Peptide profiling in epithelial tumor plasma by the emerging proteomic techniques

A qualitative description of the peptide sharing between poliovirus and Homo sapiens

In a companion paper, we reported that pentapeptides from human poliovirus 1, Mahoney strain, occur repeatedly in human proteins for a total of more than 18,000 overlaps. In the present study, we describe the distribution of the polio pentapeptides throughout biochemical pathways and networks characterizing functions and tissues in the human host. The present study might be of help to better define the poliovirus-host relationships as well as for designing peptide modules with anti-polio activity.

Identification of Autoantibodies for α and γ-Enolase in Serum from a Patient with Melanoma

Melanoma is one of lethal malignant skin tumors and the sole effective cure for the disease can be achieved by surgical resection of primary tumor and early diagnosis for melanoma is crucial for patients’ prognosis. Detection of novel tumor-related antibodies would aid in the diagnosis of early-stage cancer, in the detection of recurrence and in the development of a more effective immunotherapy. In the middle of the exploration of a candidate of biomarker for melanoma by proteomics-base technique, we encountered the coexistence of autoantibodies for α-enolase and γ-enolase in serum derived from a patient with melanoma, who had received the repeated treatments with alkylating agents and interferon β. Although melanoma is known to be a highly antigenic tumor, it is still unclear why these autoantibodies appeared. To evaluate the usefulness in detecting the circulating α-enolase or γ-enolase autoantibodies in serum from melanoma patients for biomarkers for tumor progression, more studies are needed.

The absolute quantification of eight inter-α-trypsin inhibitor heavy chain 4 (ITIH4)-derived peptides in serum from breast cancer patients

PURPOSE

Various studies exploring the potential of the low-molecular-weight serum peptidome have identified proteolytic cleavage products of inter-α-trypsin inhibitor heavy chain-4 (ITIH(4)) as potential markers for different types of cancer, presumably generated by tumor-associated exoproteases. However, further elucidation of the discriminative properties of such peptides requires specific quantitative analytical methods.

EXPERIMENTAL DESIGN

Using a recently developed and fully validated liquid chromatography-tandem mass spectrometric method, we have compared absolute serum concentrations of eight peptides derived from ITIH(4 [658-687]) to ([667-687]) (ITIH(4)-30 to -21) between breast cancer patients (n=45) and controls (n=78). Furthermore, serum samples obtained before and after surgical removal of the tumor were analyzed (n=30).

RESULTS

The inter-individual variability in measured serum concentrations was high. Nevertheless, most peptides showed a tendency toward elevated levels in the presence of the breast cancer tumor. Significantly increased serum concentrations were observed in the breast cancer group for ITIH(4)-25 (p=0.036) and -29 (p=0.015). Intra-individual comparisons of serum obtained before and after surgery showed significantly decreased serum levels after surgery for seven of the ITIH(4)-derived peptides (p<0.02).

CONCLUSIONS AND CLINICAL RELEVANCE

The obtained results particularly suggest potential for these ITIH(4)-derived peptides in the follow-up of breast cancer after surgery.

Sensitive liquid chromatography/tandem mass spectrometry assay for absolute quantification of ITIH4-derived putative biomarker peptides in clinical serum samples

To explore the potential of peptide fragments derived from inter-alpha-trypsin inhibitor heavy chain-4 (ITIH(4)) as serum markers for different cancer types, sensitive and specific analytical assays are required. Liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) would be suitable; however, a previously developed method for quantification of eight ITIH(4) fragments (ITIH(4)-21, -22, -25, -26, -27, -28, -29 and -30) was found to be insensitive for clinical use. A more sensitive LC/MS/MS assay has now been developed and validated, which was further optimized to facilitate analyses of large sets of clinical serum samples. Benefits compared to the previous method include reduction of sample volume (100 microL), omission of protein precipitation and evaporation and transferring solid-phase extraction (SPE) to a 96-well format. Chromatographic separation on an XBridge BEH300 C(18) column, using a water/methanol gradient containing acetic acid, was coupled to triple quadrupole mass spectrometric detection, applying heated electrospray ionization. Method validation revealed deviations from nominal concentrations below 10.1% and intra- and inter-assay precisions below 17.4 and 20.0%, respectively, at the lower limit of quantification (LLOQ) for all peptides. The reported changes resulted in more rapid and efficient analyses and reduced LLOQs for the six less abundant peptides (1.2; 1.0; 1.2; 2.0; 2.0 and 2.0 ng/mL vs. 2.1; 2.0; 2.5; 2.6; 2.2 and 2.4 ng/mL for ITIH(4)-21, -22, -25, -27, -28 and -29, respectively). The method has shown its applicability by quantifying all peptides in appropriate concentration ranges in serum from healthy volunteers and application to clinical samples from breast cancer patients.

Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer

Background

The proteomics approach termed proteome pattern analysis has been shown previously to have potential in the detection and classification of breast cancer. Here we aimed to identify changes in serum proteome patterns related to therapy of breast cancer patients.

Methods

Blood samples were collected before the start of therapy, after the surgical resection of tumors and one year after the end of therapy in a group of 70 patients diagnosed at early stages of the disease. Patients were treated with surgery either independently (26) or in combination with neoadjuvant chemotherapy (5) or adjuvant radio/chemotherapy (39). The low-molecular-weight fraction of serum proteome was examined using MALDI-ToF mass spectrometry, and then changes in intensities of peptide ions registered in a mass range between 2,000 and 14,000 Da were identified and correlated with clinical data.

Results

We found that surgical resection of tumors did not have an immediate effect on the mass profiles of the serum proteome. On the other hand, significant long-term effects were observed in serum proteome patterns one year after the end of basic treatment (we found that about 20 peptides exhibited significant changes in their abundances). Moreover, the significant differences were found primarily in the subgroup of patients treated with adjuvant therapy, but not in the subgroup subjected only to surgery. This suggests that the observed changes reflect overall responses of the patients to the toxic effects of adjuvant radio/chemotherapy. In line with this hypothesis we detected two serum peptides (registered m/z values 2,184 and 5,403 Da) whose changes correlated significantly with the type of treatment employed (their abundances decreased after adjuvant therapy, but increased in patients treated only with surgery). On the other hand, no significant correlation was found between changes in the abundance of any spectral component or clinical features of patients, including staging and grading of tumors.

Conclusions

The study establishes a high potential of MALDI-ToF-based analyses for the detection of dynamic changes in the serum proteome related to therapy of breast cancer patients, which revealed the potential applicability of serum proteome patterns analyses in monitoring the toxicity of therapy.

Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer

Background

Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry.

Methods

Blood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other high-molecular-weight serum proteins. Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves.

Results

We have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients. The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity. Spectral components (i.e., protein ions) that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity). Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression. In addition, we observed a significantly (p = 0.0003) increased level of osteopontin in blood of the group of cancer patients studied (however, the plasma level of osteopontin classified cancer samples with 88% sensitivity but only 28% specificity).

Conclusion

MALDI-ToF spectrometry of serum has an obvious potential to differentiate samples between early breast cancer patients and healthy controls. Importantly, a classifier built on MS-based serum proteome patterns outperforms available protein biomarkers analyzed in blood by immunoassays.

Highly sensitive detection of melanoma based on serum proteomic profiling

PURPOSE

There is no available tumor marker that can detect primary melanoma. Proteomics analysis has been proposed as a novel tool that would lead to the discovery of potential new tumor markers.

METHODS

We developed a serum proteomic fingerprinting approach coupled with a classification method to determine whether proteomic profiling could discriminate between melanoma and healthy volunteers. A total of 108 serum samples from 30 early-stage [American Joint Committee on Cancer (AJCC) stage I or II] and 30 advanced-stage (AJCC stage III or IV) melanoma patients and 48 healthy volunteers were analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) utilizing protein chip technology and artificial neural networks.

RESULTS

In a first step, a multiprotein classifier was built using a training set of 30 pathologically confirmed melanoma and 24 healthy volunteer serum samples, resulting in good classification accuracy for correct diagnosis and stage classification assignment. Subsequently, our multiprotein classifier was tested in an independent validation set of 30 melanoma and 24 non-cancer serum samples patients, maintained in a good diagnostic accuracy of 98.1% (sensitivity 96.7%, specificity 100%), and 100% stage I/II classification assignment.

CONCLUSIONS

Although results remain to be confirmed in larger collective patient cohorts, we could demonstrate the usefulness of proteomic profiling as a sensitive and specific assay to detect melanoma, including non-metastatic melanoma, from the serum.

The measurement of serum ceruloplasmin is useful for diagnostic differentiation of immune thrombocytopenic purpura

BACKGROUND

To expand the criteria of immune thrombocytopenic purpura (ITP), which is a diagnosis of exclusion, we analyzed proteins separated by 1-dimensional gel electrophoresis of the retained fraction in a Con A-Sepharose column from ITP patients' sera.

