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

A study of lymph node ratio as a prognostic marker in colon cancer

AIM

The aim of this study was to evaluate and describe the lymph node ratio (LNR) as a prognostic parameter for patients with colon cancer. As lymphatic involvement is the key, focus was set at stage III disease. Interest was directed at the possibility of identifying high-risk groups and the clinical implementation and consequence.

METHOD

The study was retrospective using a database of clinical data of all cancer patients treated at our unit. It has been continuous in registration, inclusion and update since 1999 including survival and clinical features. All patients (n=265) diagnosed with stage III colon cancer during 1999-2003 were included for the study. LNR was calculated and quartile groups were created. LNR and associated parameters were analysed towards 3-year disease-free survival (DFS). Basic patient data as well as surgery, pathology and postoperative treatment were taken into consideration.

RESULTS

Significant differences in disease-free survival were found for TNM N-status, tumour differentiation grade and LNR quartile group. There was a difference in 3-year DFS from 80% in LNR group 1 compared with less than 30% in group 4. These results were of prognostic interest both independently and in interaction with each other. High-risk groups could be identified and in the worst prognosis LNR group we also found a tendency towards more side effects with adjuvant chemotherapy.

CONCLUSION

The lymph node ratio, the quota between the number of lymph node metastasis and assessed lymph nodes, is a highly significant (p<0.001) prognostic factor in stage III colon cancer. It can be an aid in identifying risk groups that could benefit from a more intense postoperative surveillance and possibly bring changes in adjuvant treatment strategy. More studies of clinical data, genetic and biochemical markers are needed in this patient group to understand the possible difference in tumour behaviour and tailor the treatment.

Identification of serum biomarkers for nasopharyngeal carcinoma by proteomic analysis

BACKGROUND

Early diagnosis of nasopharyngeal carcinoma (NPC) remains a challenge. Serum protein profiling is a promising approach for the classification of cancer versus noncancer samples. The objective of the current study was to assess the feasibility of mass spectrometry-based protein profiling and a classification tree algorithm for discriminating between patients with NPC and noncancer controls.

METHODS

Serum samples from patients with NPC and noncancer controls were analyzed by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The study was divided into a preliminary training set and a blind test set: A preliminary training set and a classification tree of spectra derived from 55 patients with NPC and a group of 60 noncancer controls were used to develop a proteomic model that discriminated cancer from noncancer effectively. Then, the validity of the classification tree was challenged with a blind test set, which included another 25 patients with NPC and 28 noncancer controls.

RESULTS

Four protein peaks at 4097 daltons (Da), 4180 Da, 5912 Da, and 8295 Da were chosen automatically as a biomarker pattern in the training set that discriminated cancer from noncancer with sensitivity of 94.5% and specificity of 96.7%. When the SELDI marker pattern was tested with the blinded test set, it yielded a sensitivity of 92%, a specificity of 92.9%, and an accuracy rate of 92.5%. The accuracy of 2 protein peaks (4581 Da and 7802 Da) was 80% for predicting stage I and II NPC and 86% for predicting stage III and IV NPC.

CONCLUSIONS

The high sensitivity and specificity obtained by the serum protein profiling approach demonstrated that SELDI-TOF-MS combined with a tree analysis model both can facilitate discriminating between NPC and noncancer controls and can provide an innovative clinical diagnostic platform to improve the detection of NPC.

Blood markers for early detection of colorectal cancer: a systematic review

BACKGROUND

Despite different available methods for colorectal cancer (CRC) screening and their proven benefits, morbidity, and mortality of this malignancy are still high, partly due to low compliance with screening. Minimally invasive tests based on the analysis of blood specimens may overcome this problem. The purpose of this review was to give an overview of published studies on blood markers aimed at the early detection of CRC and to summarize their performance characteristics.

METHOD

The PUBMED database was searched for relevant studies published until June 2006. Only studies with more than 20 cases and more than 20 controls were included. Information on the markers under study, on the underlying study populations, and on performance characteristics was extracted. Special attention was given to performance characteristics by tumor stage.

RESULTS

Overall, 93 studies evaluating 70 different markers were included. Most studies were done on protein markers, but DNA markers and RNA markers were also investigated. Performance characteristics varied widely between different markers, but also between different studies using the same marker. Promising results were reported for some novel assays, e.g., assays based on SELDI-TOF MS or MALDI-TOF MS, for some proteins (e.g., soluble CD26 and bone sialoprotein) and also for some genetic assays (e.g., L6 mRNA), but evidence thus far is restricted to single studies with limited sample size and without further external validation.

CONCLUSIONS

Larger prospective studies using study populations representing a screening population are needed to verify promising results. In addition, future studies should pay increased attention to the potential of detecting precursor lesions.

New perspectives and strategy research biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. Cirrhosis caused by hepatitis B virus, hepatitis C virus or chronic alcohol intake is associated with major risk. Systematic screening for HCC of asymptomatic patients with cirrhosis is needed for earlier detection of small tumors requiring treatment (liver transplantation, surgical resection, percutaneous techniques). The recommended screening strategy among cirrhotic patients is based on regular liver ultrasonography associated with serum alpha-fetoprotein (AFP) assay. As the performance of AFP is not satisfactory, additional tumoral markers are proposed (des-gamma-carboxyprothrombin, glycosylated AFP-L3 fraction). Currently, diagnosis of HCC in cirrhotic patients includes non-invasive tests (imaging after contrast administration, AFP assay); diagnostic biopsy is performed when imaging is limited. After treatment, tumor recurrence is assessed by regular follow-up (AFP assay and imaging). Despite the lack of accurate markers, recent developments in genomic and proteomic approaches will allow the discovery of new biomarkers for primary tumors, as well as for recurrence. This review summarizes the current state of biomarkers for screening, diagnosis and follow-up of HCC, and highlights new perspectives in the field.

Recent Advances in Real-time Mass Spectrometry Detection of Bacteria

The analysis of bio-aerosols poses a technology challenge, particularly when sampling and analysis are done in situ. Mass spectrometry laboratory technology has been modified to achieve quick bacteria typing of aerosols in the field. Initially, aerosol material was collected and subjected off-line to minimum sample treatment and mass spectrometry analysis. More recently, sampling and analysis were combined in a single process for the real-time analysis of bio-aerosols in the field. This chapter discusses the development of technology for the mass spectrometry of bio-aerosols, with a focus on bacteria aerosols. Merits and drawbacks of the various technologies and their typing signatures are discussed. The chapter concludes with a brief view of future developments in bio-aerosol mass spectrometry.

Combining self-assembled monolayers and mass spectrometry for applications in biochips

Biochip arrays have enabled the massively parallel analysis of genomic DNA and hold great promise for application to the analysis of proteins, carbohydrates, and small molecules. Surface chemistry plays an intrinsic role in the preparation and analysis of biochips by providing functional groups for immobilization of ligands, providing an environment that maintains activity of the immobilized molecules, controlling nonspecific interactions of analytes with the surface, and enabling detection methods. This review describes recent advances in surface chemistry that enable quantitative assays of a broad range of biochemical activities. The discussion emphasizes the use of self-assembled monolayers of alkanethiolates on gold as a structurally well-defined and synthetically flexible platform for controlling the immobilization and activity of molecules in an array. The review also surveys recent methods of performing label-free assays, and emphasizes the use of matrix-assisted laser desorption/ionization mass spectrometry to directly observe molecules attached to the self-assembled monolayers.

Detection and significance of serum protein markers of small-cell lung cancer

Currently, no satisfactory biomarkers are available to screen for small-cell lung cancer (SCLC). We applied a surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) ProteinChip system to detect 150 serum samples (including 54 SCLC patients, 24 non-small cell lung cancer [NSCLC] patients, 32 pneumonia patients, and 40 healthy individuals). The spectra data were analyzed by support vector machine (SVM) and potential biomarkers were chosen for the system training and used to construct diagnostic model. Pattern 1, constructed of four protein peaks with mass/charge (m/z) of 4,293 Da, 4,612 Da, 6,455 Da, and 7,582 Da, separated SCLC patients from the healthy individuals with a sensitivity of 88.9% and a specificity of 85.7%. This pattern performed significantly better than the current marker, neuron-specific enolase (NSE) (P<0.05). Pattern 2, constructed of protein peaks with mass/charge (m/z) of 2,764 Da and 1,7368 Da, separated SCLC from pneumonia with a sensitivity of 88.9% and a specificity of 91.7%. Pattern 3, constructed of another three protein peaks with m/z of 3,912 Da, 7,562 Da, and 13,777 Da, separated SCLC from NSCLC. The sensitivity and specificity were 83.3% and 75.0%, respectively. These results suggested that SELDI-TOF MS combined with support vector machine yields significantly higher sensitivity and specificity for the detection of serum protein of SCLC.

Overview and introduction to clinical proteomics

As the field of clinical proteomics progresses, discovery of disease biomarkers becomes paramount. However, the immediate challenges are to establish standard operating procedures for both clinical specimen handling and reduction of sample complexity and to increase the ability to detect proteins and peptides present in low amounts. The traditional concept of a disease biomarker is shifting toward a new paradigm, namely, that an ensemble of proteins or peptides would be more efficient than a single protein/peptide in the diagnosis of disease. Because clinical proteomics usually requires easy access to well-defined fresh clinical specimens (including morphologically consistent tissue and properly pretreated body fluids of sufficient quantity), biorepository systems need to be established. Here, we address these questions and emphasize the necessity of developing various microdissection techniques for tissue specimens, multidimensional fractionation for body fluids, and other related techniques (including bioinformatics), tools which could become integral parts of clinical proteomics for disease biomarker discovery.

