Serum molecular biomarkers in neuromyelitis optica and multiple sclerosis.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a rare and severe inflammatory demyelinating disorder of the central nervous system (CNS), which mainly affects the optic nerves and spinal cord. The aims of this study were to determine whether the expression levels of serological cytokines could distinguish 1) NMOSD from healthy controls (HCs); and 2) NMOSD patients with and without the aquaporin-4 (AQP4) antibody biomarker from each other; and 3) NMOSD patients without the antibody to AQP4 from MS patients. METHODS: The expression levels of 200 proteins in serum from 41 NMOSD (32 with antibodies to AQP4, 9 without antibodies to AQP4), 12 MS patients, and 34 HCs were measured using glass-based antibody arrays. None of the patients received any immunosuppressive treatment. In parallel, the correlation between protein expression in NMOSD/MS patients and clinical traits was determined with Weighted Gene Co-expression Network Analysis (WGCNA). RESULTS: Thirty-nine serological proteins were differentially expressed in NMOSD patients compared to HCs, with 29 of these proteins not observed in MS patients. In addition, the data reveal 15 differentially-expression proteins (DEPs) between AQP4-IgG seronegative and AQP4-IgG seropositive NMOSD patients, and 9 DEPs between NMOSD and MS patients who did not have AQP4-IgG. CONCLUSION: Serological IL-17B is significantly upregulated in both NMOSD and MS patients compared to HCs, and could be a key biomarker of NMOSD and MS. Serological VEGF, MPIF-1 and NrCAM were positively associated with AQP4-IgG titer. We also demonstrate that EGF may be involved in the breakdown of the BBB by downregulating Claudin-5.

Dried blood sample analysis by antibody array across the total testing process.

Dried blood samples (DBSs) have many advantages; yet, impediments have limited the clinical utilization of DBSs. We developed a novel volumetric sampling device that collects a precise volume of blood, which overcomes the heterogeneity and hematocrit issues commonly encountered in a traditional DBS card collection as well as allowing for more efficient extraction and processing procedures and thus, more efficient quantitation, by using the entire sample. We also provided a thorough procedure validation using this volumetric DBS collection device with an established quantitative proteomics analysis method, and then analyzed 1000 proteins using this approach in DBSs concomitantly with serum for future consideration of utility in clinical applications. Our data provide a first step in the establishment of a DBS database for the broad application of this sample type for widespread use in clinical proteomic and other analyses applications.

Three subtypes of lung cancer fibroblasts define distinct therapeutic paradigms.

Cancer-associated fibroblasts (CAFs) are highly heterogeneous. With the lack of a comprehensive understanding of CAFs' functional distinctions, it remains unclear how cancer treatments could be personalized based on CAFs in a patient's tumor. We have established a living biobank of CAFs derived from biopsies of patients' non-small lung cancer (NSCLC) that encompasses a broad molecular spectrum of CAFs in clinical NSCLC. By functionally interrogating CAF heterogeneity using the same therapeutics received by patients, we identify three functional subtypes: (1) robustly protective of cancers and highly expressing HGF and FGF7; (2) moderately protective of cancers and highly expressing FGF7; and (3) those providing minimal protection. These functional differences among CAFs are governed by their intrinsic TGF-ß signaling, which suppresses HGF and FGF7 expression. This CAF functional classification correlates with patients' clinical response to targeted therapies and also associates with the tumor immune microenvironment, therefore providing an avenue to guide personalized treatment.

Data Analysis for Antibody Arrays.

When obtaining high-throughput data from antibody arrays, researchers have to face a couple of questions: How and by what means can they get reasonable results significant to their research from these data? Similar to a gene microarray, the classical statistical pipeline of an antibody array includes data preprocessing transformation, differential expression analysis, classification, and biological annotation analysis. In this chapter, we will provide a pipeline of statistical approaches suitable for antibody arrays to facilitate better understanding of the results gained from each of these steps.

Sandwich-Based Antibody Arrays for Protein Detection.

Sandwich-based antibody arrays enable the detection of multiple proteins simultaneously, thus offering a time- and cost-effective alternative to single-plex platforms. The protein of interest is "sandwiched" between an antibody that captures it to the array and a second antibody that is used for detection. Here we describe a 1-day procedure to process samples, such as serum or cell lysates, with a quantitative sandwich-based antibody array on a glass substrate using fluorescence.

One-Step Antibody Arrays.