METHODS

Serum samples were from 19 adult patients with chronic ITP, 9 patients with thrombocytopenia of decreased production, and 20 healthy controls. Samples were applied to a Con A-Sepharose column, and the retained fraction was subjected to 10% SDS-PAGE. The % area of each densitometric protein peak was compared between the two groups and proteins in each band were identified using LC-MS/MS.

RESULTS

Eleven protein bands were distinctly separated by 1-dimensional electrophoresis. The percent area of bands #2 and #3 were significantly higher in ITP patients than in controls. The percent area of band #2 (p<0.01) was significantly higher in ITP patients than in non-ITP patients. We identified alpha(2)-macroglobulin, ceruloplasmin (Cp), and C3 in band #2 and complement factor B in #3 band. Serum concentrations of alpha(2)-macroglobulin and Cp were significantly higher in ITP patients than in controls. Serum concentrations of Cp were significantly higher in ITP patients than in non-ITP patients (p=0.0005). Serum complement factor B concentrations were significantly higher in ITP patients and non-ITP patients than in controls. ROC analysis showed that the total percent area of bands #2 and #3, and Cp had higher diagnosis availability for ITP patients when compared with controls and non-ITP patients, respectively.

CONCLUSIONS

Measurement of Cp separated by the present method could be useful for the diagnosis of ITP in the presence of thrombocytopenia and a non- or low-inflammatory state.

Proteomics in cancer

Proteomic studies have generated numerous datasets of potential diagnostic, prognostic, and therapeutic significance in human cancer. Two key technologies underpinning these studies in cancer tissue are two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Although surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF)-MS is the mainstay for serum or plasma analysis, other methods including isotope-coded affinity tag technology, reverse-phase protein arrays, and antibody microarrays are emerging as alternative proteomic technologies. Because there is little overlap between studies conducted with these approaches, confirmation of these advanced technologies remains an elusive goal. This problem is further exacerbated by lack of uniform patient inclusion and exclusion criteria, low patient numbers, poor supporting clinical data, absence of standardized sample preparation, and limited analytical reproducibility (in particular of 2D-PAGE). Despite these problems, there is little doubt that the proteomic approach has the potential to identify novel diagnostic biomarkers in cancer. In therapeutic proteomics, the challenge is significant due to the complexity systems under investigation (i.e., cells generate over 10(5) different polypeptides). However, the most significant contribution of therapeutic proteomics research is expected to derive not from single experiments, but from the synthesis and comparison of large datasets obtained under different conditions (e.g., normal, inflammation, cancer) and in different tissues and organs. Thus, standardized processes for storing and retrieving data obtained with different technologies by different research groups will have to be developed. Shifting the emphasis of cancer proteomics from technology development and data generation to careful study design, data organization, formatting, and mining is crucial to answer clinical questions in cancer research.

Characterization of biomarkers in polycystic ovary syndrome (PCOS) using multiple distinct proteomic platforms

A variety of prefractionation methods (including a novel reversed-phase solid-phase-extraction (RP-SPE) combined with SDS-PAGE and proteomic based approaches (e.g., 2-dimensional gel electrophoresis (2DE) and MALDI-TOF mass spectrometry combined with Artificial Neural Network (ANN) bioinformatic tools) were used to investigate the protein/peptide signatures in patients with Polycystic Ovary Syndrome (PCOS). Four potential PCOS biomarkers were identified (complement C4alpha3c and C4gamma and haptoglobin alpha and beta chains).

A proteomic primer for the clinician

Proteomics is a rapidly developing field and it opens new horizons in many research areas of life sciences. In the field of medicine, proteomics promises to accelerate the discovery of new drug targets and protein disease markers useful for in vitro diagnosis. In this article, we review the current proteomics technologies for biomarker discovery and validation, which include two-dimensional gel electrophoresis, one- and two-dimensional liquid chromatography, and proteomic microarrays. We will also review proteomic strategies for protein-protein interactions and identification of post-translational modifications. Selection of the more effective technology or combination of technologies is required to maximize the interpretation and utility of the data.

Contributions of advanced proteomics technologies to cancer diagnosis

The ability of Medicine to effectively treat and cure cancer is directly dependent on their capability to detect cancers at their earliest stages. The advent of proteomics has brought with it the hope of discovering novel biomarkers in the early phases of tumorigenesis that can be used to diagnose diseases, predict susceptibility, and monitor progression. This discipline incorporates technologies that can be applied to complex biosystems such as serum and tissue in order to characterize the content of, and changes in, the proteome induced by physiological changes, benign or pathologic. These tools include 2-DE, 2D-DIGE, ICAT, protein arrays, MudPIT and mass spectrometries including SELDI-TOF. The application of these tools has assisted to uncover molecular mechanisms associated with cancer at the global level and may lead to new diagnostic tests and improvements in therapeutics. In this review these approaches are evaluated in the context of their contribution to cancer biomarker discovery. Particular attention is paid to the promising contribution of the ProteinChip/SELDI-TOF platform as a revolutionary approach in proteomic patterns analysis that can be applied at the bedside for discovering protein profiles that distinguish disease and disease-free states with high sensitivity and specificity. Understanding the basic concepts and tools used will illustrate how best to apply these technologies for patient benefit for the early cancer detection and improved patient care.

An ecotoxicoproteomic approach (SELDI-TOF mass spectrometry) to biomarker discovery in crab exposed to pollutants under laboratory conditions

Ciphergen ProteinChip Technology is a proteomic tool, used for the discovery of new and sensitive biomarkers. This approach was used to evaluate the protein profile of crabs exposed to various pollutants. Two different exposure experiments were performed: spider crabs (Hyas araneus) were exposed for 3 weeks to diallyl phatalate (DAP), bisphenol A (BisA) and polybrominated diphenyl ether (PBDE-47), while shore crabs (Carcinus maeanas) were exposed to crude oil, crude oil spiked with alkylphenols (APs) and 4-nonylphenol (NP). Gender and species-related protein pattern alterations were observed and compared to controls. Results showed different responses to pollutants by the two species. Major disruption in protein peak expression was observed in samples exposed to mixtures of pollutants, i.e. oil spiked with APs. Compared to shore crab, spider crab species showed a lower degree of response in terms of number of altered protein peaks following exposure. In general, female individuals of both species showed a larger number of significantly altered proteins compared to males. Data analysis by non-metric multi-dimensional scaling (MDS) was performed. Bi-dimesional-MDS plots revealed a good separation of groups for both spider and shore crabs. In some cases, a good discrimination can also be observed between the two genders within each treatment. Results highlight the potential of crabs as sentinel organisms for the aquatic environment. The results indicate that SELDI-ToF technology is a powerful tool to discover protein expression signatures for different pollutants and sex dependent responses.

Clinical proteomics: searching for better tumour markers with SELDI-TOF mass spectrometry

Recently, the focus of cancer research has expanded from genetic information in the human genome to protein expression analyses. Because this 'proteome' reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumour markers for disease diagnosis and therapy monitoring. Some current proteomic technologies are particularly suitable for protein profiling in the search for new biomarkers. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry has been used frequently, highlighting many new proteins as biomarkers (e.g. for ovarian, breast, prostate and colorectal cancer). However, it is becoming increasingly recognized that reproducibility and validation of these biomarkers should be addressed carefully, as should their origin and identity. If these efforts are made, protein profiling can contribute to the better diagnosis of patients and the optimization of their treatment.

Quantification of fragments of human serum inter-alpha-trypsin inhibitor heavy chain 4 by a surface-enhanced laser desorption/ionization-based immunoassay

BACKGROUND

Several proteolytically derived fragments from the proline-rich region (PRR) of human inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) have been identified by surface-enhanced or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS or MALDI-TOF-MS) as potential disease markers.

METHODS

Previously, we developed a SELDI-based immunoassay that can simultaneously distinguish and quantify multiple isoforms/variants of a protein/peptide of interest. In this study, we used this high-throughput approach to quantify and characterize the extensive fragmentation within the PRR of human serum ITIH4 and determined its association with different disease conditions. The ITIH4-related fragments were first immunocaptured by use of beads coupled with peptide-specific antibodies. The eluates were then studied by SELDI-TOF-MS. In addition, freshly collected and immediately processed serum and plasma samples were used to analyze the ex vivo stability of these ITIH4 fragments.

RESULTS

Human serum ITIH4 was shown to be extensively proteolytically processed within the PRR, and its fragmentation patterns were closely associated with different disease conditions. Fragmentation patterns were generally consistent with cleavages by endoprotease followed by exoprotease actions. Observed fragments changed little under different assay conditions or blood collection and processing procedures.

CONCLUSIONS

The fragmentation patterns within the PRR of human serum ITIH4 are associated with different disease conditions and may hold important diagnostic information. These fragmentation patterns could be useful as potential biomarkers for detection and classification of cancer.