Overview and introduction to clinical proteomics

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Hypoplastic left heart syndrome: From bedside to bench and back

Hypoplastic Left Heart Syndrome (HLHS) is a complex Congenital Heart Disease (CHD) that was almost universally fatal until the advent of the Norwood operation in 1981. Children with HLHS who largely succumbed to the disease within the first year of life, are now surviving to adulthood. However, this survival is associated with multiple comorbidities and HLHS infants have a higher mortality rate as compared to other non-HLHS single ventricle patients. In this review we (a) discuss current clinical challenges associated in the care of HLHS patients, (b) explore the use of systems biology in understanding the molecular framework of this disease, (c) evaluate induced pluripotent stem cells as a translational model to understand molecular mechanisms and manipulate them to improve outcomes, and (d) investigate cell therapy, gene therapy, and tissue engineering as a potential tool to regenerate hypoplastic cardiac structures and improve outcomes.

Applications of MALDI-TOF mass spectrometry in clinical proteomics

INTRODUCTION

The development of precision medicine requires advanced technologies to address the multifactorial disease stratification and to support personalized treatments. Among omics techniques, proteomics based on Mass Spectrometry (MS) is becoming increasingly relevant in clinical practice allowing a phenotypic characterization of the dynamic functional status of the organism. From this perspective, Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) MS is a suitable platform for providing a high-throughput support to clinics. Areas covered: This review aims to provide an updated overview of MALDI-TOF MS applications in clinical proteomics. The most relevant features of this analysis have been discussed, highlighting both pre-analytical and analytical factors that are crucial in proteomics studies. Particular emphasis is placed on biofluids proteomics for biomarkers discovery and on recent progresses in clinical microbiology, drug monitoring, and minimal residual disease (MRD). Expert commentary: Despite some analytical limitations, the latest technological advances together with the easiness of use, the low time and low cost consuming and the high throughput are making MALDI-TOF MS instruments very attractive for the clinical practice. These features offer a significant potential for the routine of the clinical laboratory and ultimately for personalized medicine.

Stathmin decreases cholangiocarcinoma cell line sensitivity to staurosporine-triggered apoptosis via the induction of ERK and Akt signaling

Cholangiocarcinoma is a rare, but highly fatal malignancy. However, the intrinsic mechanism involved in its tumorigenesis remains obscure. An urgent need remains for a promising target for cholangiocarcinoma biological therapies. Based on comparative proteomical technologies, we found 253 and 231 different spots in gallbladder tumor cell lines and cholangiocarcinoma cell lines, respectively, relative to non-malignant cells. Using Mass Spectrometry (MS) and database searching, we chose seven differentially expressed proteins. High Stathmin expression was found in both cholangiocarcinoma and gallbladder carcinoma cells. Stathmin expression was validated using immunohistochemistry and western blot in cholangiocarcinoma tissue samples and peritumoral tissue. It was further revealed that high Stathmin expression was associated with the repression of staurosporine-induced apoptosis in the cholangiocarcinoma cell. Moreover, we found that Stathmin promoted cancer cell proliferation and inhibited its apoptosis through protein kinase B (Akt) and extracellular signal-regulated kinase (ERK) signaling. Integrin, β1 appears to serve as a partner of Stathmin induction of ERK and Akt signaling by inhibiting apoptosis in the cholangiocarcinoma cell. Understanding the regulation of anti-apoptosis effect by Stathmin might provide new insight into how to overcome therapeutic resistance in cholangiocarcinoma.

Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

Organic acidemias (OAs) are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA), neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS-) based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs.

Identification of human complement factor B as a novel biomarker candidate for pancreatic ductal adenocarcinoma

