Dissecting the human plasma proteome and inflammatory response biomarkers

A central focus of clinical proteomics is to search for biomarkers in plasma for diagnostic and therapeutic use. We studied a set of plasma proteins accessed from the Healthy Human Individual's Integrated Plasma Proteome (HIP²) database, a larger set of curated human proteins, and a subset of inflammatory proteins, for overlap with sets of known protein biomarkers, drug targets, and secreted proteins. Most inflammatory proteins were found to occur in plasma, and over three times the level of biomarkers were found in inflammatory plasma proteins and their interacting protein neighbors compared to the sets of plasma and curated human proteins. Percentage overlaps with Gene Ontology terms were similar between the curated human set and plasma protein set, yet the set of inflammatory plasma proteins had a distinct ontology‐based profile. Most of the major hub proteins within protein‐protein interaction networks of tissue‐specific sets of inflammatory proteins were found to occur in disease pathways. The present study presents a systematic approach for profiling a plasma subproteome's relationship to both its potential range of clinical application and its overlap with complex disease.     

Comparison of protein enrichment strategies for proteome analysis of plasma

Efforts to discover protein biomarkers in plasma are hampered by the high abundance of few proteins, which interfere with the detection of low‐abundant proteins. Different commercially available protein‐partitioning products were tested for their ability to lower the detection limit of proteins in 2‐D gels. Immuno‐depletion using polyclonal antibodies raised against the proteins of highest abundance (Seppro IgY14 System) was compared with a two‐step immuno‐depletion strategy, where depletion with the Seppro IgY14 column was followed by depletion with the Seppro IgY‐SuperMix system. The third strategy tested was protein pre‐fractionation using the ProteoMiner kit, where proteins compete for binding sites on bead‐bound peptide hexamers with different binding properties. The pre‐fractionated protein samples were analyzed using 2‐DE, which revealed stunning differences in protein patterns. However, detectable protein spots in the different plasma fractions contained exclusively high‐abundant proteins normally present in plasma at concentrations between 1 μg and 40 mg/mL.     

Distinct proteome features of plasma microparticles

Plasma microparticles (MPs) are spherical cell membrane fragments derived from either apoptotic or activated cells. Characterized by a rich phospholipid moiety and many protein constituents, MPs normally circulate in the blood and contribute to numerous physiological processes. In disease states, MPs derived from the injured organ likely contain valuable markers for determining the site, type, and extent of disease pathology. However, the basic protein characteristics of plasma MPs have yet to be described. In this study, MPs from a pooled plasma sample derived from 16 healthy donors, all of group A blood type, were prepared by ultracentrifugation. Flow cytometry confirmed that a majority of these MPs are smaller than 1 microm. Factor Xa generation assay revealed the presence of tissue factor activity in these MPs, confirming MPs' role in initiating blood coagulation. The MP proteome was analyzed by two-dimensional (2-D) gel electrophoresis performed in triplicate, and compared with a 2-D gel of pooled whole plasma and blood platelets. Overall, plasma MPs displayed distinct protein features and a greater number of protein spots (1021-1055) than that detected in whole plasma (331-370). Protein spots expressed in high abundance in the MP proteome were then excised and submitted for protein identity determination. This process provided protein identification for 169 protein spots and reported their relative protein quantities within the MP proteome. These 169 protein spots represented 83 different proteins and their respective isoforms. Thirty of these proteins have never before been reported in previous proteome analyses of human plasma. These results provide unprecedented information on the MP proteome and create a basis for future studies to understand MP biology and pathophysiology.     

A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

     

A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer

Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients.     

7th HUPO World Congress of Proteomics: Launching the Second Phase of the HUPO Plasma Proteome Project (PPP‐2) 16–20 August 2008, Amsterdam,The Netherlands

The HUPO Plasma Proteome Project new phase, PPP‐2, held its initial workshop on 17 August, 2008, at the 7^th World Congress of Proteomics in Amsterdam. Technology platforms, data repositories, informatics, and engagement of research groups for the submission of major datasets were key topics. Plasma is expected to be the common pathway for biomarker development and application through collaboration and integration with other HUPO initiatives.     

