Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture

Advances in human papillomavirus detection for cervical cancer screening and diagnosis: challenges of conventional methods and opportunities for emergent tools

Human papillomavirus (HPV) infection is the main cause of cervical cancer and other cancers such as anogenital and oropharyngeal cancers. The prevention screening and treatment of cervical cancer has remained one of the top priorities of the World Health Organization (WHO). In 2020, the WHO came up with the 90-70-90 strategy aimed at eliminating cervical cancers as a public health problem by the year 2030. One of the key priorities of this strategy is the recommendation for countries to ensure that 70% of their women are screened using a high-performance test by the age of 35, and again by the age of 45. Over the years, several traditional methods (notably, Pap smear and nucleic acid-based techniques) have been used for the detection of cervical cancer. While these methods have significantly reduced the incidence of cervical cancer and death, they still come short of excellence for the total eradication of HPV infection. The challenges include low sensitivity, low specificity, poor reproducibility, the need for high-level specialists, and the high cost of access to the facilities, to mention a few. Interestingly, however, several efforts are being made today to mitigate these challenges. In this review, we discussed the pros and cons of the traditional screening and testing of HPV infections, the efforts being made to improve their performances, and the emergent tools (especially, the electrochemical methods) that promise to revolutionize the screening and testing of HPV infections. The main aim of the review is to provide some novel clues to researchers that would allow for the development of high-performance, affordable, and triage-suitable electrochemical-based diagnostic tools for HPV and cervical cancer.

Proteolysis Assays With Conserved or Aminofluorescein-Labeled Red Blood Cells

Backgrounds: Various physiological functions and reaction cascades, as well as disease progression in the living systems, are controlled by the activity of specific proteolytic enzymes. We conducted the study to evaluate protease activity by assessing peptide fragments from either conserved or labeled red blood cells (RBCs) with aminofluorescein (AF) in the reaction media. Methods: RBCs were incubated in media containing trypsin. Subsequently, the concentration of peptide fragments in the reaction media, resulted by the digestion with trypsin from conserved cells, was estimated by 3-(4-carboxybenzoyl)quinoline-2-carboxaldehyde (CBQCA) as an amine-reactive fluorogenic reagent. In a second approach, we conjugated AF to the conserved RBCs and then exposed AF-labeled RBCs to trypsin. This was followed by directly measuring the fluorescence intensity (FI) in the reaction media to estimate the concentration of AF-labeled peptide fragments resulting from the enzyme's activity. Results: Show a concentration- and time-dependent increase in FIs, reflecting the activity of trypsin as a proteolytic enzyme. The FIs increased significantly by 4 to 5 folds in samples treated with different enzyme concentrations, and by over 11 folds after 2 h incubation in media containing a 50 μL trypsin, as evidenced by CBQCA assays. Conclusion: These fast and affordable approaches could be applied with high reliability for the general estimation of protease activity in samples and customized for diagnostic purposes and prognostic evaluation in various diseases.

Biomarker-Based Precision Therapy for Alzheimer's Disease: Multidimensional Evidence Leading a New Breakthrough in Personalized Medicine

(1) Background: Alzheimer's disease (AD) is a worldwide neurodegenerative disorder characterized by the buildup of abnormal proteins in the central nervous system and cognitive decline. Since no radical therapy exists, only symptomatic treatments alleviate symptoms temporarily. In this review, we will explore the latest advancements in precision medicine and biomarkers for AD, including their potential to revolutionize the way we diagnose and treat this devastating condition. (2) Methods: A literature search was performed combining the following Medical Subject Heading (MeSH) terms on PubMed: "Alzheimer's disease", "biomarkers", "APOE", "APP", "GWAS", "cerebrospinal fluid", "polygenic risk score", "Aβ42", "τP-181", " p-tau217", "ptau231", "proteomics", "total tau protein", and "precision medicine" using Boolean operators. (3) Results: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with AD risk, while a transcriptomic analysis has revealed dysregulated gene expression patterns in the brains of individuals with AD. The proteomic and metabolomic profiling of biological fluids, such as blood, urine, and CSF, and neuroimaging biomarkers have also yielded potential biomarkers of AD that could be used for the early diagnosis and monitoring of disease progression. (4) Conclusion: By leveraging a combination of the above biomarkers, novel ultrasensitive immunoassays, mass spectrometry methods, and metabolomics, researchers are making significant strides towards personalized healthcare for individuals with AD.

Proteomic insights into mental health status: plasma markers in young adults

Global emphasis on enhancing prevention and treatment strategies necessitates an increased understanding of the biological mechanisms of psychopathology. Plasma proteomics is a powerful tool that has been applied in the context of specific mental disorders for biomarker identification. The p-factor, also known as the "general psychopathology factor", is a concept in psychopathology suggesting that there is a common underlying factor that contributes to the development of various forms of mental disorders. It has been proposed that the p-factor can be used to understand the overall mental health status of an individual. Here, we aimed to discover plasma proteins associated with the p-factor in 775 young adults in the FinnTwin12 cohort. Using liquid chromatography-tandem mass spectrometry, 13 proteins with a significant connection with the p-factor were identified, 8 of which were linked to epidermal growth factor receptor (EGFR) signaling. This exploratory study provides new insight into biological alterations associated with mental health status in young adults.

A single step and rapid protein extraction protocol developed for cell lines and tissues: Compatible for gel based and gel free proteomic approaches

Proteins are crucial research molecules in modern biology. Almost every biological research area needs protein-based assays to answer the research questions. The study of the total protein content of a biological sample known as Proteomics, is one of the highly rated qualitative and quantitative approach to address numerous biological problems including clinical research. The key step to successfully generate high quality proteomics data is the efficient extraction of proteins from biological samples. Although different methods are in use for protein extraction from a wide variety of samples, however, because of their prolonged protocol and multiple steps involved, final protein yield is sacrificed. Here, we have shown the development of a simple single step method for extraction of proteins from mammalian cell lines as well as tissue samples in an effective and reproducible manner. This method is based on lysis of samples directly in a modified lysis buffer without CHAPS (7 M Urea, 2 M Thiourea, and 10 mM Tris-Cl; pH 8.5) that is compatible with gel based and gel free approaches. This developed protocol is reliable and should be useful for a wide range of proteomic studies involving various biological samples.

Prognostic potential of miR-144 in various cancers: A meta-analysis

BACKGROUND

MicrorNA-144 (MiR-144) has been shown to be an attractive prognostic tumor biomarker and play a fundamental role in various cancers, However, the conclusion was inconsistency. The aim of this study was to identify the prognostic role of miR-144 in cancers.

METHODS

Relevant studies were searched in PubMed, EMBASE and Web of Science up to April 20, 2022. Hazard ratios (HR), odds ratio (OR) and 95% confidence intervals were pooled from the selected studies.

RESULTS

A total of 15 articles involving 1846 participants fulfilled the inclusion criteria. The results revealed that low miR-144 expression was significantly associated with favorable overall survival (HR: 0.68, 95% confidence interval [CI]: 0.53-0.88) in various cancers. Low miR-144 expression had better predictive value in patients with urinary system cancer (HR: 0.48, 95% CI: 0.35-0.64). In addition, low miR-144 expression was associated with tumor diameter (big vs small) (OR: 1.69, 95% CI: 1.08-2.75), tumor stage (III-IV vs I-II) (OR: 2.52, 95% CI: 3.76-8.14) and invasion depth (T3 + T4 vs T2 + T1) (OR: 3.24, 95% CI: 1.72-4.89).

