Possibilities and limitations of 2DE-based analyses for identifying low-abundant tumor markers in human serum and plasma

Proteomics Methodologies: The Search of Protein Biomarkers Using Microfluidic Systems Coupled to Mass Spectrometry

Protein biomarkers have been the subject of intensive studies as a target for disease diagnostics and monitoring. Indeed, biomarkers have been extensively used for personalized medicine. In biological samples, these biomarkers are most often present in low concentrations masked by a biologically complex proteome (e.g., blood) making their detection difficult. This complexity is further increased by the needs to detect proteoforms and proteome complexity such as the dynamic range of compound concentrations. The development of techniques that simultaneously pre-concentrate and identify low-abundance biomarkers in these proteomes constitutes an avant-garde approach to the early detection of pathologies. Chromatographic-based methods are widely used for protein separation, but these methods are not adapted for biomarker discovery, as they require complex sample handling due to the low biomarker concentration. Therefore, microfluidics devices have emerged as a technology to overcome these shortcomings. In terms of detection, mass spectrometry (MS) is the standard analytical tool given its high sensitivity and specificity. However, for MS, the biomarker must be introduced as pure as possible in order to avoid chemical noise and improve sensitivity. As a result, microfluidics coupled with MS has become increasingly popular in the field of biomarker discovery. This review will show the different approaches to protein enrichment using miniaturized devices and the importance of their coupling with MS.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Two-Dimensional Gel Electrophoresis and 2D-DIGE

Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) continues to be one of the most versatile and widely used techniques to study the proteome of a biological system, particularly in the separation of intact proteins. A modified version of 2D-PAGE, two-dimensional difference gel electrophoresis (2D-DIGE), which uses differential labeling of protein samples with up to three fluorescent tags, offers greater sensitivity and reproducibility over conventional 2D-PAGE gels for differential quantitative analysis of protein expression between experimental groups. Both these methods have distinct advantages in the separation and identification of thousands of individual protein species including protein isoforms and post-translational modifications. This chapter discusses the principles of 2D-PAGE and 2D-DIGE including limitations to the methods. 2D-PAGE and 2D-DIGE continue to be popular methods in bioprocessing-related research, particularly on recombinant Chinese hamster ovary cells, which are also discussed in this chapter.

Understanding Cervical Cancer through Proteomics

Cancer is one of the leading public health issues worldwide, and the number of cancer patients increases every day. Particularly, cervical cancer (CC) is still the second leading cause of cancer death in women from developing countries. Thus, it is essential to deepen our knowledge about the molecular pathogenesis of CC and propose new therapeutic targets and new methods to diagnose this disease in its early stages. Differential expression analysis using high-throughput techniques applied to biological samples allows determining the physiological state of normal cells and the changes produced by cancer development. The cluster of differential molecular profiles in the genome, the transcriptome, or the proteome is analyzed in the disease, and it is called the molecular signature of cancer. Proteomic analysis of biological samples of patients with different grades of cervical intraepithelial neoplasia (CIN) and CC has served to elucidate the pathways involved in the development and progression of cancer and identify cervical proteins associated with CC. However, several cervical carcinogenesis mechanisms are still unclear. Detecting pathologies in their earliest stages can significantly improve a patient's survival rate, prognosis, and recurrence. The present review is an update on the proteomic study of CC.

Assessment of Serum Tumor Markers for Predicting Ocular Metastasis in Lung Adenocarcinoma: A Retrospective Study

The purpose of this study was to detect clinical variations between lung adenocarcinoma patients with and without ocular metastasis (OM) to identify risk factors for OM and assess the diagnostic values. We included 1153 patients with lung adenocarcinoma in this study. Independent t-tests and chi-square tests were used to compare patients' clinical characteristics. Statistically significant parameters were analyzed by binary logistic regression to detect risk factors of OM. The results showed that the OM group had increased alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), cytokeratin fragment 19 (CYFRA 21-1), carbohydrate antigen- (CA-) 125, CA-153, and total prostate-specific antigen (TPSA) compared with the NOM group. CYFRA21-1 is the most useful biomarker for detecting OM in this population.

