MALDI profiling and imaging mass spectrometry (IMS) are novel techniques for direct analysis of peptides and small proteins in biological tissues. In this work we applied them to the study of Anopheles gambiae antennae, with the aim of analysing expression of soluble proteins involved in olfaction perireceptor events. MALDI spectra obtained by direct profiling on single antennae and by the analysis of extracts, showed similar profiles, although spectra obtained through profiling had a richer ion population and higher signal to noise ratio. Male and female antennae showed distinct protein profiles. MALDI imaging experiments were also performed and differences were observed in the localization of some proteins. Two proteins were identified through high resolution measurement and top-down MS/MS experiments. A 8 kDa protein only present in the male antennae matched with an unannotated sequence of the An. gambiae genome, while the presence of odorant binding protein 9 (OBP-9) was confirmed through experiments of 2-DE, followed by MS and MS/MS analysis of digested spots. This work shows that MALDI MS profiling is a technique suitable for the analysis of proteins of small and medium MW in insect appendices, and allows obtaining data for several specimens which can be investigated for differences between groups. Proteins of interest can be identified through other complementary MS approaches.     

Assessing protein patterns in disease using imaging mass spectrometry

Direct tissue profiling and imaging mass spectrometry (MS) provides a detailed assessment of the complex protein pattern within a tissue sample. MALDI MS analysis of thin tissue sections results in over of 500 individual protein signals in the mass range of 2 to 70 kDa that directly correlate with protein composition within a specific region of the tissue sample. To date, profiling and imaging MS has been applied to multiple diseased tissues, including human gliomas and nonsmall cell lung cancer. Interrogation of the resulting complex MS data sets has resulted in identification of both disease-state and patient-prognosis specific protein patterns. These results suggest the future usefulness of proteomic information in assessing disease progression, prognosis, and drug efficacy.     

Detergent addition to tryptic digests and ion mobility separation prior to MS/MS improves peptide yield and protein identification for in situ proteomic investigation of frozen and formalin‐fixed paraffin‐embedded adenocarcinoma tissue sections

The identification of proteins involved in tumour progression or which permit enhanced or novel therapeutic targeting is essential for cancer research. Direct MALDI analysis of tissue sections is rapidly demonstrating its potential for protein imaging and profiling in the investigation of a range of disease states including cancer. MALDI‐mass spectrometry imaging (MALDI‐MSI) has been used here for direct visualisation and in situ characterisation of proteins in breast tumour tissue section samples. Frozen MCF7 breast tumour xenograft and human formalin‐fixed paraffin‐embedded breast cancer tissue sections were used. An improved protocol for on‐tissue trypsin digestion is described incorporating the use of a detergent, which increases the yield of tryptic peptides for both fresh frozen and formalin‐fixed paraffin‐embedded tumour tissue sections. A novel approach combining MALDI‐MSI and ion mobility separation MALDI‐tandem mass spectrometry imaging for improving the detection of low‐abundance proteins that are difficult to detect by direct MALDI‐MSI analysis is described. In situ protein identification was carried out directly from the tissue section by MALDI‐MSI. Numerous protein signals were detected and some proteins including histone H3, H4 and Grp75 that were abundant in the tumour region were identified.     

Serum protein profiling by solid phase extraction and mass spectrometry: A future diagnostics tool?

Serum protein profiling by MS is a promising method for early detection of disease. Important characteristics for serum protein profiling are preanalytical factors, analytical reproducibility and high throughput. Problems related to preanalytical factors can be overcome by using standardized and rigorous sample collection and sample handling protocols. The sensitivity of the MS analysis relies on the quality of the sample; consequently, the blood sample preparation step is crucial to obtain pure and concentrated samples and enrichment of the proteins and peptides of interest. This review focuses on the serum sample preparation step prior to protein profiling by MALDI MS analysis, with particular focus on various SPE methods. The application of SPE techniques with different chromatographic properties such as RP, ion exchange, or affinity binding to isolate specific subsets of molecules (subproteomes) is advantageous for increasing resolution and sensitivity in the subsequent MS analysis. In addition, several of the SPE sample preparation methods are simple and scalable and have proven easy to automate for higher reproducibility and throughput, which is important in a clinical proteomics setting.     

MALDI mass spectrometry in prostate cancer biomarker discovery

Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Application of the random forest classification method to peaks detected from mass spectrometric proteomic profiles of cancer patients and controls

The random forest classification method was applied to classify samples from 76 breast cancer patients and 77 controls whose proteomic profile had been obtained using mass spectrometry. The analysis consisted of two stages, the detection of peaks from the profiles and the construction of a classification rule using random forests. Using a peak detection method based on finding common local maxima in the smoothed sample spectra, 444 peaks were detected, reducing to 365 robust peaks found in at least 7 out of 10 random subsets of samples. Subjects were classified as cases or controls using the random forest algorithm applied to the 365 peaks. Based on the prediction of the status of out-of-bag samples, the total error rate was 16.3%, with a sensitivity of 81.6% and a specificity of 85.7%. Measures of importance of each of the peaks were calculated to identify regions of the spectrum influencing the classification, and the four most important peaks were identified as mz3863_13, mz2943_12, mz3193_44 and mz8925_94. Combining initial peak detection with the random forest algorithm provides a high-performance classification system for proteomic data, with unbiased estimates of future performance.     

