SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

Study of Three Potential Diagnostic Biomarkers in Nasopharyngeal Carcinoma Samples from Guilan, North of Iran

Introduction  Finding biomarkers for highly lethal cancers is a priority. Objective  The current study was designed to understand the clinical significance of vascular endothelial growth factor (VEGF), latent membrane protein 1 (LMP1), and tumor necrosis factor-α (TNF-α) expression as the biomarkers, and evaluate their correlation with each other, in nasopharyngeal carcinoma (NPC) in the province of Guilan, North of Iran. Methods  Gene expression was evaluated in 25 formalin-fixed paraffin-embedded (FFPE) blocks from cases of confirmed NPC and 20 FFPE samples of non-NPC by quantifying messenger ribonucleic acid (mRNA) and protein levels, using real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) methods, respectively. Furthermore, the correlations among the protein levels of different genes, along with the patients' demographic characteristics were assessed. Results  Our findings on mRNA and protein levels demonstrated that the expression of the LMP1 gene in the NPC group was significantly elevated compared with that of the non-NPC group. In addition, the protein levels in the NPC group indicated a positive and significant correlation between LMP1 and VEGF expression. It was noted that both protein and mRNA levels showed no significant differences in the expression of TNF-α and VEGF genes between the NPC and control groups. Furthermore, there was no significant relationship between the expression of these proteins and the demographic characteristics of NPC patients. Conclusion  Overall, a significant increase in LMP1 expression was observed in NPC patients, which may serve as a diagnostic biomarker for NPC. Also, LMP1 might be involved in NPC progression by inducing VEGF gene expression.

Plasma biomarker panel for major depressive disorder by quantitative proteomics using ensemble learning algorithm: A preliminary study

Major depressive disorder (MDD) is a major international public health issue; thus, investigating its underlying mechanisms and identifying suitable biomarkers to enable its early detection are imperative. Using data-independent acquisition-mass spectrometry-based proteomics, the plasma of 44 patients with MDD and 25 healthy controls was studied to detect differentially expressed proteins. Bioinformatics analyses, such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, Protein-Protein Interaction network, and weighted gene co-expression network analysis were employed. Moreover, an ensemble learning technique was used to build a prediction model. A panel of two biomarkers, L-selectin and an isoform of the Ras oncogene family was identified. With an area under the receiver operating characteristic curve of 0.925 and 0.901 for the training and test sets, respectively, the panel was able to distinguish MDD from the controls. Our investigation revealed numerous potential biomarkers and a diagnostic panel based on several algorithms, which may contribute to the future development of a plasma-based diagnostic approach and better understanding of the molecular mechanisms of MDD.

Apoptosis Effects of Oxalis corniculata L. Extract on Human MCF-7 Breast Cancer Cell Line:

Background: Recently, the non-toxic properties of natural plant products have gained more focus as anticancer agents. Therefore, this study aimed to assess the apoptosis effects of the ethanolic extract of Oxalis corniculata on the MCF-7 breast cancer cell line.Materials and Methods: In this experimental study, aerial parts of O. corniculata were collected in Lahijan city (Iran), and after confirmation, they were dried and extracted with ethanol for 24 h. Then, the total phenolic and flavonoid contents of the extract were measured. The 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay was used to measure the antioxidant properties of the extract. Selected cell lines (MCF-7 and human dermal fibroblast) were cultured in 6-wells dishes (1×10⁶ cells/well). After 72 h of treating the extract, cytotoxicity was assessed using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. The expression of apoptotic genes (such as p53, bcl-2, bax, and CD95) was studied by real-time polymerase chain reaction (PCR). Results: The extract's total phenolic content was 31.30±02 μg of gallic acid equivalents/mg of dry extract, and the total flavonoid content was 49.61±04 μg of quercetin as equivalents/mg of extract. The antioxidant activity ofO. corniculata was measured at the dose of 619.2 μg/μl, indicating that it decreases cancer cell viability and enhances apoptosis. Within the half maximal inhibitory concentrations, real-time PCR revealed substantial increases in p53 (P<0.001), CD95 (P<0.05), and bcl-2 expression (P<0.05) in MCF-7 cells treated with O. corniculata. Conclusion: This study suggests that O. corniculata may cause apoptosis by oxidative stress in cancer cells.[GMJ.2022;11:e2484].