Identification of protein changes in the blood plasma of lung cancer patients subjected to chemotherapy using a 2D-DIGE approach

A comparative analysis of blood samples (depleted of albumin and IgG) obtained from lung cancer patients before chemotherapy versus after a second cycle of chemotherapy was performed using two-dimensional difference gel electrophoresis (2D-DIGE). The control group consisted of eight patients with non-cancerous lung diseases, and the experimental group consisted of four adenocarcinoma (ADC) and four squamous cell carcinoma (SCC) patients. Analyses of gels revealed significant changes in proteins and/or their proteoforms between control patients and lung cancer patients, both before and after a second cycle of chemotherapy. Most of these proteins were related to inflammation, including acute phase proteins (APPs) such as forms of haptoglobin and transferrin, complement component C3, and clusterin. The variable expression of APPs can potentially be used for profiling lung cancer. The greatest changes observed after chemotherapy were in transferrin and serotransferrin, which likely reflect disturbances in iron turnover after chemotherapy-induced anaemia. Significant changes in plasma proteins between ADC and SCC patients were also revealed, suggesting use of plasma vitronectin as a potential marker of SCC.

Comparing Complex Protein Samples Using Two-Dimensional Polyacrylamide Gels

This manuscript describes protocols for separation of complex protein samples using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Electrophoresis in a single dimension, e.g., 1D SDS polyacrylamide gels, has the potential to rapidly separate hundreds of proteins. When two orthogonal high-resolution electrophoretic methods are efficiently combined in perpendicular dimensions, complex protein mixtures can be separated into thousands of discrete spots. The most common 2D gel separation for intact proteins involves a first-dimensional separation using isoelectric focusing (IEF) followed by separation based on protein size (SDS-PAGE). Currently, most 2D gel studies rely on the use of commercially available immobilized pH gradient (IPG) gels, which provide improved ease of use and reproducibility compared with older methods. IPG gels are available in a range of sizes and different pH ranges. Resolution typically increases as the 2D gel size increases; however, difficulty of use increases sharply and throughput decreases as gel size increases. © 2019 by John Wiley & Sons, Inc.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Clinical Proteomics: Closing the Gap from Discovery to Implementation

Clinical proteomics, the application of proteome analysis to serve a clinical purpose, represents a major field in the area of proteome research. Over 1000 manuscripts on this topic are published each year, with numbers continuously increasing. However, the anticipated outcome, the transformation of the reported findings into improvements in patient management, is not immediately evident. In this article, the value and validity of selected clinical proteomics findings are investigated, and it is assessed how far implementation has progressed. A main conclusion from this assessment is that to achieve implementation, well-powered clinical studies are required in the appropriate population, addressing a specific clinical need and with a clear context-of-use. Efforts toward implementation, to be feasible, must be supported by the key players in science: publishers and funders. The authors propose a change on objectives, from additional discovery studies toward studies aiming at validation of the plethora of potential biomarkers that have been described, to demonstrate practical value of clinical proteomics. All elements required, potential biomarkers, technologies, and bio-banked samples are available (based on today's literature), hence a change in focus from discovery toward validation and application is not only urgently necessary, but also possible based on resources available today.

Two-Dimensional Gel Electrophoresis and 2D-DIGE

Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) continues to be one of the most versatile and widely used techniques to study the proteome of a biological system. In particular, a modified version of 2D-PAGE, two-dimensional difference gel electrophoresis (2D-DIGE), which uses differential labeling of protein samples with up to three fluorescent tags, offers greater sensitivity and reproducibility over conventional 2D-PAGE gels for differential quantitative analysis of protein expression between experimental groups. Both these methods have distinct advantages in the separation and identification of thousands of individual proteins species including protein isoforms and post-translational modifications. This review will discuss the principles of 2D-PAGE and 2D-DIGE including limitations to the methods. 2D-PAGE and 2D-DIGE continue to be popular methods in bioprocessing-related research (particularly on recombinant Chinese hamster ovary cells), which will also be discussed in the review chapter.