Mining the fecal proteome: from biomarkers to personalised medicine

Introduction: Fecal proteomics has gained increased prominence in recent years. It can provide insights into the diagnosis and surveillance of many bowel diseases by both identifying potential biomarkers in stool samples and helping identify disease-related pathways. Fecal proteomics has already shown its potential for the discovery and validation of biomarkers for colorectal cancer screening, and the analysis of fecal microbiota by MALDI-MS for the diagnosis of a range of bowel diseases is gaining clinical acceptance.

Areas covered: Based on a comprehensive analysis of the current literature, we introduce the range of sensitive and specific proteomics methods which comprise the current ‘Proteomics Toolbox’, explain how the integration of fecal proteomics with data processing/bioinformatics has been used for the identification of potential biomarkers for both CRC and other gut-related pathologies and analysis of the fecal microbiome, outline some of the current fecal assays in current clinical practice and introduce the concept of personalised medicine which these technologies will help inform.

Expert commentary: Integration of fecal proteomics with other proteomics and genomics strategies as well as bioinformatics is paving the way towards personalised medicine, which will bring with it improved global healthcare.     

COVID-19 plasma proteome reveals novel temporal and cell-specific signatures for disease severity and high-precision disease management

Coronavirus disease 2019 (COVID-19) is a systemic inflammatory condition with high mortality that may benefit from personalized medicine and high-precision approaches. COVID-19 patient plasma was analysed with targeted proteomics of 1161 proteins. Patients were monitored from Days 1 to 10 of their intensive care unit (ICU) stay. Age- and gender-matched COVID-19-negative sepsis ICU patients and healthy subjects were examined as controls. Proteomic data were resolved using both cell-specific annotation and deep-analysis for functional enrichment. COVID-19 caused extensive remodelling of the plasma microenvironment associated with a relative immunosuppressive milieu between ICU Days 3–7, and characterized by extensive organ damage. COVID-19 resulted in (1) reduced antigen presentation and B/T-cell function, (2) increased repurposed neutrophils and M1-type macrophages, (3) relatively immature or disrupted endothelia and fibroblasts with a defined secretome, and (4) reactive myeloid lines. Extracellular matrix changes identified in COVID-19 plasma could represent impaired immune cell homing and programmed cell death. The major functional modules disrupted in COVID-19 were exaggerated in patients with fatal outcome. Taken together, these findings provide systems-level insight into the mechanisms of COVID-19 inflammation and identify potential prognostic biomarkers. Therapeutic strategies could be tailored to the immune response of severely ill patients.     

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.     

The HUPO Plasma Proteome Project: a report from the Munich congress

The Human Proteome Organization has several major collaborative research initiatives, including the Plasma Proteome Project. A major feature of the HUPO World Congress in Munich in August 2005 was the release of the special issue of PROTEOMICS with 28 articles from the pilot phase of the Plasma Proteome Project. An open Workshop and a presentation in the closing plenary session of the congress focused on next phases for the Plasma Proteome Project.     

Multi-component immunoaffinity subtraction chromatography: an innovative step towards a comprehensive survey of the human plasma proteome

In order to discover novel protein markers indicative of disease processes or drug effects, the proteomics technology platform most commonly used consists of high resolution protein separation by two-dimensional electrophoresis (2-DE), mass spectrometric identification of proteins from stained gel spots and a bioinformatic data analysis process supported by statistics. This approach has been more successful in profiling proteins and their disease- or treatment-related quantitative changes in tissue homogenates than in plasma samples. Plasma protein display and quantitation suffer from several disadvantages: very high abundance of a few proteins; high heterogeneity of many proteins resulting in long charge trains; crowding of 2-DE separated protein spots in the molecular mass range between 45-80 kD and in the isoelectric point range between 4.5 and 6. Therefore, proteomic technologies are needed that address these problems and particularly allow accurate quantitation of a larger number of less abundant proteins in plasma and other body fluids. The immunoaffinity-based protein subtraction chromatography (IASC) described here removes multiple proteins present in plasma and serum in high concentrations effectively and reproducibly. Applying IASC as an upfront plasma sample preparation process for 2-DE, the protein spot pattern observed in gels changes dramatically and at least 350 additional lower abundance proteins are visualized. Affinity-purified polyclonal antibodies (pAbs) are the immunoaffinity reagents used to specifically remove the abundant proteins such as albumin, immunoglobulin G, immunoglobulin A, transferrin, haptoglobin, alpha-1-antitrypsin, hemopexin, transthyretin, alpha-2-HS glycoprotein, alpha-1-acid glycoprotein, alpha-2-macroglobulin and fibrinogen from human plasma samples. To render the immunoaffinity subtraction procedure recyclable, the pAbs are immobilized and cross-linked on chromatographic matrices. Antibody-coupled matrices specific for one protein each can be pooled to form mixed-bed IASC columns. We show that up to ten affinity-bound plasma proteins with similar solubility characteristics are eluted from a mixed-bed column in one step. This facilitates automated chromatographic processing of plasma samples in high throughput, which is desirable in proteomic disease marker discovery projects.     

ProteoConnections: a bioinformatics platform to facilitate proteome and phosphoproteome analyses

Novel and improved computational tools are required to transform large-scale proteomics data into valuable information of biological relevance. To this end, we developed ProteoConnections, a bioinformatics platform tailored to address the pressing needs of proteomics analyses. The primary focus of this platform is to organize peptide and protein identifications, evaluate the quality of the acquired data set, profile abundance changes, and accelerate data interpretation. Peptide and protein identifications are stored into a relational database to facilitate data mining and to evaluate the quality of data sets using graphical reports. We integrated databases of known PTMs and other bioinformatics tools to facilitate the analysis of phosphoproteomics data sets and to provide insights for subsequent biological validation experiments. Phosphorylation sites are also annotated according to kinase consensus motifs, contextual environment, protein domains, binding motifs, and evolutionary conservation across different species. The practical application of ProteoConnections is further demonstrated for the analysis of the phosphoproteomics data sets from rat intestinal IEC-6 cells where we identified 9615 phosphorylation sites on 2108 phosphoproteins. Combined proteomics and bioinformatics analyses revealed valuable biological insights on the regulation of phosphoprotein functions via the introduction of new binding sites on scaffold proteins or the modulation of protein-protein, protein-DNA, or protein-RNA interactions. Quantitative proteomics data can be integrated into ProteoConnections to determine the changes in protein phosphorylation under different cell stimulation conditions or kinase inhibitors, as demonstrated here for the MEK inhibitor PD184352.     

Systematical evaluation of the effects of sample collection procedures on low-molecular-weight serum/plasma proteome profiling

Blood is an ideal source for biomarker discovery. However, little has been done to address the effects of sampling, handling and storage procedures on serum/plasma proteomes. We used magnetic bead-based MALDI-TOF MS to systematically evaluate the influence of each procedure on low-molecular-weight serum/plasma proteome profiling on the basis of the whole spectra. We found that sampling procedures, including the selection of blood collection tubes and anticoagulants, variations in clotting time or time lag before centrifugation, and hemolysis, displayed significant effects on the proteomes. Moreover, serum and plasma were mutually incompatible for proteome comparison. By contrast, overnight fasting, handling procedures, including centrifugation speeds (1500 x g vs. 3000 x g) or time (15 min vs. 30 min), and storage conditions, such as at 4 degrees C or 25 degrees C for up to 24 h or at -80 degrees C for up to 3 months, and repeated freeze/thaw of up to ten cycles, had relatively minor effects on the proteomes based upon our analysis of about 100 peaks. We concluded that low-molecular-weight serum/plasma proteomes were diversely affected by sampling, handling and storage with most change from variations of sampling procedures. We therefore suggest the necessity of standardizing sampling procedure for proteome comparison and biomarker discovery.     

Plasma proteome analysis for anti‐obesity and anti‐diabetic potentials of chitosan oligosaccharides in ob/ob mice

Altered levels of adipokines, derived as a result of distorted adipocytes, are the major factors responsible for changing biochemical parameters in obesity that leads to the development of metabolic disorders such as insulin resistance and atherosclerosis. In our previous reports, chitosan oligosaccharides (CO) were proved to inhibit the differentiation of 3T3‐L1 adipocytes. In the present study, an attempt was made to investigate the anti‐obesity and anti‐diabetic effect of CO on ob/ob mice, by means of differential proteomic analysis of plasma. This was followed by immunoblotting, and gene expression in adipose tissue to clarify the molecular mechanism. CO treatment showed reduced diet intake (13%), body weight gain (12%), lipid (29%) and glucose levels (35%). 2‐DE results showed differential levels of five proteins namely RBP4, apoE, and apoA‐IV by >2‐fold down‐regulation and by >2‐fold of apoA‐I and glutathione peroxidase (GPx) up‐regulation after CO treatment. Immunoblotting studies of adiponectin and resistin showed amelioration in their levels in plasma. Furthermore, the results of gene expressions for adipose tissue specific TNF‐α, and IL‐6 secretary molecules were also down‐regulated by CO treatment. Gene expressions of PPARγ in adipose tissue were in good agreement with the ameliorated levels of adipokines, thereby improving the pathological state. Taken together, CO might act as a potent down‐regulator of obesity‐related gene expression in ob/ob mice that may normalize altered plasma proteins to overcome metabolic disorders of obesity.     

Proteomic and cytokine plasma biomarkers for predicting progression from colorectal adenoma to carcinoma in human patients

In the present study, we screened proteomic and cytokine biomarkers between patients with adenomatous polyps and colorectal cancer (CRC) in order to improve our understanding of the molecular mechanisms behind turmorigenesis and tumor progression in CRC. To this end, we performed comparative proteomic analysis of plasma proteins using a combination of 2DE and MS as well as profiled differentially regulated cytokines and chemokines by multiplex bead analysis. Proteomic analysis identified 11 upregulated and 13 downregulated plasma proteins showing significantly different regulation patterns with diagnostic potential for predicting progression from adenoma to carcinoma. Some of these proteins have not previously been implicated in CRC, including upregulated leucine‐rich α‐2‐glycoprotein, hemoglobin subunit β, Ig α‐2 chain C region, and complement factor B as well as downregulated afamin, zinc‐α‐2‐glycoprotein, vitronectin, and α‐1‐antichymotrypsin. In addition, plasma levels of three cytokines/chemokines, including interleukin‐8, interferon gamma‐induced protein 10, and tumor necrosis factor α, were remarkably elevated in patients with CRC compared to those with adenomatous polyps. Although further clinical validation is required, these proteins and cytokines can be established as novel biomarkers for CRC and/or its progression from colon adenoma.     

A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer

Background

Over 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening.

Methods

In the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n?=?106), endometrial cancer (n?=?74), benign ovarian tumors (n?=?150) and healthy population controls (n?=?399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n?=?280), endometrial cancer (n?=?228), women with benign ovarian tumors (n?=?76) and healthy controls (n?=?57).

Results

In the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III–IV with a sensitivity of 0.88 and specificity of 0.92 (AUC?=?0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p?=?9.56e?22). Also, population controls could be distinguished from ovarian cancer stage III–IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC?=?0.89).

Conclusion

The PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination.

Funding

The Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.

     

Plasma proteome analysis in diet-induced obesity-prone and obesity-resistant rats

One of the major issues in the field of obesity is why some humans become obese and others resist development of obesity when exposed to high-calorie diets. Despite the same genetic background, namely obesity-prone (OP) and -resistant (OR) rats, differing responses have been demonstrated in a high fat diet-induced rodent model. The aim of the present study was to discover novel obesity-related biomarkers for susceptibility and/or resistance to obesity by proteomic analysis of OP and OR rat plasma. After feeding of high fat diet, OP rats gained approximately 25% more body weight than OR rats and were used for proteomic analysis using 2-DE combined with MALDI-TOF-MS. We categorized identified proteins into three groups by analysis of both average spot density in each group and individual spot density of six rats as a function of body weight. Consequently, category (1) included inter-α-inhibitor H4 heavy chain and fetuin B precursor, which can be used as novel plasma biomarkers for risk of obesity. Nine proteins of category (2) and (3) can also be plausible plasma markers in the study of obesity. This proteomic study is an important advancement over the previous steps needed for identification of OP and OR rats.     

Progress in the identification of plasma biomarkers of colorectal cancer

Proteomic analysis of human tissue and plasma samples has been a useful tool in recent years for the identification of potential biomarkers to aid in the early diagnosis of colorectal cancer. However, biomarkers relating to the crucial transition between adenomatous lesions and invasive colorectal malignancy have not previously been described. The work of Choi et al. (Proteomics 2013, 13, 2361–2374) attempts to address this issue. Using plasma samples from age‐matched patients with colorectal adenomas or invasive disease this group identified a range of plasma proteins and cytokines that were differentially expressed. This information not only provides insights into the biology of the adenoma to carcinoma progression sequence but it also represents a step towards the goal of achieving diagnostically accurate and clinically acceptable biomarkers in early colorectal cancer.