Quantitative Proteomic Study Unmasks Fibrinogen Pathway in Polycystic Liver Disease

(1) Background: Polycystic liver disease (PLD) is a heterogeneous group of congenital disorders characterized by bile duct dilatation and cyst development derived from cholangiocytes. Nevertheless, the cystogenesis mechanism is currently unknown and the PLD treatment is limited to liver transplantation. Novel and efficient therapeutic approaches are th6us needed. In this context, the present work has a principal aim to find novel molecular pathways, as well as new therapeutic targets, involved in the hepatic cystogenesis process. (2) Methods: Quantitative proteomics based on SWATH-MS technology were performed comparing hepatic proteomes of Wild Type and mutant/polycystic livers in a polycystic kidney disease (PKD) murine model (Pkd1cond/cond;Tam-Cre-/+). (3) Results: We identified several proteins altered in abundance, with two-fold cut-off up-regulation or down-regulation and an adjusted p-value significantly related to hepatic cystogenesis. Then, we performed enrichment and a protein-protein analysis identifying a cluster focused on hepatic fibrinogens. Finally, we validated a selection of targets by RT-qPCR, Western blotting and immunohistochemistry, finding a high correlation with quantitative proteomics data and validating the fibrinogen complex. (4) Conclusions: This work identified a novel molecular pathway in cystic liver disease, highlighting the fibrinogen complex as a possible new therapeutic target for PLD.

Integrating SWATH-MS proteomics and transcriptome analysis to preliminarily identify three DEGs as biomarkers for proliferative diabetic retinopathy

PURPOSE

We intended to preliminarily find differentially expressed proteins that play crucial roles in proliferative diabetic retinopathy (PDR), and lay the foundation for subsequent further research on the mechanism.

EXPERIMENTAL DESIGN

Here, we developed a new strategy integrated the sequential windowed acquisition of all theoretical fragment ion (SWATH) mass spectra (MS) with multi-dataset joint analysis to screen for the PDR plasma biomarker. The annotation of the given gene list was performed with ClueGO function analysis. Additionally, the protein-protein interaction relationship was also revealed by the STRING database.

RESULTS

In SWATH-MS assays, we identified 23 upregulated and 13 downregulated proteins in PDR plasma. In the mRNA database analysis, 375 genes were identified as differentially expressed genes in GSE102485. Only three genes (FCGR3A, DPEP2, and ADGRF5) were characterized as upregulated in both the dataset and the SWATH-MS list. The area under the ROC curve (AUC) of FCGR3A, DPEP2, and ADGRF5 in distinguishing PDR from others was 0.739, 0.770, and 0.739.

CONCLUSIONS AND CLINICAL RELEVANCE

We provide a novel strategy for biomarker screening and identified plasma FCGR3A, DPEP2, and ADGRF5 as potential biomarkers for patients with PDR. Identifying the key molecules of the disease is essential for the development of new therapeutic molecules and new uses of existing drugs.

Detection of Circulating Serum Protein Biomarkers of Non-Muscle Invasive Bladder Cancer after Protein Corona-Silver Nanoparticles Analysis by SWATH-MS

Because cystoscopy is expensive and invasive, a new method of detecting non-invasive muscular bladder cancer (NMIBC) is needed. This study aims to identify potential serum protein markers for NMIBC to improve diagnosis and to find treatment approaches that avoid disease progression to a life-threatening phenotype (muscle-invasive bladder cancer, MIBC). Here, silver nanoparticles (AgNPs, 9.73 ± 1.70 nm) as a scavenging device together with sequential window acquisition of all theoretical mass spectra (SWATH-MS) were used to quantitatively analyze the blood serum protein alterations in two NMIBC subtypes, T1 and Ta, and they were compared to normal samples (HC). NMIBC’s analysis of serum samples identified three major groups of proteins, the relative content of which is different from the HC content: proteins implicated in the complement and coagulation cascade pathways and apolipoproteins. In conclusion, many biomarker proteins were identified that merit further examination to validate their useful significance and utility within the clinical management of NMIBC patients.

SWATH-MS and MRM: Quantification of Ras-related proteins in HIV-1 infected and methamphetamine-exposed human monocyte-derived macrophages (hMDM)

HIV-1 infection of macrophages is a multistep and multifactorial process that has been shown to be enhanced by exposure to methamphetamine (Meth). In this study, we sought to identify the underlying mechanisms of this effect by quantifying the effect of Meth on the proteome of HIV-1-infected macrophages using sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) approach. The analyses identified several members of the Rab family of proteins as being dysregulated by Meth treatment, which was confirmed by bioinformatic analyses that indicated substantial alteration of vesicular transport pathways. Validation of the SWATH-MS was performed using an MRM based approach, which confirmed that Meth exposure affects expression of the Rab proteins. However, the pattern of expression changes were highly dynamic, and displayed high donor-to-donor variability. Surprisingly a similar phenomenon was observed for Actin. Our results demonstrate that Meth affects vesicular transport pathways, suggesting a possible molecular mechanism underlying its effect on HIV infection hMDM and a potential broader effect of Meth on cellular homeostasis.

Research status and prospects of biomarkers for nasopharyngeal carcinoma in the era of high‑throughput omics (Review)

As a malignant tumor type, nasopharyngeal carcinoma (NPC) is characterized by distinct geographical, ethnic and genetic differences; presenting a major threat to human health in many countries, especially in Southern China. At present, no accurate and effective methods are available for the early diagnosis, efficacious evaluation or prognosis prediction for NPC. As such, a large number of patients have locoregionally advanced NPC at the time of initial diagnosis. Many patients show toxic reactions to overtreatment and have risks of cancer recurrence and distant metastasis owing to insufficient treatment. To solve these clinical problems, high‑throughput '‑omics' technologies are being used to screen and identify specific molecular biomarkers for NPC. Because of the lack of comprehensive descriptions regarding NPC biomarkers, the present study summarized the research progress that has been made in recent years to discover NPC biomarkers, highlighting the existing problems that require exploration. In view of the lack of authoritative reports at present, study design factors that affect the screening of biomarkers are also discussed here and prospects for future research are proposed to provide references for follow‑up studies of NPC biomarkers.

Improved SILAC Quantification with Data-Independent Acquisition to Investigate Bortezomib-Induced Protein Degradation

Stable isotope labeling by amino acids in cell culture (SILAC) coupled to data-dependent acquisition (DDA) is a common approach to quantitative proteomics with the desirable benefit of reducing batch effects during sample processing and data acquisition. More recently, using data-independent acquisition (DIA/SWATH) to systematically measure peptides has gained popularity for its comprehensiveness, reproducibility, and accuracy of quantification. The complementary advantages of these two techniques logically suggests combining them. Here we develop a SILAC-DIA-MS workflow using free, open-source software. We empirically determine that using DIA achieves similar peptide detection numbers as DDA and that DIA improves the quantitative accuracy and precision of SILAC by an order of magnitude. Finally, we apply SILAC-DIA-MS to determine protein turnover rates of cells treated with bortezomib, an FDA-approved 26S proteasome inhibitor for multiple myeloma and mantle cell lymphoma. We observe that SILAC-DIA produces more sensitive protein turnover models. Of the proteins determined to be differentially degraded by both acquisition methods, we find known proteins that are degraded by the ubiquitin-proteasome pathway, such as HNRNPK, EIF3A, and IF4A1/EIF4A-1, and a slower turnover for CATD, a protein implicated in invasive breast cancer. With improved quantification from DIA, we anticipate that this workflow will make SILAC-based experiments like protein turnover more sensitive.

Phosphoproteome and Biological Evidence Revealed Abnormal Calcium Homeostasis in Keloid Fibroblasts and Induction of Aberrant Platelet Aggregation

Keloid is a benign tumor characterized by persistent inflammation, increased fibroblast proliferation, and abnormal deposition of collagen in the wound. The etiology of keloid is unclear. Here, we explored the phospho-signaling changes in human keloid fibroblasts via phosphoproteome mass spectrometry analysis. We found that comparative phosphoproteomics could statistically distinguish keloid from control fibroblasts. Differentially expressed phosphoproteins could predict the activation of known keloid-relevant upstream regulators including transforming growth factor-β1, interleukin (IL)-4, and IL-5. With multiple bioinformatics analyses, phosphorylated FLNA, TLN1, and VCL were significantly enriched in terms of calcium homeostasis and platelet aggregation. We biologically verified that keloid fibroblasts had a higher level of Ca²⁺ influx than the control fibroblasts upon ionomycin stimulation. Via co-cultivation analysis, we found that human keloid fibroblasts could directly promote platelet aggregation. As suggested by PhosphoPath and gene set enrichment analysis, pFLNA was centered as the top phosphoproteins associated with keloid phenotypes. We validated that pFLNA was upregulated both in keloid fibroblasts and keloid tissue section, implicating its biomarker potential. In conclusion, we reported the first phosphoproteome on keloid fibroblasts, based on which we revealed that keloid fibroblasts had aberrant calcium homeostasis and could directly induce platelet aggregation.

From fuzziness to precision medicine: on the rapidly evolving proteomics with implications in mitochondrial connectivity to rare human disease

Mitochondrial (mt) dysfunction is linked to rare diseases (RDs) such as respiratory chain complex (RCC) deficiency, MELAS, and ARSACS. Yet, how altered mt protein networks contribute to these ailments remains understudied. In this perspective article, we identified 21 mt proteins from public repositories that associate with RCC deficiency, MELAS, or ARSACS, engaging in a relatively small number of protein-protein interactions (PPIs), underscoring the need for advanced proteomic and interactomic platforms to uncover the complete scope of mt connectivity to RDs. Accordingly, we discuss innovative untargeted label-free proteomics in identifying RD-specific mt or other macromolecular assemblies and mapping of protein networks in complex tissue, organoid, and stem cell-differentiated neurons. Furthermore, tag- and label-based proteomics, genealogical proteomics, and combinatorial affinity purification-mass spectrometry, along with advancements in detecting and integrating transient PPIs with single-cell proteomics and transcriptomics, collectively offer seminal follow-ups to enrich for RD-relevant networks, with implications in RD precision medicine.

Serum-Derived Exosomal Proteins as Potential Candidate Biomarkers for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common form of hepatic malignancies. The diagnosis of HCC remains challenging due to the low sensitivity and specificity of the diagnostic method. Exosomes, which are abundant in various proteins from parent cells, play pivotal roles in intercellular communication and have been confirmed as promising sources of disease biomarkers. Herein, we performed a simple but robust proteomic profiling on exosomes derived from 1 μL of serum using a data-independent acquisition (DIA) method for the first time, to screen potential biomarkers for the diagnosis of HCC. Ten pivotal differentially expressed proteins (DEPs) (von Willebrand factor (VWF), LGALS3BP, TGFB1, SERPINC1, HPX, HP, HBA1, FGA, FGG, and FGB) were screened as a potential candidate biomarker panel, which could completely discriminate patients with HCC from normal control (NC). Interestingly, Gene Expression Profiling Interactive Analysis (GEPIA) revealed that the expression levels of four genes increased and those of six genes decreased in HCC tissues compared with normal tissues, which were in concordance with protein expression levels. In conclusion, we screened 10 exosomal proteins holding promise for acting as a potential candidate biomarker panel for detection of HCC through a simple but robust proteomic profiling.

Integrating SWATH-MS Proteomics and Transcriptome Analysis Identifies CHI3L1 as a Plasma Biomarker for Early Gastric Cancer

Early diagnosis of gastric cancer (GC) provides patients opportunities for minimally invasive endoscopic resection. Here, we developed a new strategy integrated the state-of-the-art sequential windowed acquisition of all theoretical fragment ion (SWATH) mass spectra (MS) with multi-dataset joint analysis to screen for the stage-I GC plasma biomarker. In SWATH-MS assays, we identified 37 upregulated and 21 downregulated proteins in GC plasma. In the mRNA database analysis, 633 genes were identified as differentially expressed genes in at least 4 out of 5 datasets, but there were only 94 genes identified as upregulated. Only 1 gene, CHI3L1, was characterized as upregulated in both the dataset consensus list and the SWATH-MS list. Then, we detected the CHI3L1 level in the plasma of a large cohort consisting of 200 participants. The area under the ROC curve (AUC) of CHI3L1 in distinguishing GC from others was 0.788. Integrating the plasma CHI3L1 level with clinical factors further boosted the AUC to 0.887. In conclusion, we provide a novel strategy for biomarker screening, combining recent MS techniques with public database analysis, and identified plasma CHI3L1 as a potential biomarker for patients with endoscopically resectable GC.

Proteomic Analysis in Morquio A Cells Treated with Immobilized Enzymatic Replacement Therapy on Nanostructured Lipid Systems

Morquio A syndrome, or mucopolysaccharidosis type IVA (MPS IVA), is a lysosomal storage disease due to mutations in the N-acetylgalactosamine-6-sulfatase (GALNS) gene. Systemic skeletal dysplasia and the related clinical features of MPS IVA are due to disruption of cartilage and its extracellular matrix, leading to an imbalance of growth. Enzyme replacement therapy (ERT) with recombinant human GALNS, alpha elosulfase, provides a systemic treatment. However, this therapy has a limited impact on skeletal dysplasia because the infused enzyme cannot penetrate cartilage and bone. Therefore, an alternative therapeutic approach to reach the cartilage is an unmet challenge. We have developed a new drug delivery system based on a nanostructure lipid carrier with the capacity to immobilize enzymes used for ERT and to target the lysosomes. This study aimed to assess the effect of the encapsulated enzyme in this new delivery system, using in vitro proteomic technology. We found a greater internalization of the enzyme carried by nanoparticles inside the cells and an improvement of cellular protein routes previously impaired by the disease, compared with conventional ERT. This is the first qualitative and quantitative proteomic assay that demonstrates the advantages of a new delivery system to improve the MPS IVA ERT.

Clinical biomarker discovery by SWATH-MS based label-free quantitative proteomics: impact of criteria for identification of differentiators and data normalization method

BACKGROUND

SWATH-MS has emerged as the strategy of choice for biomarker discovery due to the proteome coverage achieved in acquisition and provision to re-interrogate the data. However, in quantitative analysis using SWATH, each sample from the comparison group is run individually in mass spectrometer and the resulting inter-run variation may influence relative quantification and identification of biomarkers. Normalization of data to diminish this variation thereby becomes an essential step in SWATH data processing. In most reported studies, data normalization methods used are those provided in instrument-based data analysis software or those used for microarray data. This study, for the first time provides an experimental evidence for selection of normalization method optimal for biomarker identification.

METHODS

The efficiency of 12 normalization methods to normalize SWATH-MS data was evaluated based on statistical criteria in 'Normalyzer'-a tool which provides comparative evaluation of normalization by different methods. Further, the suitability of normalized data for biomarker discovery was assessed by evaluating the clustering efficiency of differentiators, identified from the normalized data based on p-value, fold change and both, by hierarchical clustering in Genesis software v.1.8.1.

RESULTS

Conventional statistical criteria identified VSN-G as the optimal method for normalization of SWATH data. However, differentiators identified from VSN-G normalized data failed to segregate test and control groups. We thus assessed data normalized by eleven other methods for their ability to yield differentiators which segregate the study groups. Datasets in our study demonstrated that differentiators identified based on p-value from data normalized with Loess-R stratified the study groups optimally.

CONCLUSION

This is the first report of experimentally tested strategy for SWATH-MS data processing with an emphasis on identification of clinically relevant biomarkers. Normalization of SWATH-MS data by Loess-R method and identification of differentiators based on p-value were found to be optimal for biomarker discovery in this study. The study also demonstrates the need to base the choice of normalization method on the application of the data.

Integrated Tear Proteome and Metabolome Reveal Panels of Inflammatory-Related Molecules via Key Regulatory Pathways in Dry Eye Syndrome

Dry eye syndrome (DES) is a growing public health concern with a high global prevalence; however, the fundamental processes involved in its pathogenic mechanisms remain poorly understood. In the present study, we applied nanoscale liquid chromatography and quadrupole time-of-flight tandem mass spectrometry (nanoLC/Q-TOF-MS/MS) and ultraperformance LC/Q-TOF-MS/MS technologies on tear samples obtained from 18 dry eye patients and 19 healthy controls for integrated proteomic and metabolomic analyses. Overall, 1031 tear proteins were detected, while 190 proteins were determined to be significantly expressed in dry eye patients. Further functional analysis suggested that various biological processes were highly expressed and involved in the pathogenesis of DES, especially immune and inflammatory processes. In total, 156 named metabolites were identified, among which 34 were found to be significantly changed in dry eye patients. The results highlighted the key elements, especially inflammatory-related proteins and metabolites that played important roles in the development of DES. Further, the regulatory roles of primary pathways, including complement and coagulation cascades, glycolysis/gluconeogenesis, and amino acid metabolism, were also identified as processes involved in DES. Collectively, our work not only provided insight into the potential biomarkers of DES for diagnostic and prognostic purposes but extended our knowledge of the physiopathology of this syndrome.