Protein levels of clusterin and glutathione synthetase in platelets allow for early detection of colorectal cancer

Colorectal cancer (CRC) is one of the most frequent malignancies in the Western world. Early tumor detection and intervention are important determinants on CRC patient survival. During early tumor proliferation, dissemination and angiogenesis, platelets store and segregate proteins actively and selectively. Hence, the platelet proteome is a potential source of biomarkers denoting early malignancy. By comparing protein profiles of platelets between healthy volunteers (n = 12) and patients with early- (n = 7) and late-stage (n = 5) CRCs using multiplex fluorescence two-dimensional gel electrophoresis (2D-DIGE), we aimed at identifying differentially regulated proteins within platelets. By inter-group comparisons, 94 differentially expressed protein spots were detected (p < 0.05) between healthy controls and patients with early- and late-stage CRCs and revealed distinct separations between all three groups in principal component analyses. 54 proteins of interest were identified by mass spectrometry and resulted in high-ranked Ingenuity Pathway Analysis networks associated with Cellular function and maintenance, Cellular assembly and organization, Developmental disorder and Organismal injury and abnormalities (p < 0.0001 to p = 0.0495). Target proteins were validated by multiplex fluorescence-based Western blot analyses using an additional, independent cohort of platelet protein samples [healthy controls (n = 15), early-stage CRCs (n = 15), late-stage CRCs (n = 15)]. Two proteins-clusterin and glutathione synthetase (GSH-S)-featured high impact and were subsequently validated in this independent clinical cohort distinguishing healthy controls from patients with early- and late-stage CRCs. Thus, the potential of clusterin and GSH-S as platelet biomarkers for early detection of CRC could improve existing screening modalities in clinical application and should be confirmed in a prospective multicenter trial.

EB1 protein alteration characterizes sporadic but not ulcerative colitis associated colorectal cancer

Background

While carcinogenesis in Sporadic Colorectal Cancer (SCC) has been thoroughly studied, less is known about Ulcerative Colitis associated Colorectal Cancer (UCC). This study aimed to identify and validate differentially expressed proteins between clinical samples of SCC and UCC to elucidate new insights of UCC/SCC carcinogenesis and progression.

Results

Multiplex-fluorescence two-dimensional gel electrophoresis (2-D DIGE) and mass spectrometry identified 67 proteoforms representing 43 distinct proteins. After analysis by Ingenuity Pathway Analysis^® (IPA), subsequent Western blot validation proofed the differential expression of Heat shock 27 kDA protein 1 (HSPB1) and Microtubule-associated protein R/EB family, member 1 (EB1) while the latter one showed also expression differences by immunohistochemistry.

Materials and Methods

Fresh frozen tissue of UCC (n = 10) matched with SCC (n = 10) was investigated. Proteins of cancerous intestinal mucosal cells were obtained by Laser Capture Microdissection (LCM) and compared by 2-D DIGE. Significant spots were identified by mass spectrometry. After IPA, three proteins [EB1, HSPB1, and Annexin 5 (ANXA5)] were chosen for further validation by Western blotting and tissue microarray-based immunohistochemistry.

Conclusions

This study identified significant differences in protein expression of colorectal carcinoma cells from UCC patients compared to patients with SCC. Particularly, EB1 was validated in an independent clinical cohort.

Mixture Modeling of 2-D Gel Electrophoresis Spots Enhances the Performance of Spot Detection

2-D gel electrophoresis is the most commonly used method in biomedicine to separate even thousands of proteins in a complex sample on a single gel. Even though the technique is quite known, there is still a need to find an efficient and reliable method for detection of protein spots on gel image. In this paper, a three-step algorithm based on mixture of 2-D normal distribution functions is introduced to improve the efficiency of spot detection performed by the existing algorithms, namely Pinnacle software and watershed segmentation method. Comparison of methods is based on using simulated and real data sets with known true spot positions and different number of spots. Fitting a mixture of components to gel image allows for achieving higher sensitivity in detecting spots, regardless the method used to find initial conditions for the model parameters, and it leads to better overall performance of spot detection. By using mixture model, location of spot centers can be estimated with higher accuracy than using the Pinnacle method. An application of spot shape modeling gives higher sensitivity of obtaining low-intensity spots than the watershed method, which is crucial in the discovery of novel biomarkers.

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule.