Cancer biomarker development and two-dimensional difference gel electrophoresis (2D-DIGE)

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer

BACKGROUND

Among gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups.

METHODS

Thirty-four patients, categorized into three groups-10 with EC, 12 with Hy, and 12 CO-between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS).

RESULTS

In all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance.

CONCLUSION

The identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

Saliva biomarkers in oral disease

Saliva is a versatile biofluid that contains a wide variety of biomarkers reflecting both physiologic and pathophysiologic states. Saliva collection is noninvasive and highly applicable for tests requiring serial sampling. Furthermore, advances in test accuracy, sensitivity and precision for saliva has improved diagnostic performance as well as the identification of novel markers especially in oral disease processes. These include dental caries, periodontitis, oral squamous cell carcinoma (OSCC) and Sjögren's syndrome (SS). Numerous growth factors, enzymes, interleukins and cytokines have been identified and are the subject of much research investigation. This review highlights current procedures for successful determination of saliva biomarkers including preanalytical factors associated with sampling, storage and pretreatment as well as subsequent analysis. Moreover, it provides an overview of the diagnostic applications of these salivary biomarkers in common oral diseases.

A numerical study on microfluidic devices to maintain the concentration and purity of dielectrophoresis-induced separated fractions of analyte

Determining the physical and chemical properties of biologically important particles such as cells, organelles, viruses, exosomes, complexes, nucleotides, and proteins is needed to understand their function. These properties are determined with common analytical tools (mass spectrometry, cryo-EM, NMR, various spectroscopies, nucleotide sequencing, etc.) whose function can be improved when samples are pure and concentrated. Separations science plays a central role in conditioning samples, ranging from low-resolution benchtop operations like precipitations or extractions to higher-resolution chromatography and electrophoresis. In the last two decades, gradient insulator-based dielectrophoresis (g-iDEP) has emerged as a high-resolution separation technique capable of highly selective enrichment of cells, viruses, exosomes, and proteins. Specific evidence has been shown that pure homogeneous and concentrated fractions of cells and exosomes can be generated from complex mixtures. However, recovering those fractions for analysis has not been developed, limiting the technique to an analytical rather than a preparative one. Here, a finite element analysis was undertaken to identify geometries and operational parameters to efficiently remove the enriched fraction while retaining maximum concentration and providing total mass transfer. Geometric factors (e.g., side channel width and distance from the gradient-inducing gap) were studied, along with the addition of a second inlet side channel. Two flow-generating mechanisms-electroosmosis and hydrostatic pressure-were evaluated for semi-optimized device designs, including a comparison of the one- and two-inlet designs. Simulations indicate effectively one hundred percent mass transfer and a concentration increase by an order of magnitude for several device configurations and operational parameters.

Electrochemical aptasensor based on the engineered core-shell MOF nanostructures for the detection of tumor antigens

It is essential to develop ultrasensitive biosensors for cancer detection and treatment monitoring. In the development of sensing platforms, metal-organic frameworks (MOFs) have received considerable attention as potential porous crystalline nanostructures. Core-shell MOF nanoparticles (NPs) have shown different diversities, complexities, and biological functionalities, as well as significant electrochemical (EC) properties and potential bio-affinity to aptamers. As a result, the developed core-shell MOF-based aptasensors serve as highly sensitive platforms for sensing cancer biomarkers with an extremely low limit of detection (LOD). This paper aimed to provide an overview of different strategies for improving selectivity, sensitivity, and signal strength of MOF nanostructures. Then, aptamers and aptamers-modified core-shell MOFs were reviewed to address their functionalization and application in biosensing platforms. Additionally, the application of core-shell MOF-assisted EC aptasensors for detection of several tumor antigens such as prostate-specific antigen (PSA), carbohydrate antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), human epidermal growth factor receptor-2 (HER2), cancer antigen 125 (CA-125), cytokeratin 19 fragment (CYFRA21-1), and other tumor markers were discussed. In conclusion, the present article reviews the advancement of potential biosensing platforms toward the detection of specific cancer biomarkers through the development of core-shell MOFs-based EC aptasensors.

Clinical application of serum-based proteomics technology in human tumor research

The rapid development of proteomics technology in the past decades has led to further human understanding of tumor research, and in some ways, the technology plays a very important supporting role in the early detection of tumors. Human serum has been shown to contain a variety of proteins closely related to life activities, and the dynamic change in proteins can often reflect the physiological and pathological conditions of the body. Serum has the advantage of easy extraction, so the application of proteomics technology in serum has become a hot spot and frontier area for the study of malignant tumors. However, there are still many difficulties in the standardized use of proteomic technologies, which inevitably limit the clinical application of proteomic technologies due to the heterogeneity of human proteins leading to incomplete whole proteome populations, in addition to most serum protein markers being now not highly specific in aiding the early detection of tumors. Nevertheless, further development of proteomics technologies will greatly increase our understanding of tumor biology and help discover more new tumor biomarkers with specificity that will enable medical technology.

Application of Polypyrrole-Based Electrochemical Biosensor for the Early Diagnosis of Colorectal Cancer

Although colorectal cancer (CRC) is easy to treat surgically and can be combined with postoperative chemotherapy, its five-year survival rate is still not optimistic. Therefore, developing sensitive, efficient, and compliant detection technology is essential to diagnose CRC at an early stage, providing more opportunities for effective treatment and intervention. Currently, the widely used clinical CRC detection methods include endoscopy, stool examination, imaging modalities, and tumor biomarker detection; among them, blood biomarkers, a noninvasive strategy for CRC screening, have shown significant potential for early diagnosis, prediction, prognosis, and staging of cancer. As shown by recent studies, electrochemical biosensors have attracted extensive attention for the detection of blood biomarkers because of their advantages of being cost-effective and having sound sensitivity, good versatility, high selectivity, and a fast response. Among these, nano-conductive polymer materials, especially the conductive polymer polypyrrole (PPy), have been broadly applied to improve sensing performance due to their excellent electrical properties and the flexibility of their surface properties, as well as their easy preparation and functionalization and good biocompatibility. This review mainly discusses the characteristics of PPy-based biosensors, their synthetic methods, and their application for the detection of CRC biomarkers. Finally, the opportunities and challenges related to the use of PPy-based sensors for diagnosing CRC are also discussed.

Nipple fluid for breast cancer diagnosis using the nanopore of Phi29 DNA-packaging motor

Detection of cancer in its early stage is a challenging task for oncologists. Inflammatory breast cancer has symptoms that are similar to mastitis and can be mistaken for microbial infection. Currently, the differential diagnosis between mastitis and Inflammatory breast cancer via nipple aspirate fluid (NAF) is difficult. Here, we report a label-free and amplification-free detection platform using an engineered nanopore of the phi29 DNA-packaging motor with biomarker Galectin3 (GAL3), Thomsen-Friedenreich (TF) binding peptide as the probe fused at its C-terminus. The binding of the biomarker in NAF samples from breast cancer patients to the probe results in the connector's conformational change with a current blockage of 32 %. Utilization of dwell time, blockage ratio, and peak signature enable us to detect basal levels of biomarkers from patient NAF samples at the single-molecule level. This platform will allow for breast cancers to be resolved at an early stage with accuracy and thoroughness.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

2D-DIGE Analysis of Liver Disease in Mice

Hepatocellular carcinoma (HCC) is the major type of primary liver cancer. In this chapter, we describe our routine two-dimensional difference gel electrophoresis (2D-DIGE) workflow for analysis of mouse liver tissue in physiological conditions, as well as of mouse HCC. 2D-DIGE still constitutes a valuable comparative proteomics technique, not only providing information on global protein expression in a sample but also on potential posttranslational protein modifications, occurrence of protein degradation fragments, and the existence of protein isoforms. Thus, 2D-DIGE analysis provides highly complementary data to non-gel-based shotgun mass spectrometry (MS) methods (e.g., liquid chromatography (LC)-MS/MS)-allowing, for example, identification of novel protein biomarkers for HCC or increasing insights into the molecular mechanisms underlying hepatocarcinogenesis.

Top-Down Proteomics and Comparative 2D-DIGE Analysis

The combination of large-scale protein separation techniques, sophisticated mass spectrometry, and systems bioinformatics has led to the establishment of proteomics as a distinct discipline within the wider field of protein biochemistry. Both discovery proteomics and targeted proteomics are widely used in biological and biomedical research, whereby the analytical approaches can be broadly divided into proteoform-centric top-down proteomics versus peptide-centric bottom-up proteomics. This chapter outlines the scientific value of top-down proteomics and describes how fluorescence two-dimensional difference gel electrophoresis can be combined with the systematic analysis of crucial post-translational modifications. The concept of on-membrane digestion following the electrophoretic transfer of proteins and the usefulness of comparative two-dimensional immunoblotting are discussed.

Sample Preparation and Protein Determination for 2D-DIGE Proteomics

Fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) is a widely employed method for efficient protein separation and the determination of abundance changes in distinct proteoforms. This makes this gel-based method a key technique of comparative approaches in top-down proteomics. For the appropriate screening of proteome-wide alterations, initial preparative steps involve sample handling, homogenization, subcellular fractionation, and the determination of protein concentration, which makes the optimal application of these techniques a crucial part of a successful initiation of a new 2D-DIGE-based analysis. This chapter describes sample homogenization and a standardized protein assay for the preparation of homogenates with a known protein concentration for subsequent differential fluorescent tagging and two-dimensional gel electrophoretic separation.

Identification of Ubiquitination-Associated Proteins Using 2D-DIGE

Ubiquitination is a post-translational modification, in which a small regulatory protein (~8.6 kDa) is tagged as a single moiety or as a chain to target proteins. Ubiquitination is the most versatile cellular regulatory mechanism, essential to the physiological and pathophysiological cellular events that regulate protein turnover, gene transcription, cell cycle progression, DNA repair, apoptosis, viral budding, and receptor-mediated endocytosis. Changes and abnormalities within the ubiquitination process can result in a plethora of diseases, including various cancers. The ubiquitination process is tightly controlled in a stepwise manner by four enzymes: E1 ubiquitin-activating enzymes, E2 ubiquitin-conjugating enzymes, E3 ubiquitin-ligating enzymes, and deubiquitinating proteases. Using fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) to detect and quantitate cellular proteins associated with the ubiquitination process will facilitate the evaluation of this post-translational modification associated with the pathophysiological phenotype.

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.

Miniaturized microfluidic-based nucleic acid analyzer to identify new biomarkers of biopsy lung cancer samples for subtyping

Identifying new biomarkers is necessary and important to diagnose and treat malignant lung cancer. However, existing protein marker detection methods usually require complex operation steps, leading to a lag time for diagnosis. Herein, we developed a rapid, minimally invasive, and convenient nucleic acid biomarker recognition method, which enabled the combined specific detection of 11 lung cancer typing markers in a microliter reaction system after only one sampling. The primers for the combined specific detection of 11 lung cancer typing markers were designed and screened, and the microfluidic chip for parallel detection of the multiple markers was designed and developed. Furthermore, a miniaturized microfluidic-based analyzer was also constructed. By developing a microfluidic chip and a miniaturized nucleic acid analyzer, we enabled the detection of the mRNA expression levels of multiple biomarkers in rice-sized tissue samples. The miniaturized nucleic acid analyzer could detect ≥10 copies of nucleic acids. The cell volume of the typing reaction on the microfluidic chip was only 0.94 μL, less than 1/25 of that of the conventional 25-μL Eppendorf tube PCR method, which significantly reduced the testing cost and significantly simplified the analysis of multiple biomarkers in parallel. With a simple injection operation and reverse transcription loop-mediated isothermal amplification (RT-LAMP), real-time detection of 11 lung cancer nucleic acid biomarkers was performed within 45 min. Given these compelling features, 86 clinical samples were tested using the miniaturized nucleic acid analyzer and classified according to the cutoff values of the 11 biomarkers. Furthermore, multi-biomarker analysis was conducted by a machine learning model to classify different subtypes of lung cancer, with an average area under the curve (AUC) of 0.934. This method shows great potential for the identification of new nucleic acid biomarkers and the accurate diagnosis of lung cancer.

Application of two-dimensional difference gel electrophoresis to identify protein changes between center, margin, and adjacent non-tumor tissues obtained from non-small-cell lung cancer with adenocarcinoma or squamous cell carcinoma subtype

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

Gel-Based Proteomic Identification of Suprabasin as a Potential New Candidate Biomarker in Endometrial Cancer

Endometrial cancer (EC) is the most frequent gynaecologic cancer in postmenopausal women. We used 2D-DIGE and mass spectrometry to identify candidate biomarkers in endometrial cancer, analysing the serum protein contents of 10 patients versus 10 control subjects. Using gel-based proteomics, we identified 24 candidate biomarkers, considering only spots with a fold change in volume percentage ≥ 1.5 or intensity change ≤ 0.6, which were significantly different between cases and controls (p < 0.05). We used Western blotting analysis both in the serum and tissue of 43 patients for data validation. Among the identified proteins, we selected Suprabasin (SBSN), an oncogene previously associated with poor prognosis in different cancers. SBSN principal isoforms were subjected to Western blotting analysis in serum and surgery-excised tissue: both isoforms were downregulated in the tissue. However, in serum, isoform 1 was upregulated, while isoform 2 was downregulated. Data-mining on the TCGA and GTEx projects, using the GEPIA2.0 interface, indicated a diminished SBSN expression in the Uterine Corpus Endometrial Cancer (UCEC) database compared to normal tissue, confirming proteomic results. These results suggest that SBSN, specifically isoform 2, in tissue or serum, could be a potential novel biomarker in endometrial cancer.

Proteomic Profiling of Plasma-Derived Biomarkers in Patients with Bladder Cancer: A Step towards Clinical Translation

Background: Bladder cancer is a life-threatening disease and a major cause of cancer-associated complications. The main challenges confronted during the clinical management of bladder cancer are associated with recurrence and disease progression to the muscle-invasive phenotype. Improved early detection of the disease is of paramount importance to prevent disease progression and improve survival. Hence, novel clinically applicable biomarkers for early detection are warranted. Methods: In the current study, a comparative proteomic approach was undertaken using plasma samples to identify protein biomarkers associated with the muscle-invasive phenotype of bladder carcinoma. Isolated plasma proteins were depleted, DIGE-labeled, then subjected to conventional 2D electrophoresis followed by mass spectrometry for identification of differentially expressed proteins. Western blot was used for data validation. Results: Fourteen differentially expressed proteins with statistically significant changes in abundance between the cancer group and control group were identified. Three differentially expressed proteins were selected for validation, among which apolipoprotein A1 exhibited high specificity and sensitivity (AUC = 0.906). Ingenuity pathway analysis identified IFN-γ and TNF-α as the main signaling hub for the differentially regulated proteins. Conclusion: Our findings provide additional insight into understanding bladder cancer pathogenesis. Our data identified potential non-invasive plasma-derived biomarker proteins that merit additional investigation to validate its clinical usefulness to prevent bladder cancer progression.

Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum

Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. We have used 2D-Difference In Gel Electrophoresis (2D-DIGE) coupled with Mass Spectrometry (MS) procedures to investigate the serum proteome of 15 patients with endometrial cancer and 15 non-cancer subjects. We have identified 16 proteins with diagnostic potential, considering only spots with a fold change in %V ≥ 1.5 or ≤0.6 in intensity, which were statistically significant (p < 0.05). Western blotting data analysis confirmed the upregulation of CLU, ITIH4, SERPINC1, and C1RL in endometrial and exosome cancer sera compared to those of control subjects. The application of the logistic regression constructed based on the abundance of these four proteins separated the controls from the cancers with excellent levels of sensitivity and specificity. After a validation phase, our findings support the potential of using the proposed algorithm as a diagnostic tool in the clinical stage.

Validation of serum apolipoprotein A1 in rabies virus-infected mice as a biomarker for the preclinical diagnosis of rabies

Rabies is a type of acute fetal encephalitis caused by rabies virus (RABV). While it becomes incurable after symptom onset, it can be prevented by post‐exposure prophylaxis (PEP) during the long incubation period. While preclinical diagnosis aids the appropriate PEP administration, it is mostly nonfeasible owing to the absence of viremia or a specific antibody response during the incubation period. Here, an attempt was made to identify a serum biomarker for the preclinical diagnosis of rabies. Using the serum from a mouse inoculated intramuscularly (i.m.) with 5 × 10⁵ focus‐forming units (FFU) of recombinant RABV expressing red firefly luciferase (1088/RFLuc) immediately before symptom onset, two‐dimensional differential gel electrophoresis was conducted, followed by mass spectrometry, and it was confirmed that apolipoprotein A1 (ApoA1) was up‐regulated. ELISA showed that the serum ApoA1 and specific antibody levels increased during the incubation period and on the day of symptom onset. Since a lower infectious dose can be used to induce the unstable and long incubation period generally observed in natural infection, the ApoA1 level in mice inoculated i.m. with 10³ FFU of 1088/RFLuc was examined by monitoring viral dynamics using in vivo imaging. The serum ApoA1 and specific antibody levels were up‐regulated in 50% and 58.3% of mice exhibiting robust RABV replication, respectively, but not in mice exhibiting weak RABV replication. In addition, it was reported that ApoA1 was found to be a biomarker for neuronal damage. Additional biomarker candidates will be needed for the effective preclinical diagnosis of rabies.

Saliva Proteomics as Fluid Signature of Inflammatory and Immune-Mediated Skin Diseases

Saliva is easy to access, non-invasive and a useful source of information useful for the diagnosis of serval inflammatory and immune-mediated diseases. Following the advent of genomic technologies and -omic research, studies based on saliva testing have rapidly increased and human salivary proteome has been partially characterized. As a proteomic protocol to analyze the whole saliva proteome is not currently available, the most common aim of the proteomic analysis is to discriminate between physiological and pathological conditions. The salivary proteome has been initially investigated in several diseases: oral squamous cell carcinoma and oral leukoplakia, chronic graft-versus-host disease, and Sjögren's syndrome. Otherwise, salivary proteomics studies in the dermatological field are still in the initial phase, thus the aim of this review is to collect the best research evidence on the role of saliva proteomics analysis in immune-mediated skin diseases to understand the direction of research in this field. The results of PRISMA analysis reported herein suggest that human saliva analysis could provide significant data for the diagnosis and prognosis of several immune-mediated and inflammatory skin diseases in the next future.

Proteomics signature of autoimmune atrophic gastritis: towards a link with gastric cancer

BACKGROUND

Autoimmune atrophic gastritis (AAG) is a chronic disease that can progress to gastric cancer (GC). To better understand AAG pathology, this proteomics study investigated gastric proteins whose expression levels are altered in this disease and also in GC.

METHODS

Using two-dimensional difference gel electrophoresis (2D-DIGE), we compared protein maps of gastric corpus biopsies from AAG patients and controls. Differentially abundant spots (|fold change|≥ 1.5, P < 0.01) were selected and identified by LC-MS/MS. The spots were further assessed in gastric antrum biopsies from AAG patients (without and with Helicobacter pylori infection) and from GC patients and unaffected first-degree relatives of GC patients.

RESULTS

2D-DIGE identified 67 differentially abundant spots, with 28 more and 39 less abundant in AAG-corpus than controls. LC-MS/MS identified these as 53 distinct proteins. The most significant (adjusted P < 0.01) biological process associated with the less abundant proteins was "tricarboxylic acid cycle". Of the 67 spots, 57 were similarly differentially abundant in AAG-antrum biopsies irrespective of H. pylori infection status. The differential abundance was also observed in GC biopsies for 14 of 28 more abundant and 35 of 39 less abundant spots, and in normal gastric biopsies of relatives of GC patients for 6 and 25 spots, respectively. Immunoblotting confirmed the different expression levels of two more abundant proteins (PDIA3, GSTP gene products) and four less abundant proteins (ATP5F1A, PGA3, SDHB, PGC).

CONCLUSION

This study identified a proteomics signature of AAG. Many differential proteins were shared by GC and may be involved in the progression of AAG to GC.

A Quest for New Cancer Diagnosis, Prognosis and Prediction Biomarkers and Their Use in Biosensors Development

Traditional techniques for cancer diagnosis, such as nuclear magnetic resonance, ultrasound and tissue analysis, require sophisticated devices and highly trained personnel, which are characterized by elevated operation costs. The use of biomarkers has emerged as an alternative for cancer diagnosis, prognosis and prediction because their measurement in tissues or fluids, such as blood, urine or saliva, is characterized by shorter processing times. However, the biomarkers used currently, and the techniques used for their measurement, including ELISA, western-blot, polymerase chain reaction (PCR) or immunohistochemistry, possess low sensitivity and specificity. Therefore, the search for new proteomic, genomic or immunological biomarkers and the development of new noninvasive, easier and cheaper techniques that meet the sensitivity and specificity criteria for the diagnosis, prognosis and prediction of this disease has become a relevant topic. The purpose of this review is to provide an overview about the search for new cancer biomarkers, including the strategies that must be followed to identify them, as well as presenting the latest advances in the development of biosensors that possess a high potential for cancer diagnosis, prognosis and prediction, mainly focusing on their relevance in lung, prostate and breast cancers.

What Room for Two-Dimensional Gel-Based Proteomics in a Shotgun Proteomics World?

Two-dimensional gel electrophoresis was instrumental in the birth of proteomics in the late 1980s. However, it is now often considered as an outdated technique for proteomics—a thing of the past. Although this opinion may be true for some biological questions, e.g., when analysis depth is of critical importance, for many others, two-dimensional gel electrophoresis-based proteomics still has a lot to offer. This is because of its robustness, its ability to separate proteoforms, and its easy interface with many powerful biochemistry techniques (including western blotting). This paper reviews where and why two-dimensional gel electrophoresis-based proteomics can still be profitably used. It emerges that, rather than being a thing of the past, two-dimensional gel electrophoresis-based proteomics is still highly valuable for many studies. Thus, its use cannot be dismissed on simple fashion arguments and, as usual, in science, the tree is to be judged by the fruit.

Advances of proteomics technologies for multidrug-resistant mechanisms

Multidrug resistance (MDR) is a vital issue in cancer treatment. Drug resistance can be developed through a variety of mechanisms, including increased drug efflux, activation of detoxifying systems and DNA repair mechanisms, and escape of drug-induced apoptosis. Identifying the exact mechanism related in a particular case is a difficult task. Proteomics is the large-scale study of proteins, particularly their expression, structures and functions. In recent years, comparative proteomic methods have been performed to analyze MDR mechanisms in drug-selected model cancer cell lines. In this paper, we review the recent developments and progresses by comparative proteomic approaches to identify potential MDR mechanisms in drug-selected model cancer cell lines, which may help understand and design chemical sensitizers.

2D electrophoresis image brightness correction based on gradient interval histogram

Background

Two-dimensional electrophoresis (2DE) is one of the most widely applied techniques in comparative proteomics. The basic task of 2DE is to identify differential protein expression by quantitative analysis of 2DE images. To reduce the errors of spot quantification in 2DE images, a novel brightness correction method based on gradient interval histogram (GIH) is proposed in this paper.

Results

First, GIH equalization is proposed to enhance the protein spot edges, especially the weak protein spots in the 2DE image. Second, to eliminate the overall brightness shift, GIH matching is applied to the 2DE images that need to be compared. Finally, the proposed method is verified by subjective quality evaluation and quantitative analysis of protein spots in real 2DE images.

Conclusions

The experimental results show that the average error of the quantification of corresponding protein spots in the resulting image pairs is less than 3%, which is significantly superior to that of the existing methods.

Saliva and Oral Diseases

Saliva is a fascinating biological fluid which has all the features of a perfect diagnostic tool. In fact, its collection is rapid, simple, and noninvasive. Thanks to several transport mechanisms and its intimate contact with crevicular fluid, saliva contains hundreds of proteins deriving from plasma. Advances in analytical techniques have opened a new era-called "salivaomics"-that investigates the salivary proteome, transcriptome, microRNAs, metabolome, and microbiome. In recent years, researchers have tried to find salivary biomarkers for oral and systemic diseases with various protocols and technologies. The review aspires to provide an overall perspective of salivary biomarkers concerning oral diseases such as lichen planus, oral cancer, blistering diseases, and psoriasis. Saliva has proved to be a promising substrate for the early detection of oral diseases and the evaluation of therapeutic response. However, the wide variation in sampling, processing, and measuring of salivary elements still represents a limit for the application in clinical practice.

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.

Electrochemical biosensors for the detection of lung cancer biomarkers: A review

Cancer is one of the most widespread challenges and important diseases, which has the highest mortality rate. Lung cancer is the most common type of cancer, so that about 25% of all cancer deaths are related to the lung cancer. The lung cancer is classified as two different types with different treatment methodology: the small cell lung carcinoma and nonsmall cell lung carcinoma are two categories of the lung cancer. Since the lung cancer is often in the latent period in its early stages, therefore, early diagnosis of lung cancer has many challenges. Hence, there is a need for sensitive and reliable tools for preclinical diagnosis of lung cancer. Therefore, many detection methods have been employed for early detection of lung cancer. As lung cancer tumors growth in the body, the cancerous cells release numerous DNA, proteins, and metabolites as special biomarkers of the lung cancer. The levels of these biomarkers show the stages of the lung cancer. Therefore, detection of the biomarkers can be used for screening and clinical diagnosis of the lung cancer. There are numerous biomarkers for the lung cancer such as EGFR, CEA, CYFRA 21-1, ENO1, NSE, CA 19-9, CA 125 and VEGF. Nowadays, electrochemical methods are very attractive and useful in the lung cancer detections. So, in this paper, the recent advances and improvements (2010-2018) in the electrochemical detection of the lung cancer biomarkers have been reviewed.

Mass spectrometric characterization of the zein protein composition in maize flour extracts upon protein separation by SDS-PAGE and 2D gel electrophoresis

Highly homogenous α zein protein was isolated from maize kernels in an environment-friendly process using 95% ethanol as solvent. Due to the polyploidy and genetic polymorphism of the plant source, the application of high resolution separation methods in conjunction with precise analytical methods, such as MALDI-TOF-MS, is required to accurately estimate homogeneity of products that contain natural zein protein. The α zein protein product revealed two main bands in SDS-PAGE analysis, one at 25 kDa and other at 20 kDa apparent molecular mass. Yet, high resolution 2DE revealed approximately five protein spot groups in each row, the first at ca. 25 kDa and the second at ca. 20 kDa. Peptide mass fingerprinting data of the proteins in the two dominant SDS-PAGE bands matched to 30 amino acid sequence entries out of 102 non-redundant data base entries. MALDI-TOF-MS peptide mapping of the proteins from all spots indicated the presence of only α zein proteins. The most prominent ion signals in the MALDI mass spectra of the protein mixture of the 25 kDa SDS gel band after in-gel digestion were found at m/z 1272.6 and m/z 2009.1, and the most prominent ion signals of the protein mixture of the 20 kDa band after in-gel digestion were recorded at m/z 1083.5 and m/z 1691.8. These ion signals have been found typical for α zein proteins and may serve as marker ion signals which upon chymotryptic digestion reliably indicate the presence of α zein protein in two hybrid corn products.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

Calreticulin as A Novel Potential Metastasis-Associated Protein in Myxoid Liposarcoma, as Revealed by Two-Dimensional Difference Gel Electrophoresis

Myxoid liposarcoma (MLS) is a mesenchymal malignancy. To identify innovate seeds for clinical applications, we examined the proteomes of primary tumor tissues from 10 patients with MLS with different statuses of postoperative metastasis. The protein expression profiles of tumor tissues were created, and proteins with differential expression associated with postoperative metastasis were identified by two-dimensional difference gel electrophoresis (2D-DIGE) and mass spectrometry. The validation was performed using specific antibodies and in vitro analyses. Using 2D-DIGE, we observed 1726 protein species and identified proteins with unique expression levels in metastatic MLS. We focused on the overexpression of calreticulin in metastatic MLS. The higher expression of calreticulin was confirmed by Western blotting, and gene silencing assays demonstrated that reduced expression of calreticulin inhibited cell growth and invasion. Our findings suggested the important roles of calreticulin in MLS metastasis and supported its potential utility as a prognostic biomarker in MLS. Further investigations of the functional properties of calreticulin and other proteins identified in this study will improve our understanding of the biology of MLS and facilitate novel clinical applications.