Screening Of Protein Biomarkers Research Articles

Automated classification of protein expression levels in immunohistochemistry images to improve the detection of cancer biomarkers

BackgroundThe expression changes of some proteins are associated with cancer progression, and can be used as biomarkers in cancer diagnosis. Automated systems have been frequently applied in the large-scale detection of protein biomarkers and have provided a valuable complement for wet-laboratory experiments. For example, our previous work used an immunohistochemical image-based machine learning classifier of protein subcellular locations to screen biomarker proteins that change locations in colon cancer tissues. The tool could recognize the location of biomarkers but did not consider the effect of protein expression level changes on the screening process.ResultsIn this study, we built an automated classification model that recognizes protein expression levels in immunohistochemical images, and used the protein expression levels in combination with subcellular locations to screen cancer biomarkers. To minimize the effect of non-informative sections on the immunohistochemical images, we employed the representative image patches as input and applied a Wasserstein distance method to determine the number of patches. For the patches and the whole images, we compared the ability of color features, characteristic curve features, and deep convolutional neural network features to distinguish different levels of protein expression and employed deep learning and conventional classification models. Experimental results showed that the best classifier can achieve an accuracy of 73.72% and an F1-score of 0.6343. In the screening of protein biomarkers, the detection accuracy improved from 63.64 to 95.45% upon the incorporation of the protein expression changes.ConclusionsMachine learning can distinguish different protein expression levels and speed up their annotation in the future. Combining information on the expression patterns and subcellular locations of protein can improve the accuracy of automatic cancer biomarker screening. This work could be useful in discovering new cancer biomarkers for clinical diagnosis and research.

Proteomics: recent advances in the analysis of diabetic kidney disease

Diabetic kidney disease (DKD) is one of the major complications of diabetes, which has been an increasingly serious threat to human health. Despite the enormous progress that has been made in the studies of DKD pathological mechanism, there is still a lack of clinical analysis methods suitable for the accurate diagnosis of DKD, which makes it difficult for doctors to decide the treatment plan for DKD compared to other general kidney diseases. Proteins play critical roles in various life processes, therefore proteomics analysis is very important for disease early diagnosis, accurate prognosis, and monitoring of disease progression. The proteomics studies of DKD can explore the molecular mechanisms associated with proteins from the perspectives of global, dynamic, and interaction networks. Many studies were performed on clinical specimens under different physiological and pathological conditions to screen proteins that are closely related to DKD. The comprehensive characterization of these proteins will help us to find potential biomarkers and understand more intuitively the occurrence and progression of DKD. With the development of proteomics, new emerging technologies have been drawing more and more attention due to their powerful analytical capabilities. The wide use of these techniques has further promoted the application of proteomics in the screening of disease biomarkers, the revelation of pathogenic molecular mechanisms, and the evaluation of protein-drug interactive targets. This review provides an overview of proteomics technologies, describes the applications of proteomics in DKD research, and highlights the studies of DKD pathogenesis, the screening of protein biomarkers for early diagnosis, and the evaluation of therapeutic targets and efficacy. Although great progress has been made in the proteomics study of DKD, the correlation analysis of potential biomarkers and the clinical verification of drug targets will still be the focus of DKD research.

Targeted Quantification of Peptides Using Miniature Mass Spectrometry.

Proteomics by mass spectrometry (MS) allows for the identification of amino acid/peptide sequences in complex mixtures. Peptide analysis and quantitation enables screening of protein biomarkers and targeted protein biomarker analysis for clinical applications. Whereas miniature mass spectrometers have primarily demonstrated point-of-care analyses with simple procedures aiming at drugs and lipids, it would be interesting to explore their potential in analyzing proteins and peptides. In this work, we adapted a miniature MS instrument for peptide analysis. A mass range as wide as 100-2000 m/z was achieved for obtaining peptide spectra using this instrument with dual linear ion traps. MS2 and MS3 can be performed to analyze a wide range of peptides. The parameters of pressure, electric potentials, and solution conditions were optimized to analyze peptides with molecular weights between 900 and 1800 Da. The amino acid sequences were identified using both beam-type and in-trap collision-induced dissociation, and the results were comparable to those obtained by a commercial quadrupole time-of-flight mass spectrometer. With product ion monitoring scan mode, peptide quantitation was performed with a limit of detection of 20 nM achieved for the Met peptide. The method developed has also been applied to the analysis of the trypsin-digested cell lysate of SKBR3 cells with a low expression level of the Met gene.

Abstract 4060: Discovery and screening of protein biomarkers with the FirePlex Technology Platform

Abstract In patients and animal models, molecular biomarkers are used as indicators of normal and pathogenic processes. In drug discovery and screening pipelines, molecular biomarkers are used to assess the mechanism of action, efficacy, and toxicity of lead compounds. To address the need for rapid and sensitive biomarker quantitation, we have developed the FirePlex® Technology Platform. Utilizing patented hydrogel particles and a three-region encoding design, FirePlex assays allow for true, in-well multiplexing, providing flexible and customizable quantification of miRNA and protein analytes. To facilitate biomarker discovery studies, we offer our standard-throughput, flow cytometry-based assays which enable quantitation of up to 75 miRNA or protein analytes per sample, from only 20 µl of input. These assays demonstrate 5 logs of dynamic range and offer highly sensitive quantitation of analytes in serum, plasma, cell culture supernatant, urine, and CSF without the need for sample processing or RNA isolation. For drug discovery and screening studies, we offer our high-throughput FirePlex (FirePlex®-HT) Immunoassays for quantitation of up to 10 protein analytes per sample from only 6.25 µl biofluid input, in 384-well plate format. FirePlex-HT assays provide 3-4 logs dynamic range, demonstrate 1-100 pg/ml sensitivity, and have been validated in serum, plasma, and cell culture supernatant. The two-step workflow, no-wash assay format, and readout on high-content imagers limit hands-on time and are amenable to automation, thus making FirePlex-HT ideally suited for high-throughput screening studies. In addition, here we introduce our high-throughput miRNA assays for screening miRNA biomarkers in 96-well or 38-4well plate format, with readout on high-content imagers. Here we present data from miRNA and protein profiling studies using the FirePlex platform, and introduce the simplified workflow of the FirePlex-HT® immunoassays with data demonstrating the performance for quantifying key cytokines in multiplex, in biological samples. Together, this novel combination of multiplexed, high-sensitivity assays and bioinformatics tools enables rapid quantitation of protein biomarker signatures in biofluid specimens. Citation Format: Amy Perea, Russell Neuner, Bianca Heinrich, Graeme Doran, Wayne Austin, Conor Rafferty, Matt Camilleri, Michael Tackett, Long To, Elnaz Atabakhsh, James Murray, Daniel Pregibon. Discovery and screening of protein biomarkers with the FirePlex Technology Platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4060.

A Guide to Mass Spectrometry-Based Quantitative Proteomics.

Proteomics has become an attractive science in the postgenomic era, given its capacity to identify up to thousands of molecules in a single, complex sample and quantify them in an absolute and/or relative manner. The use of these techniques enables understanding of cellular and molecular mechanisms of diseases and other biological conditions, as well as identification and screening of protein biomarkers. Here we provide a straightforward, up-to-date compilation and comparison of the main quantitation techniques used in comparative proteomics such as in vitro and in vivo stable isotope labeling and label-free techniques. Additionally, this chapter includes common methods for data acquisition in proteomics and some appropriate methods for data processing. This compilation can serve as a reference for scientists who are new to, or already familiar with, quantitative proteomics.

Label-free femtomolar cancer biomarker detection in human serum using graphene-coated surface plasmon resonance chips

Sensitive and selective detection of cancer biomarkers is vital for the successful diagnosis of early stage cancer and follow-up treatment. Surface Plasmon Resonance (SPR) in combination with different amplification strategies is one of the analytical approaches allowing the screening of protein biomarkers in serum. Here we describe the development of a point-of-care sensor for the detection of folic acid protein (FAP) using graphene-based SPR chips. The exceptional properties of CVD graphene were exploited to construct a highly sensitive and selective SPR chip for folate biomarker sensing in serum. The specific recognition of FAP is based on the interaction between folic acid receptors integrated through π-stacking on the graphene coated SPR chip and the FAP analyte in serum. A simple post-adsorption of human serum:bovine serum albumin (HS:BSA) mixtures onto the folic acid modified sensor resulted in a highly anti-fouling interface, while keeping the sensing capabilities for folate biomarkers. This sensor allowed femtomolar (fM) detection of FAP, a detection limit well adapted and promising for quantitative clinical analysis.

Abstract 2495: Quantitative screening of protein biomarkers of hepatocellular carcinoma by antibody array