Immunoproteomics Methods and Techniques

The varied landscape of the adaptive immune response is determined by the peptides presented by immune cells, derived from viral or microbial pathogens or cancerous cells. The study of immune biomarkers or antigens is not new, and classical methods such as agglutination, enzyme-linked immunosorbent assay, or Western blotting have been used for many years to study the immune response to vaccination or disease. However, in many of these traditional techniques, protein or peptide identification has often been the bottleneck. Recent progress in genomics and mass spectrometry have led to many of the rapid advances in proteomics approaches. Immunoproteomics describes a rapidly growing collection of approaches that have the common goal of identifying and measuring antigenic peptides or proteins. This includes gel-based, array-based, mass spectrometry-based, DNA-based, or in silico approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers. This review gives an overview of immunoproteomics and closely related technologies that are used to define the full set of protein antigens targeted by the immune system during disease.

Time-resolved proteomics of adenovirus infected cells

Viral infections cause large problems in the world and deeper understanding of the disease mechanisms is needed. Here we present an analytical strategy to investigate the host cell protein changes during human adenovirus type 2 (HAdV-C2 or Ad2) infection of lung fibroblasts by stable isotope labelling of amino acids in cell culture (SILAC) and nanoLC-MS/MS. This work focuses on early phase of infection (6 and 12 h post-infection (hpi)) but the data is combined with previously published late phase (24 and 36 hpi) proteomics data to produce a time series covering the complete infection. As many as 2169 proteins were quantitatively monitored from 6 to 36 hpi, while some proteins were time-specific. After applying different filter criteria, 2027 and 2150 proteins were quantified at 6 and 12 hpi and among them, 431 and 544 were significantly altered at the two time points. Pathway analysis showed that the De novo purine and pyrimidine biosynthesis, Glycolysis and Cytoskeletal regulation by Rho GTPase pathways were activated early during infection while inactivation of the Integrin signalling pathway started between 6 and 12 hpi. Moreover, upstream regulator analysis predicted MYC to be activated with time of infection and protein and RNA data for genes controlled by this transcription factor showed good correlation, which validated the use of protein data for this prediction. Among the identified phosphorylation sites, a group related to glycolysis and cytoskeletal reorganization were up-regulated during infection. The results show specific aspects on how the host cell proteins, the final products in the genetic information flow, are influenced by Ad2 infection, which would be overlooked if only knowledge derived from mRNA data is considered.

Biophysical, Biochemical, and Cell Based Approaches Used to Decipher the Role of Carbonic Anhydrases in Cancer and to Evaluate the Potency of Targeted Inhibitors

Carbonic anhydrases (CAs) are thought to be important for regulating pH in the tumor microenvironment. A few of the CA isoforms are upregulated in cancer cells, with only limited expression in normal cells. For these reasons, there is interest in developing inhibitors that target these tumor-associated CA isoforms, with increased efficacy but limited nonspecific cytotoxicity. Here we present some of the biophysical, biochemical, and cell based techniques and approaches that can be used to evaluate the potency of CA targeted inhibitors and decipher the role of CAs in tumorigenesis, cancer progression, and metastatic processes. These techniques include esterase activity assays, stop flow kinetics, and mass inlet mass spectroscopy (MIMS), all of which measure enzymatic activity of purified protein, in the presence or absence of inhibitors. Also discussed is the application of X-ray crystallography and Cryo-EM as well as other structure-based techniques and thermal shift assays to the studies of CA structure and function. Further, large-scale genomic and proteomic analytical methods, as well as cell based techniques like those that measure cell growth, apoptosis, clonogenicity, and cell migration and invasion, are discussed. We conclude by reviewing approaches that test the metastatic potential of CAs and how the aforementioned techniques have contributed to the field of CA cancer research.

Nasopharyngeal Carcinoma Protein Interaction Mapping Analysis via Proteomic Approaches

Nasopharyngeal carcinoma (NPC), although not very common in many parts of the world, is a major concern in some countries, including Iran. Molecular studies are very helpful to provide essential information regarding underlying carcinogenetic mechanisms. Here, considering NPC proteomic approaches, established biomarkers were designated for protein-protein interaction network construction and analysis with corresponding plug-ins. A network of reported protein markers was constructed and topological and biological process features were investigated. Centrality analysis showed that JUN, CALM1, HSB1, and SOD1 are more important than other differentially expressed proteins in an interacting pattern. What is more, by extending the network, Tp53, PRDM10, AKT1, ALB, HSP90AA1, and EGFR achieved the highest values for NPC network strength. It can be concluded that these proteins as well as their contributing processes, particularly in a second network, may be important for NPC onset and development. Targeting these candidate proteins may allow novel treatment approaches following appropriate validation.