CONCLUSION

miR-144 may serve as a prognostic biomarker in cancers.

Diagnostic value of platelet-to-lymphocyte ratio in patients with solitary pulmonary nodules

Introduction

Nodules detected in the lung parenchyma should be considered as malignant until proven otherwise, and the necessary tests should be performed for diagnosis.

Aim

To calculate the preoperative platelet-to-lymphocyte ratio (PLR) in patients with malignant lung nodules and to investigate the diagnostic value of this ratio in determining the histopathology of the nodule.

Material and methods

Ninety-one patients who were operated on for a malignant nodule in the lung between September 2010 and September 2020 were included in the study. The PLR was calculated by dividing the absolute platelet count by the absolute lymphocyte count. These values were compared with the histopathological diagnoses of the resected tumor tissue. Patients with primary lung malignancy were classified as group 1 (n = 54), and lung metastases of other organs were classified as group 2 (n = 37).

Results

The mean PLR was 127.27 ±46.82 in the first group and 183.56 ±93.49 in the second group. There was a statistically significant difference in PLR values between the two groups, and PLR was higher in group 2. There was no statistically significant difference between the two groups in terms of lymph node positivity, nodule size and SuvMax values. A moderately strong, significant and same-sided correlation was observed between nodule size and SuvMax values in the first group of patients (r = 0.48, p = 0.001)

Conclusions

PLR values less than 89.41 indicate that the histopathological result may be a lung-derived malignancy. However, in cases where the PLR is detected above 165.6, it would be appropriate to interpret another previously detected malignancy as metastasis to the lung.

Overexpression of macrophage-colony stimulating factor-1 receptor as a prognostic factor for survival in cancer: A systematic review and meta-analysis

BACKGROUND

The relation between the expression of macrophage-colony stimulating factor-1 receptor (CSF-1R) and prognosis of cancer patients has been evaluated in multiple studies, but the results remain controversial. We, therefore, performed a meta-analysis and systematic review to figure out the role of CSF-1R in the prognosis of patients with cancer.

METHODS

Several databases were searched, including Web of Science, PubMed, and EMBASE. All human studies were published as full text. The Newcastle-Ottawa risk of bias scale was applied to evaluate the research. We extracted hazard ratios (HRs) with 95% confidence interval (95% CI) which assessed progression-free survival (PFS) and overall survival (OS) in order to assess the impacts of CSF-1R on the prognosis of cancer patients.

RESULTS

A total of 12 citations were identified, with studies including 2260 patients in different cancer types that met the eligibility criteria. It was suggested in a pooled analysis that the over-expression of CSF-1R was significantly related to worse PFS (HR: 1.68; P < .001, 1.25-2.10, 95% CI) and also poorer OS (HR=1.28; P < .001, 1.03-1.54, 95% CI). Analysis in subgroups indicated over-expressed CSF-1R was significantly associated with worse OS in hematological malignancy (HR = 2.29; P < .001, 1.49-3.09, 95% CI; model of fixed-effects; I2 = 0.0%, P < .001). Sensitivity analysis suggested that there was no study influencing the stability of the results.

CONCLUSIONS

The overexpression of CSF-1R was significantly predictive of worse prognosis in those who suffer from different kinds of malignancies, particularly in hematological malignancy, which indicates that it might be a potential biomarker of prognosis in cancer survival and a potential molecular target in the treatment of malignant tumors.

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

Sequences of the genomes of all-important bacterial pathogens of man, plants, and animals have been completed. Still, it is not enough to achieve complete information of all the mechanisms controlling the biological processes of an organism. Along with all advances in different proteomics technologies, proteomics has completed our knowledge of biological processes all around the world. Proteomics is a valuable technique to explain the complement of proteins in any organism. One of the fields that has been notably benefited from other systems approaches is bacterial pathogenesis. An emerging field is to use proteomics to examine the infectious agents in terms of, among many, the response the host and pathogen to the infection process, which leads to a deeper knowledge of the mechanisms of bacterial virulence. This trend also enables us to identify quantitative measurements for proteins extracted from microorganisms. The present review study is an attempt to summarize a variety of different proteomic techniques and advances. The significant applications in bacterial pathogenesis studies are also covered. Moreover, the areas where proteomics may lead the future studies are introduced.

Prognostic and Clinicopathological Significance of MUC Family Members in Colorectal Cancer: A Systematic Review and Meta-Analysis

Objective

To assess the association between MUC expression levels in colorectal cancer (CRC) tissues and prognosis and investigate the associations between MUC expression levels and CRC clinicopathological characteristics.

Methods

The PubMed, Embase, Cochrane Library, and Web of Science databases were searched from inception through September 13, 2019, to identify studies investigating the association between MUC expression levels in CRC tissues and prognosis. Pooled hazard ratios (HRs) or odds ratio (ORs) with 95% confidence intervals (CIs) were used to evaluate associations between MUC expression levels and prognosis or clinicopathological characteristics, respectively. The heterogeneity between studies was assessed by the I² values, whereas the likelihood of publication bias was assessed by Egger's linear regression and Begg's rank correlation test.

Results

Among 33 included studies (n = 6032 patients), there were no associations between combined MUC phenotype expression levels and overall survival (OS) or disease-free survival (DFS)/relapse-free survival (RFS) in patients with CRC. In subgroup analyses, the upregulated MUC1 expression (HR = 1.50; 95% CI, 1.29–1.74; P < 0.00001) was associated with poor OS. However, the upregulated MUC2 expression (HR = 0.64; 95% CI, 0.52–0.79; P < 0.00001) was associated with better OS. Furthermore, a high level of MUC1 expression (HR = 1.99; 95% CI, 0.99–3.99; P = 0.05) was associated with shorter DFS/RFS. However, patients with a low level of MUC2 tumors showed better DFS/RFS than patients with a high level of MUC2 tumors (HR = 0.71; 95% CI, 0.49–1.04; P = 0.08; P = 0.0.009, I² = 67%) and MUC5AC expression (HR = 0.56; 95% CI, 0.38–0.82; P = 0.003) was associated with longer DFS/RFS. In addition, a high level of MUC1 expression was associated with CRC in the rectum, deeper invasion, lymph node metastasis, distant metastasis, advanced tumor stage, and lymphatic invasion. A high level of MUC2 expression had a protective effect. High secretion of MUC5AC is associated with colon cancer compared with rectal cancer.

Conclusion

The protein expression of MUC1 might be a poor biomarker in colorectal cancer and might play a role in tumor transformation and metastasis. However, the protein expression of MUC2 expression might have a protective effect. Furthermore, randomized controlled trials (RCTs) of large patients are needed to confirm the results.

Prognostic and clinicopathological value of MUC1 expression in colorectal cancer: A meta-analysis

BACKGROUND

Accumulating evidence supports the overexpression of mucin 1 (MUC1) in colorectal cancer (CRC), but the value of elevated MUC1 expression remains controversial. Here, we evaluated the prognostic and clinicopathological value of MUC1 expression in CRC.

MATERIALS AND METHODS

The Web of Science, PubMed, Embase, Cochrane Library, and Wanfang databases, as well as the China Biology Medicine disc (CBMdisc) and China National Knowledge Infrastructure (CNKI) were searched for studies on MUC1 expression and prognosis of CRC through July 20, 2018. The pooled relative risks (RRs) and hazard ratios (HRs) with 95% confidence intervals (95% CIs) were calculated to evaluate the prognostic and clinicopathological value of MUC1 expression in CRC. The Revman version 5.3 package and STATA, version 12 were employed for pooled analysis and analysis of publication bias.

RESULTS

This meta-analysis included 16 published studies. The combined analysis showed that CRC patients with high MUC1 expression had a worse clinical outcome in overall survival (OS) (HR = 1.51, 95% CI = 1.30-1.75, P <.00001). In addition, high MUC1 expression was associated with higher TNM stage (RR = 1.44, 95% CI = 1.17-1.77, P = .0007), greater depth of invasion (RR = 1.30, 95% CI = 1.10-1.53, P = .002), and lymph node metastasis (RR = 1.47, 95% CI = 1.20-1.80, P = .0002) of CRC. However, the elevated MUC1 expression was not related to disease-free survival/recurrence-free survival (DFS/RFS) (HR = 1.51, 95% CI = 0.78-2.89, P = .22), histological grade (RR = 1.15, 95% CI = 0.96-1.38, P = .12), gender (RR = 0.95; 95% CI = 0.83-1.08, P = .44), tumor size (RR = 1.11, 95% CI = 0.85-1.44, P = .44), tumor site (RR = 1.01, 95% CI = 0.88-1.16, P = .84), or mucinous component (RR = 0.83, 95% CI = 0.60-1.14, P = .24) in CRC.

CONCLUSION

Our findings indicated that high MUC1 expression represents a marker of poor prognosis in CRC. Meanwhile, elevated MUC1 expression was associated with advanced TNM stage, greater depth of invasion, and lymph node metastasis.

Proteomic profile of TGF-β1 treated lung fibroblasts identifies novel markers of activated fibroblasts in the silica exposed rat lung

We performed liquid chromatography-tandem mass spectrometry (LC-MS/MS) on control and TGF-β1-exposed rat lung fibroblasts to identify proteins differentially expressed between cell populations. A total of 196 proteins were found to be differentially expressed in response to TGF-β1 treatment. Guided by these results, we next determined whether similar changes in protein expression were detectable in the rat lung after chronic exposure to silica dust. Of the five proteins selected for further analysis, we found that levels of all proteins were markedly increased in the silica-exposed rat lung, including the proteins for the very low density lipoprotein receptor (VLDLR) and the transmembrane (type I) heparin sulfate proteoglycan called syndecan 2 (SDC2). Because VLDLR and SDC2 have not, to our knowledge, been previously linked to the pathobiology of silicosis, we next examined whether knockdown of either gene altered responses to TGF-β1 in MRC-5 lung fibroblasts. Interestingly, we found knockdown of either VLDLR or SDC2 dramatically reduced collagen production to TGF-β1, suggesting that both proteins might play a novel role in myofibroblast biology and pathogenesis of silica-induced pulmonary fibrosis. In summary, our findings suggest that performing LC-MS/MS on TGF-β1 stimulated lung fibroblasts can uncover novel molecular targets of activated myofibroblasts in silica-exposed lung.

Prognostic significance of galectin-1 expression in patients with cancer: a meta-analysis

Background

The prognostic significance of galectin-1 (Gal-1) expression in cancerous patients has been assessed for several years while the results remain controversial. Thus, we performed the first comprehensive meta-analysis to evaluate the prognostic value of Gal-1 expression in cancerous patients.

Methods

We searched Pubmed, Embase and Web of Science to recruit studies on the prognostic impact of Gal-1 expression in cancerous patients. Eighteen studies containing 2674 patients were involved in this meta-analysis until March 30, 2018. Pooled hazard ratios (HRs) with 95% confidence interval (95% CI) were calculated to estimate the effect using random-effects model.

Results

The pooled results revealed that high Gal-1 expression in cancer tissue associated with a poor OS (HR = 1.79, 95% CI 1.54–2.08, P < 0.001). In the subgroup of tumor type, it’s observed that high Gal-1 expression was significant correlated with poor OS in digestive cancers without heterogeneity (HR = 1.94, 95% CI 1.64–2.30, P < 0.001; fixed-effects model; I² = 20.1%, P = 0.276).

Conclusions

Our present meta-analysis indicates that high Gal-1 expression might be a predictive factor of poor prognosis in cancers, particularly in digestive cancers.

Assessment of cellular and serum proteome from tongue squamous cell carcinoma patient lacking addictive proclivities for tobacco, betel nut, and alcohol: Case study

The intriguing molecular pathways involved in oral carcinogenesis are still ambiguous. The oral squamous cell carcinoma (OSCC) ranks as the most common type constituting more than 90% of the globally diagnosed oral cancers cases. The elevation in the OSCC incidence rate during past 10 years has an alarming impression on human healthcare. The major challenges associated with OSCC include delayed diagnosis, high metastatic rates, and low 5-year survival rates. The present work foundations on reverse genetic strategy and involves the identification of genes showing expressional variability in an OSCC case lacking addictive proclivities for tobacco, betel nut, and/or alcohol, major etiologies. The expression modulations in the identified genes were analyzed in 16 patients comprising oral pre-cancer and cancer histo-pathologies. The genes SCCA1 and KRT1 were found to down regulate while DNAJC13, GIPC2, MRPL17, IG-Vreg, SSFA2, and UPF0415 upregulated in the oral pre-cancer and cancer pathologies, implicating the genes as crucial players in oral carcinogenesis.

Prognostic Value of MUC2 Expression in Colorectal Cancer: A Systematic Review and Meta-Analysis

Background

The reliability of MUC2 as a prognostic marker in colorectal cancer (CRC) is controversial. This study evaluated the association between MUC2 expression levels in CRC tissues and prognosis.

Methods

The PubMed, Web of Science, Embase, Cochrane Library, China Biology Medicine disc (CBMdisc), Wanfang Database, and China National Knowledge Infrastructure (CNKI) databases were searched to identify studies exploring the relationship between MUC2 expression in CRC tissues and overall survival (OS). Pooled hazard ratios (HRs) and risk ratios (RRs) with 95% confidence intervals (CIs) were used to evaluate the associations between MUC2 expression levels and prognosis and MUC2 expression levels and CRC clinicopathological characteristics, respectively.

Results

The meta-analysis included 11 studies (2619 patients). Low MUC2 expression level was significantly associated with poor OS (HR, 1.67; 95% CI, 1.43–1.94; P < 0.00001) and disease-free survival (DFS)/recurrence-free survival (RFS) (HR, 1.60; 95% CI, 1.21–2.12; P = 0.001) in patients with CRC. Low MUC2 expression level was associated with advanced TNM stage (RR, 1.42; 95% CI, 1.26–1.60; P < 0.00001), lymph node metastasis (RR, 1.41; 95% CI, 1.25–1.60; P < 0.00001), lymphatic invasion (RR,1.64; 95% CI, 1.26–2.12; P = 0.0002), rectal tumor site (RR, 1.26; 95% CI, 1.09–1.46; P = 0.001), and large tumor size (RR,1.32; 95% CI, 1.02–1.70; P = 0.03). There were no associations between low MUC2 expression level and gender, histological grade, depth of invasion, and distant metastasis.

Conclusion

The low levels of MUC2 in CRC tissues are poor prognostic factor independent of stage or other well-recognized markers of later-stage disease. Large well-designed cohort studies are required to validate MUC2 as a biomarker for poor prognosis in CRC.

Proteomics Analysis of Blood Serums from Alzheimer's Disease Patients Using iTRAQ Labeling Technology

Alzheimer' disease (AD) is the most common form of dementia affecting up to 6% of the population over the age of 65. In order to discover differentially expressed proteins that might serve as potential biomarkers, the serums from AD patients and healthy controls were compared and analyzed using the proteomics approach of isobaric tagging for relative and absolute quantitation (iTRAQ). For the first time, AD biomarkers in serums are investigated in the Han Chinese population using iTRAQ labeled proteomics strategy. Twenty-two differentially expressed proteins were identified and out of which nine proteins were further validated with more sample test. Another three proteins that have been reported in the literature to be potentially associated with AD were also investigated for alteration in expression level. Functions of those proteins were mainly related to the following processes: amyloid-β (Aβ) metabolism, cholesterol transport, complement and coagulation cascades, immune response, inflammation, hemostasis, hyaluronan metabolism, and oxidative stress. These results support current views on the molecular mechanism of AD. For the first time, differential expression of zinc-alpha-2-glycoprotein (AZGP1), fibulin-1 (FBLN1), platelet basic protein (PPBP), thrombospondin-1 (THBS1), S100 calcium-binding protein A8 (S100A8), and S100 calcium-binding protein A9 (S100A9) were detected in the serums of AD patients compared with healthy controls. These proteins might play a role in AD pathophysiology and serve as potential biomarkers for AD diagnosis. Specifically, our results strengthened the crucial role of Aβ metabolism and blood coagulation in AD pathogenesis and proteins related to these two processes may be used as peripheral blood biomarkers for AD.

Serum proteomics study reveals candidate biomarkers for systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease which is characterized by the presence of autoantibodies. It will be helpful if specific serum biomarkers can be used for monitoring the disease activity as well as differentiating SLE from other diseases. For this purpose, we used a label free-based two dimensional liquid chromatography mass spectrometry platform to analyze serum samples from SLE patients in active or inactivestage. Significant differences were found for 42 serum proteins implicated in pathways including complement and coagulation cascades. Further gene set enrichment analysis revealed that gene sets including formation of fibrin clot, ECM glycoproteins and innate immune system were highly correlated with the SLE disease activity. To further assess the validity of these findings, thrombospondin-4 was selected for subsequent ELISA assays. We also explored the autoantibody of three candidate biomarkers in larger cohorts including SLE, Rheumatoid arthritis, Sjogrensyndrome patients and normal controls. Our findings provided valuable information on the proteomic changes in the serum of different SLE disease activity. Serum properdin, collectin-11 and thrombospondin-4 were valuable in monitoring the disease activity of SLE, and the autoantibodies to them may be valuable in differentiating SLE from other diseases for clinical diagnosis in the future.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Analysis of Reproducibility of Proteome Coverage and Quantitation Using Isobaric Mass Tags (iTRAQ and TMT)

This study aimed to compare the depth and reproducibility of total proteome and differentially expressed protein coverage in technical duplicates and triplicates using iTRAQ 4-plex, iTRAQ 8-plex, and TMT 6-plex reagents. The analysis was undertaken because comprehensive comparisons of isobaric mass tag reproducibility have not been widely reported in the literature. The highest number of proteins was identified with 4-plex, followed by 8-plex and then 6-plex reagents. Quantitative analyses revealed that more differentially expressed proteins were identified with 4-plex reagents than 8-plex reagents and 6-plex reagents. Replicate reproducibility was determined to be ≥69% for technical duplicates and ≥57% for technical triplicates. The results indicate that running an 8-plex or 6-plex experiment instead of a 4-plex experiment resulted in 26 or 39% fewer protein identifications, respectively. When 4-plex spectra were searched with three software tools-ProteinPilot, Mascot, and Proteome Discoverer-the highest number of protein identifications were obtained with Mascot. The analysis of negative controls demonstrated the importance of running experiments as replicates. Overall, this study demonstrates the advantages of using iTRAQ 4-plex reagents over iTRAQ 8-plex and TMT 6-plex reagents, provides estimates of technical duplicate and triplicate reproducibility, and emphasizes the value of running replicate samples.

Proteomics and peptidomics: moving toward precision medicine in urological malignancies

Urological malignancies are a major cause of morbidity and mortality worldwide. Advances in early detection, diagnosis, prognosis and prediction of treatment response can significantly improve patient care. Proteomic and peptidomic profiling studies are at the center of kidney, prostate and bladder cancer biomarker discovery and have shown great promise for improved clinical assessment. Mass spectrometry (MS) is the most widely employed method for proteomic and peptidomic analyses. A number of MS platforms have been developed to facilitate accurate identification of clinically relevant markers in various complex biological samples including tissue, urine and blood. Furthermore, protein profiling studies have been instrumental in the successful introduction of several diagnostic multimarker tests into the clinic. In this review, we will provide a brief overview of high-throughput technologies for protein and peptide based biomarker discovery. We will also examine the current state of kidney, prostate and bladder cancer biomarker research as well as review the journey toward successful clinical implementation.

Differential Neuroproteomic and Systems Biology Analysis of Spinal Cord Injury

Acute spinal cord injury (SCI) is a devastating condition with many consequences and no known effective treatment. Although it is quite easy to diagnose traumatic SCI, the assessment of injury severity and projection of disease progression or recovery are often challenging, as no consensus biomarkers have been clearly identified. Here rats were subjected to experimental moderate or severe thoracic SCI. At 24h and 7d postinjury, spinal cord segment caudal to injury center versus sham samples was harvested and subjected to differential proteomic analysis. Cationic/anionic-exchange chromatography, followed by 1D polyacrylamide gel electrophoresis, was used to reduce protein complexity. A reverse phase liquid chromatography-tandem mass spectrometry proteomic platform was then utilized to identify proteome changes associated with SCI. Twenty-two and 22 proteins were up-regulated at 24 h and 7 day after SCI, respectively; whereas 19 and 16 proteins are down-regulated at 24 h and 7 day after SCI, respectively, when compared with sham control. A subset of 12 proteins were identified as candidate SCI biomarkers - TF (Transferrin), FASN (Fatty acid synthase), NME1 (Nucleoside diphosphate kinase 1), STMN1 (Stathmin 1), EEF2 (Eukaryotic translation elongation factor 2), CTSD (Cathepsin D), ANXA1 (Annexin A1), ANXA2 (Annexin A2), PGM1 (Phosphoglucomutase 1), PEA15 (Phosphoprotein enriched in astrocytes 15), GOT2 (Glutamic-oxaloacetic transaminase 2), and TPI-1 (Triosephosphate isomerase 1), data are available via ProteomeXchange with identifier PXD003473. In addition, Transferrin, Cathepsin D, and TPI-1 and PEA15 were further verified in rat spinal cord tissue and/or CSF samples after SCI and in human CSF samples from moderate/severe SCI patients. Lastly, a systems biology approach was utilized to determine the critical biochemical pathways and interactome in the pathogenesis of SCI. Thus, SCI candidate biomarkers identified can be used to correlate with disease progression or to identify potential SCI therapeutic targets.

Identification of HSPA8 as a candidate biomarker for endometrial carcinoma by using iTRAQ-based proteomic analysis

Although there are advances in diagnostic, predictive, and therapeutic strategies, discovering protein biomarker for early detection is required for improving the survival rate of the patients with endometrial carcinoma. In this study, we identify proteins that are differentially expressed between the Stage I endometrial carcinoma and the normal pericarcinous tissues by using isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis. Totally, we screened 1,266 proteins. Among them, 103 proteins were significantly overexpressed, and 30 were significantly downexpressed in endometrial carcinoma. Using the bioinformatics analysis, we identified a list of proteins that might be closely associated with endometrial carcinoma, including CCT7, HSPA8, PCBP2, LONP1, PFN1, and EEF2. We validated the gene overexpression of these molecules in the endometrial carcinoma tissues and found that HSPA8 was most significantly upregulated. We further validated the overexpression of HSPA8 by using immunoblot analysis. Then, HSPA8 siRNA was transferred into the endometrial cancer cells RL-95-2 and HEC-1B. The depletion of HSPA8 siRNAs significantly reduced cell proliferation, promoted cell apoptosis, and suppressed cell growth in both cell lines. Taken together, HSPA8 plays a vital role in the development of endometrial carcinoma. HSPA8 is a candidate biomarker for early diagnosis and therapy of Stage I endometrial carcinoma.

Quantitative proteomics study of the neuroprotective effects of B12 on hydrogen peroxide-induced apoptosis in SH-SY5Y cells

B12 belongs to the coumarin class of compounds that have been shown to have various physiological and pharmacological activities including anti-inflammatory, antibacterial, and antioxidant. In the present study, we characterised the neuroprotective effects of B12 against H₂O₂-induced neuronal cell damage in SH-SY5Y cells. Protein expression profiling in combination with pathway analysis was deployed to investigate the molecular events associated with the neuroprotective effects in human neuronal cells using a label-free quantitative proteomics approach. A total of 22 proteins were significantly differentially expressed in H₂O₂-damaged cells with or without B12 treatment. Bioinformatics analysis using the Cytoscape platform indicated that poly pyrimidine tract binding protein 1 (PTBP1) was highly associated with the protective effect, and western blotting verified that PTBP1 was up-regulated in H₂O₂ + B12 treatment group, compared with the H₂O₂ treated group. PTBP RNAi experiments knocked down PTBP expression, which cancelled out the protective effect of B12 on cell viability. Thus, we infer that B12 neuroprotective activity involves up-regulation of PTBP1 and its associated signalling networks following H₂O₂-induced apoptosis in SH-SY5Y cells. B12 or related compounds may prove to be useful therapeutic agents for the treatment of neurodegenerative diseases such as Alzheimer’s and Parkinson’s.

Proteomics in the Assessment of the Therapeutic Response of Antineoplastic Drugs: Strategies and Practical Applications

Uncovering unknown pathological mechanisms and body response to applied medication are the driving forces toward personalized medicine. In this post-genomic era, all eyes are turned to the proteomics field, searching for answers and explanations by investigating the gene end point functional units-proteins and their proteoforms. The development of cutting-edge mass spectrometric technologies and bioinformatics tools have allowed the life-science community to discover disease-specific proteins as biomarkers, which are often concealed by high sample complexity and dynamic range of abundance. Currently, there are several proteomics-based approaches to investigate the proteome. This chapter focuses on gold standard proteomics strategies and related issues toward candidate biomarker discovery, which may have diagnostic/prognostic as well as mechanistic utility in cancer drug resistance.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Prognostic Significance of Mucin Antigen MUC1 in Various Human Epithelial Cancers: A Meta-Analysis

Accumulating evidence indicates that mucin antigen MUC1 plays a fundamental role in the initiation and progression of several types of epithelial carcinomas. However, whether the expression of MUC1 on tumor cells is associated with patients' survival remains controversial. Medline/PubMed, EMBASE, the Cochrane Library, Chinese National Knowledge Infrastructure (CNKI) databases, and Grey literature were searched up to 15 August 2015 for eligible studies of the association between the MUC1 expression and overall survival (OS) in various epithelial cancers. The hazard ratio (HR) and its 95% confidence interval (CI) were calculated from the included studies. Moreover, the odds ratio (OR) was also extracted to evaluate the association between the clinicopathological parameters of participants and MUC1 expression. A total of 3425 patients covering 23 studies were included in the analysis. The pooled results showed that positive MUC1 staining was a negative predictor of OS (HRFEM = 1.98,95% CIFEM: 1.76-2.22, PFEM = 0.479; HRREM = 2.16,95% CIREM: 1.58-2.94, PREM = 0.355) in various epithelial carcinomas. Subgroup analysis revealed that the increased MUC1 expression was significantly associated with poor OS in patients with gastric cancer (HRFEM = 2.12, 95%CIFEM: 1.75-2.57, PFEM = 0.359; HRREM = 1.89, 95% CIREM: 1.05-3.41, PREM = 0.238), colorectal cancer (HRFEM = 1.73, 95%CIFEM: 1.41-2.13, PFEM = 0.048; HRREM = 2.00,95% CIREM: 1.46-2.73, PREM = 0.019), cholangiocarcinoma (HRFEM = 2.52, 95% CIFEM: 1.42-4.49, PFEM = 0.252; HRREM = 2.34, 95% CIREM: 1.30-4.22, PREM = 0.244), and nonsmall cell lung cancer (NSCLC) (HRFEM = 2.14, 95% CIFEM: 1.46-3.14, PFEM = 0.591; HRREM = 2.81, 95% CIREM: 1.40-5.64, PREM = 0.280). In addition, MUC1 overexpression was more likely to be found in colorectal cancer patients with an advanced tumor node metastasis stage (ORREM = 1.55, 95% CIREM: 1.06-2.27; PREM = 0.187) and in gastric cancer patients with positive lymph node metastasis (ORREM = 2.37, 95% CIREM: 1.19-4.73; PREM = 0.004) and intestinal-type classification (ORREM = 2.34, 95% CIREM: 1.59-3.45; PREM = 0.767). Our findings provide evidence that MUC1 detection has a prognostic value in patients with epithelial-originated cancers, especially in NSCLC and gastrointestinal cancers.

Classification of Samples with Order-Restricted Discriminant Rules

In recent years, mass spectrometry techniques have helped proteomics to become a powerful tool for the early diagnosis of cancer, as they help to discover protein profiles specific to each pathological state. One of the questions where proteomics is giving useful practical results is that of classifying patients into one of the possible severity levels of an illness, based on some features measured on the patient. This classification is usually made using one of the many discrimination procedures available in statistical literature. We present in this chapter recently developed restricted discriminant rules that use additional information in terms of orderings on the means, and we illustrate how to apply them to mass spectrometry data using R package dawai. Specifically, we use proteomic prostate cancer data, and we describe all steps needed, including data preprocessing and feature extraction, to build a discriminant rule that classifies samples in one of several disease stages, thus helping diagnosis. The restricted discriminant rules are compared with some standard classifiers that do not take into account the additional information, showing better performance in terms of error rates.