Mass spectrometry of self-assembled monolayers: a new tool for molecular surface science

Most reactions can be performed in solution and on a surface, yet the challenges faced in applying known reactions or in developing entirely new reactions for modifying surfaces remain formidable. The products of many reactions performed in solution can be characterized in minutes, and even products having complex structures can be characterized in hours. When performed on surfaces, even the most basic reactions require a substantial effort--requiring several weeks--to characterize the yields and structures of the products. This contrast stems from the lack of convenient analytical tools that provide rapid information on the structures of molecules attached to a surface. This review describes recent work that has established mass spectrometry as a powerful method for developing and characterizing a broad range of chemical reactions of molecules attached to self-assembled monolayers of alkanethiolates on gold. The SAMDI-TOF mass spectrometry technique will enable a next generation of applications of molecularly defined surfaces to problems in chemistry and biology.

A proteome resource of ovarian cancer ascites: integrated proteomic and bioinformatic analyses to identify putative biomarkers

Epithelial ovarian cancer is the most lethal gynecological malignancy, and disease-specific biomarkers are urgently needed to improve diagnosis, prognosis, and to predict and monitor treatment efficiency. We present an in-depth proteomic analysis of selected biochemical fractions of human ovarian cancer ascites, resulting in the stringent and confident identification of over 2500 proteins. Rigorous filter schemes were applied to objectively minimize the number of false-positive identifications, and we only report proteins with substantial peptide evidence. Integrated computational analysis of the ascites proteome combined with several recently published proteomic data sets of human plasma, urine, 59 ovarian cancer related microarray data sets, and protein-protein interactions from the Interologous Interaction Database I (2)D ( http://ophid.utoronto.ca/i2d) resulted in a short-list of 80 putative biomarkers. The presented proteomics analysis provides a significant resource for ovarian cancer research, and a framework for biomarker discovery.

Differences in protein profiles of the isolates of Entamoeba histolytica and E. dispar by surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS) ProteinChip assays

Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) ProteinChip assays with weak cationic exchange chips were used for protein profiling of different isolates of Entamoeba histolytica and E. dispar. When SELDI-TOF MS spectra of cell lysates from E. histolytica strain HM-1:IMSS were compared with those from four other laboratory strains (200:NIH, HK-9, DKB, and SAW755CR) grown under the same culture conditions, different peak patterns of SELDI-TOF MS were observed among these strains, independent of their zymodeme types. Similarly, five Japanese isolates of E. histolytica grown under the same culture conditions revealed different peak patterns among themselves. The SELDI-TOF MS spectra of cell lysates from two isolates of E. dispar strain AS16IR and CYNO 09:TPC showed the presence of peaks specific for E. dispar isolates and the absence of peaks common to E. histolytica isolates. This is not only the first use of SELDI-TOF MS ProteinChip technology for protein profiling of different strains of Entamoeba but also the use for parasitic protozoa. The SELDI-TOF MS spectra show a realistic view of proteins with a biological status of E. histolytica and E. dispar isolates, contributing to show their phenotypic differences of proteins and provide a unique means of distinguishing them.

Moving forward in colorectal cancer research, what proteomics has to tell

Colorectal cancer is the third most common cancer and is highly fatal. During the last several years, research has been primarily based on the study of expression profiles using microarray technology. But now, investigators are putting into practice proteomic analyses of cancer tissues and cells to identify new diagnostic or therapeutic biomarkers for this cancer. Because the proteome reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumor markers for disease diagnosis and therapy monitoring. This review summarizes the most relevant applications of proteomics the biomarker discovery for colorectal cancer.

Novel translational strategies in colorectal cancer research

Defining translational research is still a complex task. In oncology, translational research implies using our basic knowledge learnt from in vitro and in vivo experiments to directly improve diagnostic tools and therapeutic approaches in cancer patients. Moreover, the better understanding of human cancer and its use to design more reliable tumor models and more accurate experimental systems also has to be considered a good example of translational research. The identification and characterization of new molecular markers and the discovery of novel targeted therapies are two main goals in colorectal cancer translational research. However, the straightforward translation of basic research findings, specifically into colorectal cancer treatment and vice versa is still underway. In the present paper, a summarized view of some of the new available approaches on colorectal cancer translational research is provided. Pros and cons are discussed for every approach exposed.

Microdissecting the proteome

The complexity of the proteome is extremely high, because every organ or even a part of it can differ considerably in its protein composition. Performing proteomic studies therefore means to separate these functional different tissue areas before analysis. Otherwise all gained results will be depending on the question whether they are incorrect or at least dubious and do they reflect the different functions of tissues at all. The separation of functional tissue areas can be achieved by laser-based microdissection. In this review we will discuss the compatibly of microdissected formalin or cryofixed tissue with different proteomic techniques like 2-DE, MS and protein arrays.