Advances in endometrial cancer protein biomarkers for use in the clinic

INTRODUCTION

Endometrial cancer (EC) is the fourth most common cancer in women in developed countries. The identification of sensitive and specific biomarkers to improve early detection of EC is crucial for an appropriate management of this disease, in which 30% of patients are diagnosed only at advanced stages, which is associated with high levels of morbidity and mortality. Despite major efforts and investments made to identify EC biomarkers, no protein has yet reached the stage of clinical application. Areas covered: This review gathers the numerous candidate biomarkers for EC diagnosis proposed in proteomic studies published from 1978 to 2017. Additionally, we summarize limitations associated with the proteomic technologies and study designs employed in those articles. Finally, we address new perspectives in EC biomarker research, including the comprehensive knowledge of previously suggested candidate biomarkers in conjunction with novel mass spectrometry-based proteomic technologies with enhanced sensitivity and specificity not yet applied to EC studies and a directed clinical perspective in the study design. Expert commentary: These ingredients could be the recipe to accelerate the application of protein biomarkers in the clinic.

Data-Independent Mass Spectrometry Approach for Screening and Identification of DNA Adducts

Long-term exposures to environmental toxicants and endogenous electrophiles are causative factors for human diseases including cancer. DNA adducts reflect the internal exposure to genotoxicants and can serve as biomarkers for risk assessment. Liquid chromatography-multistage mass spectrometry (LC-MSn) is the most common method for biomonitoring DNA adducts, generally targeting single exposures and measuring up to several adducts. However, the data often provide limited evidence for a role of a chemical in the etiology of cancer. An "untargeted" method is required that captures global exposures to chemicals, by simultaneously detecting their DNA adducts in the genome; some of which may induce cancer-causing mutations. We established a wide selected ion monitoring tandem mass spectrometry (wide-SIM/MS2) screening method utilizing ultraperformance-LC nanoelectrospray ionization Orbitrap MSn with online trapping to enrich bulky, nonpolar adducts. Wide-SIM scan events are followed by MS2 scans to screen for modified nucleosides by coeluting peaks containing precursor and fragment ions differing by -116.0473 Da, attributed to the neutral loss of deoxyribose. Wide-SIM/MS2 was shown to be superior in sensitivity, specificity, and breadth of adduct coverage to other tested adductomic methods with detection possible at adduct levels as low as 4 per 109 nucleotides. Wide-SIM/MS2 data can be analyzed in a "targeted" fashion by generation of extracted ion chromatograms or in an "untargeted" fashion where a chromatographic peak-picking algorithm can be used to detect putative DNA adducts. Wide-SIM/MS2 successfully detected DNA adducts, derived from chemicals in the diet and traditional medicines and from lipid peroxidation products, in human prostate and renal specimens.

Detergent-Insoluble Proteome Analysis Revealed Aberrantly Aggregated Proteins in Human Preeclampsia Placentas

Preeclampsia (PE) is a placenta disease, featured by hypertension, proteinuria, and other multiorgan dysfunctions, and its etiology is unclear. We and others have shown that intensive endoplasmic reticulum (ER) stress and unfolded protein response (UPR) occur in the PE placenta. In this study, we isolated detergent-insoluble proteins (DIPs) from human placenta tissues, which were enriched with protein aggregates, to characterize the placenta UPR in PE. With data-independent acquisition (DIA) mass spectrometry, we identified 2066 DIPs across all normal (n = 10) and PE (n = 10) placenta samples, among which 110 and 108 DIPs were significantly up- and down-regulated in PE, respectively. Per clustering analysis, differential DIPs could generally distinguish PE from normal placentas. We verified the MS quantitation of endoglin and vimentin by immunoblotting. In addition, we observed that PE placenta tissues have remarkably more endoglin in the cytoplasm. Furthermore, we found that DIPs were evenly distributed across different chromosomes and could be enriched in diversified gene ontology terms, while differential DIPs avoided to distribute on X-chromosome. Significantly up-regulated DIPs in PE were focused on the top functions of lipid metabolism, while 23 of these DIPs could form the top network regulating cellular movement, development, growth, and proliferation. Our results implicate that human PE placentas have disease-relevant differential DIPs, which reflect aberrantly aggregated proteins of placental tissues. The mass spectrometry proteomics data have been deposited to ProteomeXchange consortium with the data set identifier PXD006654, and iProX database (accession number: IPX0000948000).