Prognostic Role of MicroRNA-200c-141 Cluster in Various Human Solid Malignant Neoplasms

The miR-200 family has emerged recently as a noticeable marker for predicting cancer prognosis and tumor progression. We aimed to review the evidence of miR-200c-141 genomic cluster as prognostic biomarkers in cancers. The results suggested that high level of miR-200c had no significant impact on OS (HR = 1.14 [0.77-1.69], P = 0.501) and DFS/PFS (HR = 0.72 [0.45-1.14], P = 0.161). Stratified analyses revealed that high miR-200c expression was significantly related to poor OS in serum/plasma (HR = 2.12 [1.62-2.77], P = 0.000) but not in tissues (HR = 0.89 [0.58-1.37], P = 0.599). High miR-200c expression was significantly associated with favorable DFS/PFS in tissues (HR = 0.56 [0.43-0.73], P = 0.000) but worse DFS/PFS in serum/plasma (HR = 1.90 [1.08-3.36], P = 0.027). For miR-141, we found that high miR-141 expression predicted no significant impact on OS (HR = 1.18 [0.74-1.88], P = 0.482) but poor DFS/PFS (HR = 1.11 [1.04-1.20], P = 0.003). Similarly, subgroup analyses showed that high miR-141 expression predicted poor OS in serum/plasma (HR = 4.34 [2.30-8.21], P = 0.000) but not in tissues (HR = 1.00 [0.92-1.09], P = 0.093). High miR-141 expression was significantly associated with worse DFS/PFS in tissues (HR = 1.12 [1.04-1.20], P = 0.002) but not in serum/plasma (HR = 0.90 [0.44-1.83], P = 0.771). Our findings indicated that, compared to their tissue counterparts, the expression level of miR-200c and miR-141 in peripheral blood may be more effective for monitoring cancer prognosis. High miR-141 expression was better at predicting tumor progression than survival for malignant tumors.

Elevated GAPDH expression is associated with the proliferation and invasion of lung and esophageal squamous cell carcinomas

Glyceraldehyde-3-phosphate dehydrogenase, is one of the most investigated housekeeping genes and widely used as an internal control in analysis of gene expression levels. The present study was designed to assess whether GAPDH is associated with cancer cell growth and progression and, therefore may not be a good internal control in cancer research. Our results from clinical tissue studies showed that the levels of GAPDH protein were significantly up-regulated in lung squamous cell carcinoma tissues, compared with the adjacent normal lung tissues, and this was confirmed by western blotting and immunohistochemistry. GAPDH knockdown by siRNA resulted in significant reductions in proliferation, migration, and invasion of lung squamous carcinoma cells in vitro. In a nude mouse cancer xenograft model, GAPDH knockdown significantly inhibited the cell proliferation and migration/invasion in vivo. In summary, GAPDH may not be an appropriate internal control for gene expression studies, especially in cancer research. The role of GAPDH in cancer development and progression should be further examined in pre-clinical and clinical studies.

Prognostic Role of MicroRNA-126 for Survival in Malignant Tumors: A Systematic Review and Meta-Analysis

Background. Increasing studies found that miR-126 expression may be associated with the prognosis of cancers. Here, we performed a meta-analysis to assess the prognostic role of miR-126 in different cancers. Methods. Eligible studies were identified by searching in PubMed, Embase, the Cochrane Library, CNKI, and Wan Fang databases up to March 2015. Pooled hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) were calculated to investigate the correlation between miR-126 and survival of cancers. Results. Thirty studies including a total of 4497 participants were enrolled in this meta-analysis. The pooled results showed that high level of miR-126 was a predictor for favorable survival of carcinomas, with pooled HR of 0.77 (95% CI 0.64–0.93) for OS, 0.64 (95%CI 0.48–0.85) for DFS, and 0.70 (95% CI 0.50–0.98) for PFS/RFS/DSS. However, high level of circulating miR-126 predicted a significantly worse OS in patients with cancer (HR = 1.65, 95% CI 1.09–2.51). Conclusions. Our results indicated that miR-126 could act as a significant biomarker in the prognosis of various cancers.

Prognostic value of melanoma cell adhesion molecule expression in cancers: a meta-analysis

Melanoma cell adhesion molecule (MACM) has been reported in many studies as a novel bio-marker for its prognosis value in cancers. But the prognosis significance of MACM expression in cancer remains inconclusive. Therefore, we conducted a system review and meta-analysis to assess its prognosis value in cancers. A systematic search through Pubmed, EMBASE and Cochran Library database was conducted. Hazard Ratios (HRs) and 95% confidence intervals (CIs) were used to evaluate the prognosis value of MACM expression. Eleven studies with 2657 cases were included after sorting out 462 articles for this meta-analysis. The results of the fixed-model depending on the heterogeneity in studies demonstrated that MACM expression was significantly associated with overall survival (OS) in cancer (HR=2.84, 95% CI: 1.10-7.31, P<0.00001). Furthermore, subgroup analysis indicated that high expressed MACM predicted a poor OS in both Asian (HR=2.52, 95% CI: 1.80-3.52, P<0.00001) and Caucasian (HR=2.40, 95% CI: 2.01-2.88, P<0.00001). In conclusion, high expression of MACM was significantly associated with a poor prognostic outcome in cancer. MACM can be regarded as a novel bio-marker in different types of cancers and can be used to evaluate the prognosis of therapeutic effect during clinical practices.

Comprehensive comparison of large-scale tissue expression datasets

For tissues to carry out their functions, they rely on the right proteins to be present. Several high-throughput technologies have been used to map out which proteins are expressed in which tissues; however, the data have not previously been systematically compared and integrated. We present a comprehensive evaluation of tissue expression data from a variety of experimental techniques and show that these agree surprisingly well with each other and with results from literature curation and text mining. We further found that most datasets support the assumed but not demonstrated distinction between tissue-specific and ubiquitous expression. By developing comparable confidence scores for all types of evidence, we show that it is possible to improve both quality and coverage by combining the datasets. To facilitate use and visualization of our work, we have developed the TISSUES resource (http://tissues.jensenlab.org), which makes all the scored and integrated data available through a single user-friendly web interface.

The use of Nanotrap particles in the enhanced detection of Rift Valley fever virus nucleoprotein

BACKGROUND

Rift Valley fever virus (RVFV) is a highly pathogenic arthropod-borne virus that has a detrimental effect on both livestock and human populations. While there are several diagnostic methodologies available for RVFV detection, many are not sensitive enough to diagnose early infections. Furthermore, detection may be hindered by high abundant proteins such as albumin. Previous findings have shown that Nanotrap particles can be used to significantly enhance detection of various small analytes of low abundance. We have expanded upon this repertoire to show that this simple and efficient sample preparation technology can drastically improve the detection of the RVFV nucleoprotein (NP), the most abundant and widely used viral protein for RVFV diagnostics.