Pancreatic cancer (PC; pancreatic ductal adenocarcinoma) is characterized by significant morbidity and mortality worldwide. Although carbohydrate antigen (CA) 19-9 has been known as a PC biomarker, it is not commonly used for general screening because of its low sensitivity and specificity. Therefore, there is an urgent need to develop a new biomarker for PC diagnosis in the earlier stage of cancer. To search for a novel serologic PC biomarker, we carried out an integrated proteomic analysis for a total of 185 pooled or individual plasma from healthy donors and patients with five disease groups including chronic pancreatitis (CP), PC, and other cancers (e.g., hepatocellular carcinoma, cholangiocarcinoma, and gastric cancer) and identified complement factor b (CFB) as a candidate serologic biomarker for PC diagnosis. Immunoblot analysis of CFB revealed more than two times higher expression in plasma samples from PC patients compared with plasma from individuals without PC. Immunoprecipitation coupled to mass spectrometry analysis confirmed both molecular identity and higher expression of CFB in PC samples. CFB showed distinctly higher specificity than CA 19-9 for PC against other types of digestive cancers and in discriminating PC patients from non-PC patients (p < 0.0001). In receiver operator characteristic curve analysis, CFB showed an area under curve of 0.958 (95% CI: 0.956 to 0.959) compared with 0.833 (95% CI: 0.829 to 0.837) for CA 19-9. Furthermore, the Y-index of CFB was much higher than that of CA 19-9 (71.0 vs 50.4), suggesting that CFB outperforms CA 19-9 in discriminating PC from CP and other gastrointestinal cancers. This was further supported by immunoprecipitation and qRT-PCR assays showing higher expression of CFB in PC cell lines than in normal cell lines. A combination of CFB and CA 19-9 showed markedly improved sensitivity (90.1 vs 73.1%) over that of CFB alone in the diagnosis of PC against non-PC, with similar specificity (97.2 vs 97.9%). Thus, our results identify CFB as a novel serologic PC biomarker candidate and warrant further investigation into a large-scale validation and its role in molecular mechanism of pancreatic carcinogenesis.

PanelComposer: a web-based panel construction tool for multivariate analysis of disease biomarker candidates

Measuring and evaluating diagnostic efficiency is important in biomarker discovery and validation. The receiver operating characteristic (ROC) curve is a graphical plot for assessing the performance of a classifier or predictor that can be used to test the sensitivity and specificity of diagnostic biomarkers. In this study, we describe PanelComposer, a Web-based software tool that uses statistical results from proteomic expression data and validates biomarker candidates based on ROC curves and the area under the ROC curve (AUC) values using a logistic regression model and provides an ordered list that includes ROC graphs and AUC values for proteins (individually or in combination). This tool allows users to easily compare and assess the effectiveness and diagnostic efficiency of single or multiprotein biomarker candidates. PanelComposer is available publicly at http://panelcomposer.proteomix.org/ and is compatible with major Web browsers.

Proteomic analysis of formalin-fixed paraffin-embedded pancreatic tissue using liquid chromatography tandem mass spectrometry

OBJECTIVES

FFPE tissue is a standard method of specimen preservation for hospital pathology departments. Formalin-fixed paraffin-embedded tissue banks are a resource of histologically characterized specimens for retrospective biomarker investigation. We aim to establish liquid chromatography coupled with tandem mass spectrometry analysis of FFPE pancreatic tissue as a suitable strategy for the study of the pancreas proteome.

METHODS

We investigated the proteomic profile of FFPE pancreatic tissue specimens, using liquid chromatography coupled with tandem mass spectrometry, from 9 archived specimens that were histologically classified as normal (n = 3), chronic pancreatitis (n = 3), and pancreatic cancer (n = 3).

RESULTS

We identified 525 nonredundant proteins from 9 specimens. Implementing our filtering criteria, 78, 15, and 21 proteins were identified exclusively in normal, chronic pancreatitis, and pancreatic cancer specimens, respectively. Several proteins were identified exclusively in specimens with no pancreatic disease: spink 1, retinol dehydrogenase, and common pancreatic enzymes. Similarly, proteins were identified exclusively in chronic pancreatitis specimens: collagen α1 (XIV), filamin A, collagen α3 (VI), and SNC73. Proteins identified exclusively in pancreatic cancer included annexin 4A and fibronectin.

CONCLUSIONS

We report that differentially expressed proteins can be identified among FFPE tissue specimens originating from individuals with different pancreatic histologic findings. The mass spectrometry-based method used herein has the potential to enhance biomarker discovery and chronic pancreatitis research.

Differential gel-based proteomic approach for cancer biomarker discovery using human plasma

Two-dimensional fluorescence difference gel electrophoresis (2D DIGE) has become a general platform for analysis of various clinical samples such as biofluids and tissues. In comparison to conventional 2-D polyacrylamide gel electrophoresis (2D PAGE), 2D DIGE offers several advantages, such as accuracy and reproducibility between experiments, which facilitate spot-to-spot comparisons. Although whole plasma can be easily obtained, the complexity of plasma samples makes it challenging to analyze samples with good reproducibility. Here, we describe a method for decreasing protein complexity in plasma samples within a narrow pH range by depleting high-abundance plasma proteins. In combination with analysis of differentially expressed spots, trypsin digestion, identification of protein by mass spectrometry, and standard 2D PAGE and DIGE, this method has been optimized for comparison of plasma samples from healthy donors and patients diagnosed with hepatocellular carcinoma.