Identification of serum proteomic biomarkers for early porcine reproductive and respiratory syndrome (PRRS) infection

ABSTRACT: BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) is one of the most significant swine diseases worldwide. Despite its relevance, serum biomarkers associated with early-onset viral infection, when clinical signs are not detectable and the disease is characterized by a weak anti-viral response and persistent infection, have not yet been identified. Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) is a reproducible, accurate, and simple method for the identification of biomarker proteins related to disease in serum. This work describes the SELDI-TOF MS analyses of sera of 60 PRRSV-positive and 60 PRRSV-negative, as measured by PCR, asymptomatic Large White piglets at weaning. Sera with comparable and low content of hemoglobin (< 4.52 ug/mL) were fractionated in 6 different fractions by anion-exchange chromatography and protein profiles in the mass range 1-200 kDa were obtained with the CM10, IMAC30, and H50 surfaces. RESULTS: A total of 200 significant peaks (p < 0.05) were identified in the initial discovery phase of the study and 47 of them were confirmed in the validation phase. The majority of peaks (42) were up-regulated in PRRSV-positive piglets, while 5 were down-regulated. A panel of 14 discriminatory peaks identified in fraction 1 (pH=9), on the surface CM10, and acquired at low focus mass provided a serum protein profile diagnostic pattern that enabled to discriminate between PRRSV-positive and -negative piglets with a sensitivity and specificity of 77% and 73%, respectively. CONCLUSIONS: SELDI-TOF MS profiling of sera from PRRSV-positive and PRRSV-negative asymptomatic piglets provided a proteomic signature with large scale diagnostic potential for early identification of PRRSV infection in weaning piglets. Furthermore, SELDI-TOF protein markers represent a refined phenotype of PRRSV infection that might be useful for whole genome association studies.     

Proteomic profiling of urine for the detection of colon cancer

Background

Colorectal cancer is the second most common cause of cancer related death in the developed world. To date, no blood or stool biomarkers with both high sensitivity and specificity for potentially curable early stage disease have been validated for clinical use. SELDI and MALDI profiling are being used increasingly to search for biomarkers in both blood and urine. Both techniques provide information predominantly on the low molecular weight proteome (<15 kDa). There have been several reports that colorectal cancer is associated with changes in the serum proteome that are detectable by SELDI and we hypothesised that proteomic changes would also be detectable in urine.

Results

We collected urine from 67 patients with colorectal cancer and 72 non-cancer control subjects, diluted to a constant protein concentration and generated MALDI and SELDI spectra. The intensities of 19 peaks differed significantly between cancer and non-cancer patients by both t-tests and after adjusting for confounders using multiple linear regressions. Logistic regression classifiers based on peak intensities identified colorectal cancer with up to 78% sensitivity at 87% specificity. We identified and independently quantified 3 of the discriminatory peaks using synthetic stable isotope peptides (an 1885 Da fragment of fibrinogen and hepcidin-20) or ELISA (β2-microglobulin).

Conclusion

Changes in the urine proteome may aid in the early detection of colorectal cancer.     

Culture conditions and sample preparation methods affect spectrum quality and reproducibility during profiling of Staphylococcus aureus with matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry

Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) has emerged as a promising tool to rapidly characterize Staphylococcus aureus. Different protocols have been employed, but effects of experimental factors, such as culture condition and sample preparation, on spectrum quality and reproducibility have not been rigorously examined. We applied MALDI‐TOF MS to characterize a model system consisting of five methicillin‐sensitive (MSSA) and five methicillin‐resistant S. aureus isolates (MRSA) under two culture conditions (agar and broth) and using two sample preparation methods [intact cell method and protein extraction method (PEM)]. The effects of these treatments on spectrum quality and reproducibility were quantified. PEM facilitated increases in the number of peaks and mass range width. Broth cultures further improved spectrum quality in terms of increasing the number of peaks. In addition, PEM increased reproducibility in samples prepared using identical culture conditions. MALDI imaging data suggested that the improvement in reproducibility may result from a more homogeneous distribution of sample associated with the broth/PEM treatment. Broth/PEM treatment also yielded the highest rate (96%) of correct classification for MRSA. Taken together, these results suggest that broth/PEM maximizes the performance of MALDI‐TOF MS to characterize S. aureus.

Significance and Impact of the Study

Two culture conditions (agar or broth) and two sample preparation methods (intact cell or protein extraction) were evaluated for their effects on profiling of Staphylococcus aureus using matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS). Results indicated that MALDI‐enabled profiling of S. aureus is most effective when cultures are grown in broth and processed using a protein extraction‐based approach. These findings should enhance future efforts to maximize the performance of this approach to characterize strains of S. aureus.