RESULTS

After screening multiple Nanotrap particle architectures, we found that one particle, NT45, was optimal for RVFV NP capture, as demonstrated by western blotting. NT45 significantly enhanced detection of the NP at levels undetectable without the technology. Importantly, we demonstrated that Nanotrap particles are capable of concentrating NP in a number of matrices, including infected cell lysates, viral supernatants, and animal sera. Specifically, NT45 enhanced detection of NP at various viral titers, multiplicity of infections, and time points. Our most dramatic results were observed in spiked serum samples, where high abundance serum proteins hindered detection of NP without Nanotrap particles. Nanotrap particles allowed for sample cleanup and subsequent detection of RVFV NP. Finally, we demonstrated that incubation of our samples with Nanotrap particles protects the NP from degradation over extended periods of time (up to 120 hours) and at elevated temperatures (at 37ºC).

CONCLUSION

This study demonstrates that Nanotrap particles are capable of drastically lowering the limit of detection for RVFV NP by capturing, concentrating, and preserving RVFV NP in clinically relevant matrices. These studies can be extended to a wide range of pathogens and their analytes of diagnostic interest.

Prognostic value of neutrophil-to-lymphocyte ratio in breast cancer

Inflammation is an essential component of pathogenesis and progression of cancer. A high neutrophil-to-lymphocyte ratio (NLR) is considered as a prognostic indicator for breast cancer. This meta-analysis was conducted to establish the overall accuracy of the NLR test in the diagnosis of breast cancer. A comprehensive search of the literature was conducted by using PubMed, Web of Science and China National Knowledge Infrastructure (CNKI). Published studies dating up to July 2014 and 4,293 patients were enrolled in the present study. In order to evaluate the association between NLR and overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS) or cancer specific survival (CSS), the hazard ratios (HRs) and their 95% confidence intervals (CIs) were extracted. OS was the primary outcome. The results suggested that increased NLR was a strong predictor for OS with HR of 2.28 (95% CI = 1.08-4.80, Pheterogeneity < 0.001). Stratified analyses indicated that a high NLR appeared to be a negative prognostic marker in Caucasian populations (HR = 4.53, 95% CI = 3.11-6.60, Pheterogeneity  = 0.096), multivariate analysis method (HR = 2.10, 95% CI = 1.52-2.89, Pheterogeneity = 0.591), and mixed metastasis (HR = 4.53, 95% CI = 3.11-6.60, Pheterogeneity = 0.096). Elevated NLR was associated with a high risk for DFS (HR = 1.38, 95% CI = 1.09-1.74, Pheterogeneity = 0.050) and in subgroups of multivariate analysis (HR = 1.64, 95% CI = 1.25-2.14, Pheterogeneity = 0.545) and mixed metastasis (HR = 1.99, 95% CI = 1.28-3.09, Pheterogeneity = 0.992). In summary, NLR could be considered as a predictive factor for patients with breast cancer.

Bottom-up proteomic analysis of single HCT 116 colon carcinoma multicellular spheroids

RATIONALE

Proteomic analysis of single multicellular spheroids has not been previously reported. As three-dimensional cell cultures are an increasingly popular model system for biological research, there is interest in obtaining proteomic profiles of these samples. We investigated the proteome of single HCT 116 multicellular spheroids using protocols optimized for small sample sizes.

METHODS

Six biological replicates were analyzed via microscopy for size. Total protein content was assessed via the bicinchoninic acid assay (BCA assay). Five separate biological replicate spheroids were analyzed via mass spectrometry in technical duplicate. An ultra-performance liquid chromatography (UPLC) system coupled with an LTQ Orbitrap Velos was used for peptide separation, analysis, and identification.

RESULTS

The average diameter of six replicate HCT 116 spheroids was 940 ± 30 µm and the average total protein amount was determined to be 39 ± 4 µg. At least 1300 protein groups were identified in each single LC/MS/MS run with 10% of the material from each single spheroid loaded. Database search results showed variation between spheroid protein group identifications. Pearson correlations show that the disparity in identifications is due to random variations in spectra and protocol.

CONCLUSIONS

We detected more than 1350 protein groups in each replicate HCT 116 spheroid. While some variation was detected between replicates, differences in the number of protein groups identified were determined to be the result of random variations in mass spectra acquisition.

A meta-analysis to evaluate the cellular processes regulated by the interactome of endogenous and over-expressed estrogen receptor alpha

The nature of the proteins complexes that regulate ERα subcellular localization and activity is still an open question in breast cancer biology. Identification of such complexes will help understand development of endocrine resistance in ER+ breast cancer. Mass spectrometry (MS) has allowed comprehensive analysis of the ERα interactome. We have compared six published works analyzing the ERα interactome of MCF-7 and HeLa cells in order to identify a shared or different pathway-related fingerprint.

Overall, 806 ERα interacting proteins were identified. The cellular processes were differentially represented according to the ERα purification methodology, indicating that the methodologies used are complementary. While in MCF-7 cells, the interactome of endogenous and over-expressed ERα essentially represents the same biological processes and cellular components, the proteins identified were not over-lapping; thus, suggesting that the biological response may differ as the regulatory/participating proteins in these complexes are different. Interestingly, biological processes uniquely associated to ERα over-expressed in HeLa cell line included L-serine biosynthetic process, cellular amino acid biosynthetic process and cell redox homeostasis.

In summary, all the approaches analyzed in this meta-analysis are valid and complementary; in particular, for those cases where the processes occur at low frequency with normal ERα levels, and can be identified when the receptor is over-expressed. However special effort should be put into validating these findings in cells expressing physiological ERα levels.

Unraveling the exercise-related proteome signature in heart

Exercise training is a well-known non-pharmacological strategy for the prevention and treatment of cardiovascular diseases. Despite the established phenotypic knowledge, the molecular signature of exercise-induced cardiac remodeling remains poorly characterized. The great majority of studies dedicated to this topic use conventional reductionist methods, which only allow analyzing individual protein candidates. Nowadays, several methodologies based on mass spectrometry are available and have been successfully applied for the characterization of heart proteome, representing an attractive approach for the wide characterization of the complex molecular networks that underlie exercise-induced cardiac remodeling. Still, few studies have used these methodologies to understand the impact of exercise training on the remodeling of cardiac proteome. The present study analyzes the few available data obtained from mass spectrometry (MS)-based proteomic studies assessing the impact of distinct types of exercise training on the protein profile of heart (left ventricle and isolated mitochondria) and the potential cross-tolerance between exercise training and diseases as myocardial infarction and obesity. Network analysis was performed with bioinformatics to integrate data from distinct research papers, based on distinct exercise training protocols, animal models and methodological approaches applied in the characterization of heart proteome. The analysis revealed that exercise training confers a unique proteome signature characterized by the up-regulation of lipid and organic metabolic processes, vasculogenesis and tissue regeneration. Data retrieved from this analysis also suggested that cardiac mitochondrial proteome is highly dynamic in response to exercise training due, in part, to the action of specific kinases as PKA and PKG. Regarding to the type of exercise, treadmill training seems to have a greater effect on the modulation of cardiac proteome than swimming. Data from the present review will certainly open new perspectives on cardiac proteomics and will help to envisage future studies targeting the identification of the regulatory mechanisms underlying cardiac adaptive and maladaptive remodeling.

Prognostic significance of interleukin 17 in cancer: a meta-analysis

The prognostic value of Interleukin 17 (IL-17) in cancer patients is currently under debate and remains inconclusive. We performed a systematic review and meta-analysis to evaluate the role of IL-17 as a prognostic marker in cancer. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were combined to measure the effective value of IL-17 expression on prognosis. Nineteen eligible studies enrolling 2390 patients were identified. We found expression of IL-17 was not significantly correlated with overall survival (OS) in cancer (HR=1.29, 95% Cl: 0.94-1.76; P=0.12). Furthermore, compared to the data from our analysis that high expression of IL-17 predicted poor OS in both non-small cell lung carcinoma (NSCLC) (HR=2.30; 95% CI: 1.45-3.64; P<0.001; I(2)=0%) and hepatocellular carcinoma (HCC) (HR=2.02; 95% CI: 1.44-2.83; P<0.001; I(2)=0%), high expression of IL-17 was associated with favorable OS in esophageal squamous cell carcinoma (ESCC) (HR=0.63; 95% CI: 0.51-0.79; P<0.001; I(2)=0%). This meta-analysis showed that IL-17 has the potential to become a novel prognostic marker in HCC, NSCLC and ESCC. It could potentially help to monitor patients' prognosis and assess therapeutic efficacy in clinical treatment.

Quantitative proteomics to study carbapenem resistance in Acinetobacter baumannii

Acinetobacter baumannii is an opportunistic pathogen causing pneumonia, respiratory infections and urinary tract infections. The prevalence of this lethal pathogen increases gradually in the clinical setup where it can grow on artificial surfaces, utilize ethanol as a carbon source. Moreover it resists desiccation. Carbapenems, a β-lactam, are the most commonly prescribed drugs against A. baumannii. Resistance against carbapenem has emerged in Acinetobacter baumannii which can create significant health problems and is responsible for high morbidity and mortality. With the development of quantitative proteomics, a considerable progress has been made in the study of carbapenem resistance of Acinetobacter baumannii. Recent updates showed that quantitative proteomics has now emerged as an important tool to understand the carbapenem resistance mechanism in Acinetobacter baumannii. Present review also highlights the complementary nature of different quantitative proteomic methods used to study carbapenem resistance and suggests to combine multiple proteomic methods for understanding the response to antibiotics by Acinetobacter baumannii.

Prognostic value of PLR in various cancers: a meta-analysis

Background

Recently, more and more studies investigated the association of inflammation parameters such as the Platelet Lymphocyte Ratio (PLR) and the prognosis of various cancers. However, the prognostic role of PLR in cancer remains controversial.

Methods

We conducted a meta-analysis of published studies to evaluate the prognostic value of PLR in various cancers. In order to investigate the association between PLR and overall survival (OS), the hazard ratio (HR) and its 95% confidence interval (CI) were calculated.

Results

A total of 13964 patients from 26 studies were included in the analysis. The summary results showed that elevated PLR was a negative predictor for OS with HR of 1.60 (95%CI: 1.35–1.90; P_{heterogeneity} <0.001). Subgroup analysis revealed that increased PLR was a negative prognostic marker in patients with gastric cancer (HR = 1.35, 95%CI: 0.80–2.25, P_{heterogeneity} = 0.011), colorectal cancer (HR = 1.65, 95%CI: 1.33–2.05, P_{heterogeneity} = 0.995), hepatocellular carcinoma (HR = 3.07, 95% CI: 2.04–4.62, P_{heterogeneity} = 0.133), ovarian cancer (HR = 1.57, 95%CI: 1.07–2.31, P_{heterogeneity} = 0.641) and non-small cell lung cancer (NSCLC) (HR = 1.85, 95% CI: 1.42–2.41, P_{heterogeneity} = 0.451) except for pancreatic cancer (HR = 1.00, 95%CI: 0.92–1.09, P_{heterogeneity} = 0.388).

Conclusion

The meta-analysis demonstrated that PLR could act as a significant biomarker in the prognosis of various cancers.

A transcriptomic reporter assay employing neutrophils to measure immunogenic activity of septic patients' plasma

Background

There are diverse molecules present in blood plasma that regulate immune functions and also present a potential source of disease biomarkers and therapeutic targets. Genome-wide profiling has become a powerful method for assessing immune responses on a systems scale, but technologies that can measure the plasma proteome still face considerable challenges. An alternative approach to direct proteome assessment is to measure transcriptome responses in reporter cells exposed in vitro to plasma. In this report we describe such a “transcriptomic reporter assay” to assess plasma from patients with sepsis, which is a common and severe systemic infectious process for which physicians lack efficient diagnostic or prognostic markers.

Methods

Plasma samples collected from patients with culture-confirmed bacterial sepsis and uninfected healthy controls were used to stimulate three separate cell types – neutrophils, peripheral blood mononuclear cells, and monocyte-derived dendritic cells. Whole genome microarrays were generated from stimulated cells to assess transcriptional responses. Unsupervised analysis and enriched functional networks were evaluated for each cell type. Principal component analyses were used to assess variability in responses. A random K-nearest neighbor – feature selection algorithm was used to identify markers predictive of sepsis severity, which were then validated in an independent data set.

Results

Neutrophils demonstrated the most distinct response to plasma from septic patients with 709 genes showing altered expression profiles, many of which are involved in established immunologic pathways. The amplitude of the neutrophil transcriptomic response was shown to be correlated with sepsis severity in two independent sets of patients comprised of 64 total septic patients. A subset of 30 transcripts selected using one set of patients was demonstrated to have a high degree of accuracy (82-90%) in predicting sepsis severity and outcomes in the other independent set. This subset included several genes previously established in sepsis pathogenesis as well as novel genes.

Conclusions

These results demonstrate both the suitability and potential clinical relevance of a neutrophil reporter assay for studying plasma, in this case from septic patients. The distinctive transcriptional signature we found could potentially help predict severity of disease and guide treatment. Our findings also shed new light on mechanisms of immune dysregulation in sepsis.

MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.

Prognostic significance of dickkopf-1 overexpression in solid tumors: a meta-analysis

The prognostic significance of dickkopf-1 (DKK1) overexpression in solid tumors remains inconclusive. We performed a meta-analysis to evaluate the impact of DKK1 overexpression in solid tumors on patients' overall survival (OS) and disease-free survival (DFS). The pooled hazard ratio (HR) with 95 % confidence interval (CI) was used to estimate the effects. Thirteen studies were included for meta-analysis; four that evaluated hepatocellular carcinoma (HCC), two each that evaluated ovarian carcinoma, esophageal carcinoma, and lung cancer, and one each that evaluated other cancers, namely gastric cancer, breast cancer, urothelial carcinoma, and colorectal cancer. Twelve studies were evaluable for OS and six for DFS. Our analysis results indicated that DKK1 overexpression predicted poor OS (HR = 1.68, 95% CI 1.36-2.08; P < 0.001) and DFS (HR = 1.65, 95% CI 1.37-1.99; P < 0.001). Subgroup analyses showed that DKK1 overexpression was significantly related with poor OS in HCC patients (HR = 1.65; P < 0.001), ovarian carcinoma patients (HR = 2.63; P = 0.045), and other cancers patients (HR = 1.51; P = 0.021). Further, DKK1 overexpression was significantly related with poor DFS in HCC patients (HR = 1.53; P < 0.001) and other cancers patients (HR = 2.02; P < 0.001). This meta-analysis showed that DKK1 may be a novel prognostic marker in solid tumors in Asian patients; it could potentially help to further stratify patients for clinical treatment. More, well-designed studies from Western countries are needed to confirm this finding.