Plasma proteomic analysis in obese and overweight prepubertal children

BACKGROUND

Childhood obesity represents one of the most challenging health problems of our century and is associated with significant morbidity and mortality in adult life. Proteomics is a large-scale analysis of proteins, which provides, information on protein expression levels, post-translational modifications, subcellular localization and interactions.

OBJECTIVE

To investigate whether obesity in childhood is associated with alterations in plasma protein expression profiles.

METHODS

Plasma samples from 10 obese [age: 10·75 ± 0·16 year; body mass index (BMI): 27·50 ± 0·69 kg m(-2) ], 10 overweight (age: 10·54 ± 0·1 year; BMI: 21·88 ± 0·28 kg m(-2) ) and 10 normal-weight (age: 10·89 ± 0·19 year; BMI: 18·34 ± 0·42kg m(-2) ) prepubertal boys were subjected to protein fractionation and analysed by two-dimensional electrophoresis, followed by protein identification using matrix-assisted laser desorption time-of-flight mass spectrometry. Fasting plasma glucose and serum insulin, lipid and apolipopoprotein concentrations were determined in all subjects.

RESULTS

The expression of apolipoprotein (Apo) A-I (ApoA-I) was significantly lower in obese and overweight children compared with children of normal BMI (P < 0·05). The expression of ApoE was significantly lower in overweight compared with normal-weight children (P < 0·05), while that of ApoA-IV was significantly higher in obese children compared with their normal counterparts (P < 0·01). Serum ApoA-I concentrations were significantly lower in obese (147 ± 4·27mg dL(-1) ) and overweight (145·5 ± 9·65mg dL(-1) ) than in normal-weight (157 ± 8·77mg dL(-1) ; P = 0·036) children.

CONCLUSIONS

Obese and overweight prepubertal children demonstrated prominent alterations in the expression of plasma apolipoproteins compared with their normal counterparts. Low ApoA-I plasma expression levels and serum concentrations in obesity might be present in childhood before any significant alterations in total or high-density lipoprotein-cholesterol concentrations are documented. We recommend that serum ApoA-I concentrations are determined in all overweight and obese children.

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

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

Clinical proteomics: current status, challenges, and future perspectives

This account will give an overview and evaluation of the current advances in mass spectrometry (MS)-based proteomics platforms and technology. A general review of some background information concerning the application of these methods in the characterization of molecular sizes and related protein expression profiles associated with different types of cells under varied experimental conditions will be presented. It is intended to provide a concise and succinct overview to those clinical researchers first exposed to this foremost powerful methodology in modern life sciences of postgenomic era. Proteomic characterization using highly sophisticated and expensive instrumentation of MS has been used to characterize biological samples of complex protein mixtures with vastly different protein structure and composition. These systems are then used to highlight the versatility and potential of the MS-based proteomic strategies for facilitating protein expression analysis of various disease-related organisms or tissues of interest. Major MS-based strategies reviewed herein include (1) matrix-assisted laser desorption ionization-MS and electron-spray ionization proteomics; (2) one-dimensional or two-dimensional gel-based proteomics; (3) gel-free shotgun proteomics in conjunction with liquid chromatography/tandem MS; (4) Multiple reaction monitoring coupled tandem MS quantitative proteomics and; (5) Phosphoproteomics based on immobilized metal affinity chromatography and liquid chromatography-MS/MS.

Applications of proteomics in the study of inflammatory bowel diseases: Current status and future directions with available technologies

Inflammatory bowel diseases (IBD) are chronic, heterogeneous, and multifactorial intestinal inflammatory disorders. Major challenges in IBD research include identification of major pathogenic alterations of genes/proteins as well as effective biomarkers for early diagnosis, prognosis, and prediction of therapeutic response. Since proteins govern cellular structure and biological function, a wide selection of proteomic approaches enables effective characterization of IBD pathogenesis by investigating the dynamic nature of protein expression, cellular and subcellular distribution, posttranslational modifications, and interactions at both the cellular and subcellular levels. The aims of this review are to 1) highlight the current status of proteomic studies of IBD, and 2) introduce the available and emerging proteomic technologies that have potential applications in the study of IBD. These technologies include various mass spectrometry technologies, quantitative proteomics (2D-PAGE, ICAT, SILAC, iTRAQ), protein/antibody arrays, and multi-epitope-ligand cartography. This review also presents information and methodologies, from sample selection and enrichment to protein identification, that are not only essential but also particularly relevant to IBD research. The potential future application of these technologies is expected to have a significant impact on the discovery of novel biomarkers and key pathogenic factors for IBD.