Protein expression profiling reveals distinctive changes in serum proteins associated with chronic pancreatitis

OBJECTIVE

Testing of serum for protein patterns to monitor progression of suspected to definite chronic pancreatitis (CP).

METHODS

Serum samples of CP patients and healthy volunteers were fractionated on anion exchange columns and analyzed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry to elucidate CP-related protein alterations and to identify biomarkers for this disease. Potential biomarkers were purified and identified by mass spectrometry.

RESULTS

In total, 258 protein peaks were found that discriminated between the 2 groups. Analysis revealed 28 most prominent peaks on immobilized metal affinity capture coupled with Cu and CM10 protein chips, covering the m/z range between 3.3 and 33.3 kd. Performing multivariate pattern analysis, the best pattern model was obtained using fraction 6 on immobilized metal affinity capture coupled with Cu arrays with a sensitivity of 96% and a specificity of 84%. Using a combination of matrix-assisted laser desorption-ionization-time-of-flight mass spectrometry and immunodepletion, we identified 14-m/z peaks. The proteins were found to be significantly decreased in CP serum and were identified as retinol-binding protein, serum amyloid-alpha, apolipoprotein A-II (Apo A-II), Apo C-I, Apo C-II, Apo C-III, and transthyretin and truncated forms thereof.

CONCLUSIONS

Distinct protein profile differences exist between normal and CP serum and reflect the metabolic and inflammatory condition in CP patients. The identified protein panel may eventually serve as a diagnostic marker set for CP.

Searching for novel biomarkers of centrally and peripehrally-acting neurotoxicants, using surface-enhanced laser desorption/ionisation-time-of-flight mass spectrometry (SELDI-TOF MS)

The neurotoxicity of chemicals to humans is difficult to monitor as there are no suitable methods of detecting early neuronal dysfunction. Here, a proof of principle study was designed to assess the potential of identifying protein biomarkers in accessible biofluids for this purpose. Groups of rats were treated with a range of doses of the model neurotoxicants, acrylamide (0, 2, 10, 50mg/kg) and methylmercury (0, 0.2, 1, 5mg/kg) for up to 3 weeks and samples of serum, urine, and cerebral spinal fluid analysed by surface-enhanced laser desorption/ionisation-time-of-flight mass spectrometry. There was no neuropathology up to the highest dose tested. Protein profiles were obtained from all samples and changes in the levels of many proteins were detected in both serum and urine, although not cerebral spinal fluid. In serum, the combination of three protein ion levels with m/z values of 4968, 9402 and 12,948 was able to correctly classify the treatment groups thus: 88% control, 100% acrylamide, 92% methylmercury. In urine, three protein ions with m/z values of 4944, 12,966 and 21,992 classified correctly the groups: 67% control, 94% acrylamide, 97% methylmercury. Similar classifications using other serum and urinary protein ions were also possible. This indicates the potential of serum and urine protein biomarkers for the assessment of sub-clinical neurotoxicity.

Specific MALDI imaging and profiling for biomarker hunting and validation: fragment of the 11S proteasome activator complex, Reg alpha fragment, is a new potential ovary cancer biomarker

MALDI imaging mass spectrometry represents a new analytical tool to directly provide the spatial distribution and relative abundance of proteins in tissue. Twenty-five ovary carcinomas (stages III and IV) and 23 benign ovaries were directly analyzed using MALDI-TOF MS. The biomarker with the major prevalence (80%) has been fully identified using MALDI MS and nanoESI MS and MS/MS after separation by RP-HPLC and trypsin enzymatic digestion. This marker with an m/z of 9744 corresponds to 84 amino acid residues from the 11S proteasome activator complex, named PA28 or Reg-alpha. Validation of this marker has been performed using MALDI imaging, classical immunocytochemistry with an antibody raised against the C-terminal part of the protein, specific MALDI imaging, and Western blot analysis. The validation, using immunocytochemistry, confirmed the epithelial localization of this fragment with nucleus localization in benign epithelial cells and a cytoplasmic localization in carcinoma cells. This indicates that this antibody could be used to discriminate the borderline tumor cases. At this point, a multicentric study needs to be conducted in order to clearly establish the potential of this biomarker. Taken together these studies reflect that direct tissue analysis and specific MALDI imaging strategies facilitate biomarker hunting and validation which can be named pathological proteomics.

Use of multidimensional separation protocols for the purification of trace components in complex biological samples for proteomics analysis

The routine detection of low abundance components in complex samples for detailed proteomics analysis continues to be a challenge. Whilst the potential of multidimensional chromatographic fractionation for this purpose has been proposed for some years, and was used effectively for the purification to homogeneity of trace components in bulk biological samples for N-terminal sequence analysis, its practical application in the proteomics arena is still limited. This article reviews some of the recent data using these approaches, including the use of microaffinity purification as part of multidimensional protocols for downstream proteomics analysis.