The sandwich-based immunoassay is renowned for its specificity and sensitivity for protein detection, where the antigen is "sandwiched" by a pair of antigen epitope-specific antibodies. The capture antibody-antigen-detection antibody complex will be formed if all the components are present in a proper reaction system. A one-step rapid sandwich-based antibody array can be developed through fixing the capture antibody on a glass slide with a fluorescence-labelled detection antibody. In this chapter, we describe the process of a one-step mouse immunoglobulin isotyping array for use in hybridoma culture supernatants.

Cytometry Multiplex Bead Antibody Array.

The flow cytometry-based multiplex bead array is an advanced technology using antibody-conjugated multiplex beads to detect soluble targets in a liquid phase. This technology has been widely used for detection of soluble analytes like cytokines, chemokines, allergens, viral antigens, and cancer markers. RayPlex® Multiplex Beads Antibody Array series are developed by RayBiotech Life, Inc. to quantitatively detect a wide range of analytes with high sensitivity to meet increasing need of research and diagnosis.

Dried Blood-Based Protein Profiling Using Antibody Arrays.

Dried blood samples have been increasingly considered for clinical applications in recent years. The main disadvantages that limit DBS utility in clinical applications are the small sample volume collected, area bias and homogeneity issues, and sample preparation requirements for the necessary sensitivity and reproducibility required for clinical assessment. The recent advances in antibody array technology overcome the common disadvantages of immunoassay approaches by increasing the multiplex capabilities and decreasing the sample volume requirements as well as minimizing the expense and technical expertise required with many alternative high-density approaches like mass spectrometry.

Discovering endometriosis biomarkers with multiplex cytokine arrays.

BACKGROUND: Chronic pelvic pain is often overlooked during primary examinations because of the numerous causes of such "vague" symptoms. However, this pain can often mask endometriosis, a smoldering disease that is not easily identified as a cause of the problem. As such, endometriosis has been shown to be a potentially long-term and often undiagnosed disease due to its vague symptoms and lack of any non-invasive testing technique. Only after more severe symptoms arise (severe pelvic pain, excessive vaginal bleeding, or infertility) is the disease finally uncovered by the attending physician. Due to the nature and complexity of endometriosis, high throughput approaches for investigating changes in protein levels may be useful for elucidating novel biomarkers of the disease and to provide clues to help understand its development and progression. METHODS: A large multiplex cytokine array which detects the expression levels of 260 proteins including cytokines, chemokines, growth factors, adhesion molecules, angiogenesis factors and other was used to probe biomarkers in plasma samples from endometriosis patients with the intent of detecting and/or understanding the cause of this disease. The protein levels were then analyzed using K-nearest neighbor and split-point score analysis. RESULTS: This technique identified a 14-marker cytokine profile with the area under the curve of 0.874 under a confidence interval of 0.81-0.94. Our training set further validated the panel for significance, specificity, and sensitivity to the disease samples. CONCLUSIONS: These findings show the utility and reliability of multiplex arrays in deciphering new biomarker panels for disease detection and may offer clues for understanding this mysterious disease.

Antibody arrays in biomarker discovery.

All of life is regulated by complex and organized chemical reactions that help dictate when to grow, to move, to reproduce, and to die. When these processes go awry, or are interrupted by pathological agents, diseases such as cancer, autoimmunity, or infections can result. Cytokines, chemokines, growth factors, adipokines, and other chemical moieties make up a vast subset of these chemical reactions that are altered in disease states, and monitoring changes in these molecules could provide for the identification of disease biomarkers. From the first identification of carcinoembryonic antigen, to the discovery of prostate-specific antigen, to numerous others described within, biomarkers of disease are detectable in a plethora of sample types. The growing number of biomarkers for infection, autoimmunity, and cancer allow for increasingly early detection, to identification of novel drug targets, to prognostic indicators of disease outcome. However, more and more studies are finding that a single cytokine or growth factor is insufficient as a true disease biomarker and that a more global perspective is needed to understand true disease biology. Such a broad view requires a multiplexed platform for chemical detection, and antibody arrays meet and exceed this need by performing this detection in a high-throughput fashion. Herein, we will discuss how antibody arrays have evolved, and how they have helped direct new drug target design, helped identify therapeutic disease markers, and helped in earlier disease detection. From asthma to renal disease, and neurological dysfunction to immunologic disorders, antibody arrays afford a bright future for new biomarkers discovery.

Protein expression profiling by antibody array analysis with use of dried blood spot samples on filter paper.

Dried blood spot samples (DBSS) on filter paper offer several advantages compared to conventional serum/plasma samples: they do not require any phlebotomy or separation of blood by centrifugation; they are less invasive; they allow sample stability and shipment at room temperature; and they pose a negligible risk of infection with blood-borne viruses, such as HIV, HBV and HCV, to those who handle them. Therefore dried blood spot samples (DBSS) on filter paper can be a quick, convenient and inexpensive means of obtaining blood samples for biomarker discovery, disease screening, diagnosis and treatment monitoring in non-hospitalized, public health settings. In this study, we investigated for the first time the potential application of dried blood spot samples (DBSS) in protein expression profiling using antibody array technology. First, optimal conditions for array assay performance using dried blood spot samples (DBSS) was established, including sample elution buffer, elution time, elution temperature and assay blocking buffer. Second, we analyzed dried blood spot samples (DBSS) using three distinct antibody array platforms, including sandwich-based antibody arrays, quantitative antibody arrays and biotin-label-based antibody arrays. In comparison with paired serum samples, detection of circulating proteins in dried blood spot samples (DBSS) correlated well for both low- and high-abundance proteins on all three antibody array platforms. In conclusion, our study strongly indicates the novel application of multiplex antibody array platforms to analyze dried blood spot samples (DBSS) on filter paper represents a viable, cost-effective method for protein profiling, biomarker discovery and disease screening in a large, population-based survey.

Development of IGF signaling antibody arrays for the identification of hepatocellular carcinoma biomarkers.

PURPOSE: Our objective was to develop a system to simultaneously and quantitatively measure the expression levels of the insulin-like growth factor (IGF) family proteins in numerous samples and to apply this approach to profile the IGF family proteins levels in cancer and adjacent tissues from patients with hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN: Antibodies against ten IGF family proteins (IGF-1, IGF-1R, IGF-2, IGF-2R, IGFBP-1, IGFBP-2, IGFBP-3, IGFBP-4, IGFBP-6, and Insulin) were immobilized on the surface of a glass slide in an array format to create an IGF signaling antibody array. Tissue lysates prepared from patient's liver cancer tissues and adjacent tissues were then applied to the arrays. The proteins captured by antibodies on the arrays were then incubated with a cocktail of biotinylated detection antibodies and visualized with a fluorescence detection system. By comparison with standard protein amount, the exact protein concentrations in the samples can be determined. The expression levels of the ten IGF family proteins in 25 pairs of HCC and adjacent tissues were quantitatively measured using this novel antibody array technology. The differential expression levels between cancer tissues and adjacent tissues were statistically analyzed. RESULTS: A novel IGF signaling antibody array was developed which allows the researcher to simultaneously detect ten proteins involved in IGF signal pathway with high sensitivity and specificity. Using this approach, we found that the levels of IGF-2R and IGFBP-2 in HCC tissues were higher than those in adjacent tissues. CONCLUSION: Our IGF signaling antibody array which can detect the expression of ten IGF family members with high sensitivity and specificity will undoubtedly prove a powerful tool for drug and biomarker discovery.

A biotin label-based antibody array for high-content profiling of protein expression.

BACKGROUND/AIM: Profiling protein expression on a global scale will have significant impact on biomedical research, particularly in the discovery and development of drugs and biomarkers. Through the years, several antibody array systems have been invented and developed for multiple protein detection. However, a reliable and high-content system for protein profiling from many biological samples has yet been developed. This study aimed to develop a reliable, easy to use and cost effective method to profile protein expression levels in high-content manner with sufficient sensitivity and specificity. MATERIALS AND METHODS: To address this problem, a high density antibody array was developed and used this technology to uncover the potential biomarkers of ovarian cancer. In this system, biological samples are labeled with biotin. The biotinylated proteins are then incubated with antibody chips. The presence of proteins captured by the antibody chip is detected using streptavidin-conjugated fluorescent dye (Cy3 equivalent) as a reporter. The signals, which are visualized by laser scanning, are normalized using positive, negative, and internal controls. RESULTS: Using this biotin label-based antibody array technology, the expression levels of 507 human, 308 mouse and 90 rat target proteins can be simultaneously detected, including of cytokines, chemokines, adipokines, growth factors, angiogenic factors, proteases, soluble receptors, soluble adhesion molecules, and other proteins in a variety of samples. Most proteins can be detected at pg/ml and ng/ml levels, with a coefficient of variation of less than 20%. Using human biotin-based antibody arrays, we screened the serum expression profiles of 507 proteins in ovarian cancer patients and healthy individuals. A panel of protein expression showed significant difference between normal and cancer samples (p<0.05). By classification analysis and split-point score analysis of these two groups, a small group of proteins were found to be useful in distinguishing ovarian cancer patients from normal subjects. CONCLUSION: Our results suggest the biotin label-based antibody arrays that we have developed have great potential in applications for biomarker discovery.