Biomarker method validation in anticancer drug development

Over recent years the role of biomarkers in anticancer drug development has expanded across a spectrum of applications ranging from research tool during early discovery to surrogate endpoint in the clinic. However, in Europe when biomarker measurements are performed on samples collected from subjects entered into clinical trials of new investigational agents, laboratories conducting these analyses become subject to the Clinical Trials Regulations. While these regulations are not specific in their requirements of research laboratories, quality assurance and in particular assay validation are essential. This review, therefore, focuses on a discussion of current thinking in biomarker assay validation. Five categories define the majority of biomarker assays from 'absolute quantitation' to 'categorical'. Validation must therefore take account of both the position of the biomarker in the spectrum towards clinical end point and the level of quantitation inherent in the methodology. Biomarker assay validation should be performed ideally in stages on 'a fit for purpose' basis avoiding unnecessarily dogmatic adherence to rigid guidelines but with careful monitoring of progress at the end of each stage. These principles are illustrated with two specific examples: (a) absolute quantitation of protein biomarkers by mass spectrometry and (b) the M30 and M65 ELISA assays as surrogate end points of cell death.

The ongoing evolution of proteomics in malignancy

The complementary fields of genomics and proteomics offer insights into the molecular mechanisms of diseases. While genomics seeks to define our genetic substrate, proteomics explores the structure and function of proteins, which are the end effectors of our genes. Proteomics has been revolutionized in the past decade by the application of techniques such as protein arrays, two-dimensional gel electrophoresis, and mass spectrometry. These techniques have tremendous potential for biomarker development, target validation, diagnosis, prognosis, and optimization of treatment in medical care, especially in the field of clinical oncology. We will discuss innovations in proteomic technologies and highlight their prospective applications to patient care.

Proteomics in clinical prostate research

The incidence of early prostate cancer (PCa) has increased rapidly in recent years. The majority of newly diagnosed PCa are in early tumor phase. Presently, we do not have adequate biomarkers to assess tumor aggressiveness in individual cases. Consequently, too many patients are given curatively intended treatment. An exploration of the human proteome may provide clinically useful markers. 2-DE has been successfully used for analysis of the protein phenotype using clinical samples. Proteins are separated according to size and charge, gels are compared by image analysis, protein spots of interest are excised, and proteins identified by MS. This method is exploratory and allows protein identification. However, low-abundance proteins are difficult to detect and 2-DE is currently too labor-intensive for routine use. In recent years, nongel based techniques, such as LC-MS, SELDI-MS, and protein arrays have emerged. They require smaller sample sizes and can be more automated than 2-DE. In this review, we describe studies of the protein expression of benign prostatic tissue and PCa, which is likely to serve as the first step in prognostic biomarker discovery. The prostate proteome is still far from a complete mapping which would enhance our understanding of PCa biology.

Serum proteomic profiling of dementia with Lewy bodies: diagnostic potential of SELDI-TOF MS analysis

Dementia with Lewy bodies (DLB) is the second most common senile degenerative dementia after Alzheimer's disease (AD). The presentation of overlapping symptoms between these two disorders leads to difficulties in the determination of clinical entities. Serum samples were subjected to surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) analysis in order to identify a diagnostic marker for DLB. Four putative protein peaks (m/z 3,883, 4,964, 7,761 and 10,534) were differentially expressed in DLB patients compared to AD patients and control subjects. Receiver operating characteristics (ROC) analysis of a multivariate logistic model of the combination of three peaks (m/z 3,883, 7,761 and 10,534) exhibited the highest discriminatory ability of DLB subjects from non-DLB subjects with a sensitivity of 83.3%, a specificity of 95.8%, a positive predictive value of 90.9% and a negative predictive value of 92.0%. SELDI-TOF MS profiling, therefore, has revealed a serum signature with high diagnostic potential for DLB.

Application of proteomic technologies to discover and identify biomarkers for excessive alcohol consumption: A review

Since currently available markers of alcohol abuse are not satisfactory, searches for novel markers are warranted. Proteomic analyses are promising tools to discover and identify novel biomarkers. Using two different proteomic technologies, surface enhanced laser desorption/ionization time-of-flight mass spectrometry and agarose fluorescent two-dimensional difference gel electrophoresis, we could detect and identify a total of 11 potential biomarkers of excessive alcohol consumption. It was noteworthy that the down regulation of the 5.9 kDa protein fragment was consistently seen in habitual drinkers and the diagnostic efficiency was greater than those of conventional markers such as gamma glutamyl transferase and carbohydrate deficient transferrin.

Self-assembled monolayers for MALDI-TOF mass spectrometry for immunoassays of human protein antigens

This paper reports a method that combines self-assembled monolayers with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to perform immunoassays on clinical samples. The immunosensors are prepared by immobilizing His-tagged protein G (or A) to a monolayer presenting the Ni2+ chelates, followed by immobilization of IgG antibodies with specificity for the intended analyte. The SAMDI mass spectrometry technique confirms the presence of the two proteins on the immunosensor and additionally provides a label-free analysis of antigens that bind to the sensor. This paper reports examples of detecting several proteins from human serum, including multianalyte assays that resolve each analyte according to their mass-to-charge ratio in the SAMDI spectra. An example is described wherein SAMDI is used to identify a proteolytic fragment of cystatin C in cerebral spinal fluids from patients diagnosed with multiple sclerosis. The SAMDI-TOF immunoassay, which combines well-defined surface chemistries for the selective and reproducible localization of analytes with mass spectrometry for label-free detection of analytes, may offer an alternative methodology to address many of the issues associated with standardized clinical diagnostics.

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.

What does it need to be a biomarker? Relationships between resolution, differential quantification and statistical validation of protein surrogate biomarkers

The separation of proteins with the aim of discovering surrogate biomarkers defining differences between various stages of biological materials is the core occupation of every project in Proteomics. There are numerous recent publications suggesting a wide array of separation technologies, ranging from 2-DE, MS-linked LC, CE or chip-based surface-enhanced laser desorption ionization claiming to be useful for this purpose, and addressing the urgent clinical, diagnostic or toxicological needs for such surrogates. However, many potential biomarkers emerging from proteomic studies did not survive validation in, for example, large-scale clinical studies or simply independent experiments, and at the same time being tested in settings with case numbers bigger than perhaps a few hundreds. The major problems of protein biomarkers are associated with the huge dynamic range of possible concentrations and the ever-increasing number of molecular species due to post-translational modifications. In particular, the chemical diversity of the latter imposes a necessity of improved resolution of separation technologies, because otherwise the crucial quantitative information is lost in pools of poorly resolved peptides. Here, we present and analyze some examples of successful developments of protein biomarkers, and show the prerequisites and necessary considerations while moving protein candidates from purely descriptive phenomena to a stage of validated surrogate biomarkers. This includes a detailed discussion of requirements regarding resolution of initial separation techniques, linear dynamic range and statistics of differential quantification, but also the subsequent clinical validation, testing the biomarker in clinical settings and using large numbers of patient samples.

Mass spectrometry for enzyme assays and inhibitor screening: an emerging application in pharmaceutical research

Robust methods that monitor enzyme activity and inhibitor potency are crucial to drug discovery and development. Over the past 20 years, mass spectrometric methods have increasingly been used to measure enzyme activity and kinetics. However, for rapid screening of inhibitory compounds, various forms of fluorescence and chemiluminscence readout have continued to dominate the market. As the sensitivity, speed, and miniaturization of mass spectrometry methods continue to advance, opportunities to couple mass spectrometry with screening will continue to come to the forefront. To appreciate the tremendous potential for MS-based screening assays, it becomes necessary to understand the current state of capabilities in this arena. Thus, this review is intended to capture how mass spectrometry for studying enzymes activity has progressed from simple qualitative questions (i.e., is the product detected?) to quantitative measures of enzyme activity and kinetics and then as a tool for rapidly screening inhibitory compounds as an alternative to current methods of high throughput drug screening.

SELDI-TOF-MS analysis of chloroquine resistant and sensitivePlasmodium falciparum strains

The resistance of the malarial parasite Plasmodium falciparum to chloroquine represents an emerging problem since neither mode of drug action nor mechanisms of resistance are fully elucidated. We describe a protein expression profiling approach by SELDI-TOF-MS as a useful tool for studying the proteome of malarial parasites. Reproducible and complex protein profiles of the P. falciparum strains K1, Dd2, HB3 and 3D7 were measured on four array types. Hierarchical clustering led to a clear separation of the two major subgroups "resistant" and "sensitive" as well as of the four parasite strains. Our study delivers sets of regulated proteins derived from extensive comparative analyses of 64 P. falciparum protein profiles. A group of 12 peaks reflecting proteome changes under chloroquine treatment and a set of 10 potential chloroquine resistance markers were defined. Three of these regulated peaks were preparatively enriched, purified and identified. They were shown to represent the plasmodial EXP-1 protein, also called circumsporozoite-related antigen, as well as the alpha- and beta- (delta-) chains of human hemoglobin.

Identification of potential markers for the detection of pancreatic cancer through comparative serum protein expression profiling

OBJECTIVE

Early detection is the only promising approach to significantly improve the survival of patients with pancreatic cancer (PCa). Noninvasive tools for the diagnosis, prognosis, and monitoring of this disease are of urgent need. The purpose of this study was to identify and validate new biomarkers in PCa patient serum samples.

METHODS

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry has been applied to analyze serum protein alterations associated with PCa and to identify sets of potential biomarkers indicative for this disease. A cohort of 96 serum samples from patients undergoing PCa surgery was compared with sera from 96 healthy volunteers as controls. The sera were fractionated by anion exchange chromatography, and 3 of 6 fractions were analyzed onto 2 different chromatographic arrays.

RESULTS

Data analysis revealed 24 differentially expressed protein peaks (P < 0.001), of which 21 were downregulated in the PCa samples. The best single marker can predict 92% of the controls and 89% of the cancer samples correctly. In addition, multivariate pattern analysis was performed. The best pattern model using a set of 3 markers was obtained using fraction 6 on immobilized metal affinity capture, loaded with Cu-Cu arrays. With this pattern model, a sensitivity of 100% and a specificity of 98% for the training data set and a sensitivity of 83% and specificity of 77% for the test data set were achieved with the PCa group set as true positive. Several of protein peaks, including the best single marker at 17.27 kd and other proteins from the pattern models, were purified and identified by peptide mapping and postsource decay-matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Apolipoprotein A-II, transthyretin, and apolipoprotein A-I were identified as markers, and these identified proteins were decreased at least 2-fold in PCa serum when compared with the control group.

CONCLUSIONS

PCa is associated with a specific decrease of distinct serum proteins, which allows a reliable differentiation between pancreatic cancer and healthy controls.

Preanalytic influence of sample handling on SELDI-TOF serum protein profiles

BACKGROUND

High-throughput proteomic methods for disease biomarker discovery in human serum are promising, but concerns exist regarding reproducibility of results and variability introduced by sample handling. This study investigated the influence of different preanalytic handling methods on surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) protein profiles of prefractionated serum. We investigated whether older collections with longer sample transit times yield useful protein profiles, and sought to establish the most feasible collection methods for future clinical proteomic studies.

METHODS

To examine the effect of tube type, clotting time, transport/incubation time, temperature, and storage method on protein profiles, we used 6 different handling methods to collect sera from 25 healthy volunteers. We used a high-throughput, prefractionation strategy to generate anion-exchange fractions and examined their protein profiles on CM10, IMAC30-Cu, and H50 arrays by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.

RESULTS

Prolonged transport and incubation at room temperature generated low mass peaks, resulting in distinctions among the protocols. The most and least stringent methods gave the lowest overall peak variances, indicating that proteolysis in the latter may have been nearly complete. For samples transported on ice there was little effect of clotting time, storage method, or transit time. Certain proteins (TTR, ApoCI, and transferrin) were unaffected by handling, but others (ITIH4 and hemoglobin beta) displayed significant variability.

CONCLUSIONS

Changes in preanalytical handling variables affect profiles of serum proteins, including proposed disease biomarkers. Proteomic analysis of samples from serum banks collected using less stringent protocols is applicable if all samples are handled identically.

Recent advances in capillary electrophoresis for biomarker discovery

The use of non-invasive methods for detecting biomarkers opens a new era in patient care, since clinical investigators have long been searching for accurate and reproducible measurements of putative biomarkers. There are many factors which make this research challenging, beginning with lack of standardization of sample collection and continuing through the entire analytical procedure. Among the variety of methods so far used for biomarker screening, capillary electrophoresis represents a robust, reliable, and widely used analytical tool. This review will focus on recent applications of CE to the analysis of body fluids and tissues for identification of biomarkers.

Mass spectrometry-based immunoassays for the next phase of clinical applications

Recent applications of affinity mass spectrometry into clinical laboratories brought a renewed interest in immunoaffinity mass spectrometry as a more specific affinity method capable of selectively targeting and studying protein biomarkers. In mass spectrometry-based immunoassays, proteins are affinity retrieved from biological samples via surface-immobilized antibodies, and are then detected via mass spectrometric analysis. The assays benefit from dual specificity, which is brought about by the affinity of the antibody and the protein mass readout. The mass spectrometry aspect of the assays enables single-step detection of protein isoforms and their individual quantification. This review offers a comprehensive review of mass spectrometry-based immunoassays, from historical perspectives in the development of the immunoaffinity mass spectrometry, to current applications of the assays in clinical and population proteomic endeavors. Described in more detail are two types of mass spectrometry-based immunoassays, one of which incorporates surface plasmon resonance detection for protein quantification. All mass spectrometry-based immunoassays offer high-throughput targeted protein investigation, with clear implications in clinical research, encompassing biomarker discovery and validation, and in diagnostic settings as the next-generation immunoassays.

Achieving in-depth proteomics profiling by mass spectrometry

Proteomics addresses the important goal of determining the chemistry and composition of proteins in biological samples. Mass-spectrometry-based strategies have been highly successful in identifying and profiling proteins in complex mixtures; however, although depth of sampling continues to improve, a general recognition exists that no study has yet achieved complete protein coverage in any tissue, cell type, subcellular component, or fluid. The development of new approaches for comprehensively surveying highly complex protein mixtures, distinguishing protein isoforms, quantifying changes in protein abundance between different samples, and mapping post-translational modifications are areas of active research. These will be needed to achieve the "systems-wide" protein profiling goals of defining molecular responses to cell perturbations and obtaining biomarker information for disease detection, prognosis, and responses to therapy. We review recent progress in approaching these problems and present examples of successful applications and the outlook for the future.

High-throughput screening of packed-bed chromatography coupled with SELDI-TOF MS analysis: monoclonal antibodies versus host cell protein

A feasibility study to couple high throughput screening of packed bed chromatography with mass spectrometric detection by SELDI-TOF MS is presented. As model system monoclonal antibodies (mAb) versus host cell protein (HCP) from an industrial cultivation was chosen. Packed bed chromatography was screened on a TECAN Evo Freedom 200 station using miniaturized chromatographic columns placed on a specially designed array carrier linked to a commercially available T-Stack module. Gradient elution of the bound proteins was performed by applying a multiple step strategy. When analyzing selected HCP peaks as well as the detected antibody peaks throughout the chromatographic runs a direct correlation between applied and detected components was established. The sensitivity of conventional protein A chromatography was found to be lower than SELDI-TOF MS analysis. During initial screening a shift in the elution pattern for one of the monoclonal antibodies detected with all four resins was identified to be a heterogeneity in the mAb glycosylation pattern. In addition, a detailed differentiation between various HCP fractions through out the chromatographic process using SELDI-TOF analysis let to the detection of HCP components possibly adhering to the mAbs during chromatographic separations.

Display technologies: application for the discovery of drug and gene delivery agents

Recognition of molecular diversity of cell surface proteomes in disease is essential for the development of targeted therapies. Progress in targeted therapeutics requires establishing effective approaches for high-throughput identification of agents specific for clinically relevant cell surface markers. Over the past decade, a number of platform strategies have been developed to screen polypeptide libraries for ligands targeting receptors selectively expressed in the context of various cell surface proteomes. Streamlined procedures for identification of ligand-receptor pairs that could serve as targets in disease diagnosis, profiling, imaging and therapy have relied on the display technologies, in which polypeptides with desired binding profiles can be serially selected, in a process called biopanning, based on their physical linkage with the encoding nucleic acid. These technologies include virus/phage display, cell display, ribosomal display, mRNA display and covalent DNA display (CDT), with phage display being by far the most utilized. The scope of this review is the recent advancements in the display technologies with a particular emphasis on molecular mapping of cell surface proteomes with peptide phage display. Prospective applications of targeted compounds derived from display libraries in the discovery of targeted drugs and gene therapy vectors are discussed.

Proteomics in human cancer research

Proteomics is now widely employed in the study of cancer. Many laboratories are applying the rapidly emerging technologies to elucidate the underlying mechanisms associated with cancer development, progression, and severity in addition to developing drugs and identifying patients who will benefit most from molecular targeted compounds. Various proteomic approaches are now available for protein separation and identification, and for characterization of the function and structure of candidate proteins. In spite of significant challenges that still exist, proteomics has rapidly expanded to include the discovery of novel biomarkers for early detection, diagnosis and prognostication (clinical application), and for the identification of novel drug targets (pharmaceutical application). To achieve these goals, several innovative technologies including 2-D-difference gel electrophoresis, SELDI, multidimensional protein identification technology, isotope-coded affinity tag, solid-state and suspension protein array technologies, X-ray crystallography, NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulation have evolved, and are being used in different combinations. This review provides an overview of the field of proteomics and discusses the key proteomic technologies available to researchers. It also describes some of the important challenges and highlights the current pharmaceutical and clinical applications of proteomics in human cancer research.

Proteomics in clinical trials and practice: present uses and future promise

The study of clinical proteomics is a promising new field that has the potential to have many applications, including the identification of biomarkers and monitoring of disease, especially in the field of oncology. Expression proteomics evaluates the cellular production of proteins encoded by a particular gene and exploits the differential expression and post-translational modifications of proteins between healthy and diseased states. These biomarkers may be applied towards early diagnosis, prognosis, and prediction of response to therapy. Functional proteomics seeks to decipher protein-protein interactions and biochemical pathways involved in disease biology and targeted by newer molecular therapeutics. Advanced spectrometry technologies and new protein array formats have improved these analyses and are now being applied prospectively in clinical trials. Further advancement of proteomics technology could usher in an era of personalized molecular medicine, where diseases are diagnosed at earlier stages and where therapies are more effective because they are tailored to the protein expression of a patient's malignancy.