Abstract Protein biomarkers can be key indicators for evaluating the presence or progression of a human disease or therapeutic response to treatment. We recently carried out a biomarker screening in hepatocellular carcinoma (HCC) using our antibody array platform. Using 25 pairs of HCC and adjacent control tissue samples, the expression levels of 274 proteins including growth factors, inflammation factors, angiogenesis, apoptosis factors and adhesion molecules, were examined using an antibody arrays. A panel of proteins demonstrating significant differences in expression levels between HCC and adjacent control samples was identified by significance analysis of microarrays (SAM) and Wilcoxon signed-rank test, combined with fold-change determination. Additionally, proteomic analysis algorithms were used to capture GO annotations and to construct signaling pathways and protein-protein interaction networks for these proteins. Proteins selected through these comprehensive analyses were designated as potential biomarkers and were well able to distinguish hepatocellular carcinoma tissue samples from paired, adjacent controls with cluster tools. The expression levels of several proteins were further evaluated by enzyme-linked immunosorbent assay (ELISA). Finally, we performed follow-up verification studies on selected proteins (Nidogen-1 and CEACAM-1) for detection of HCC in 164 pairs of serum samples from HCC patients and normal subjects with reverse phase protein array (RPPA). Our work reveals promising protein biomarkers for detection of HCC. Citation Format: Shuhong Luo, Ruochun Huang, Zhongsheng Wang, Yun-Ru Chen, Jinfei Lin, Ruo-Pan Huang. Quantitative screening of protein biomarkers of hepatocellular carcinoma by antibody array. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2495. doi:10.1158/1538-7445.AM2014-2495

Ultrasensitive multiplexed protein biomarker detection based on electrochemical tag incorporated polystyrene spheres as label

Multiplexed electrochemical immunosensor was developed for ultrasensitive detection of interleukin-6 (IL-6) and interleukin-17 (IL-17) using electrochemical tag incorporated polystyrene sphere (PS) as label. The electrochemical tag contained in the PS, cadmium ion (Cd2+) or ferrocene (Fc), could be effectively detected by square wave voltammetry (SWV) after dissolving the PS with organic solvent to release the electrochemical tags onto electrode surface. With the immobilization of two different antibodies onto the PS surface, respectively, the position and intensity of the current peaks due to the two electrochemical tags could reflect the identity and level of the corresponding protein biomarkers. The significant amount of electrochemical tags incorporated into PS greatly enhanced the detection sensitivity. The proposed immunoassay exhibited high sensitivity and good selectivity for the detection of IL-6 and IL-17. The response current was linear to the logarithm concentrations of IL-6 and IL-17 in the range from 1pg/mL to1ng/mL and 2pg/mL to 1ng/mL, respectively. The detection limits of IL-6 and IL-17 were 0.5 and 1pg/mL (S/N=3). These results suggested that this electrochemical immunosensor would be widely applied for clinical screening of protein biomarkers.

Sensitive immunosensor for tumor necrosis factor α based on dual signal amplification of ferrocene modified self-assembled peptide nanowire and glucose oxidase functionalized gold nanorod

Sensitive electrochemical immunosensor for the detection of protein biomarker tumor necrosis factor α (TNF-α) was reported that uses ferrocene carboxylic acid (Fc) functionalized self-assembled peptide nanowire (Fc-PNW) as sensor platform and glucose oxidase (GOx) modified gold nanorod (GNR) as label. Greatly enhanced sensitivity is achieved based on a dual signal amplification strategy: first, the synthesized Fc-PNW used as the sensor platform increased the loading of primary anti-TNF-α antibody (Ab1) onto electrode surface due to its large surface area. At the same time, the Fc moiety on the nanowire is used as a mediator for GOx to catalyze the glucose reaction. Second, multiple GOx and secondary anti-TNF-α antibody (Ab2) molecules are bounded onto each GNR to increase the sensitivity of the immunosensor. After the preparation of the immunosensor based on the traditional sandwich protocol, the response of the immunosensor towards glucose was used as a signal to differentiate various concentrations of TNF-α. The resulting immunosensor has high sensitivity, wide linear range (0.005–10ng/mL) and good selectivity. This immunosensor preparation strategy is a promising platform for clinical screening of protein biomarkers.

Surface plasmon resonance biosensor for parallelized detection of protein biomarkers in diluted blood plasma

Surface plasmon resonance (SPR) biosensor for high-throughput screening of protein biomarkers in diluted blood plasma is reported. The biosensor combines a high-resolution SPR imaging sensor and a high-density protein array with low-fouling background. The SPR imaging sensor utilizes polarization contrast and advanced referencing and provides a total of 120 sensing areas (each 200 μm × 150 μm). Antibodies are immobilized on the sensing areas via hybridization of antibody–oligonucleotide conjugates to thiolated complementary oligonucleotides microspotted on the sensor surface (DNA-directed immobilization). A low-fouling background is achieved by covalent immobilization of bovine serum albumin to carboxyl-terminated thiols filling the areas among the thiolated oligonucleotides and outside the sensing areas. The biosensor was evaluated for detection of protein biomarkers relevant to cancer diagnostics—human chorionic gonadotropin (hCG) and activated leukocyte cell adhesion molecule (ALCAM) both in buffer and in 10% blood plasma. Limits of detection as low as 45 ng/mL (ALCAM) and 100 ng/mL (hCG) were achieved in blood plasma samples.

Quantitative screening of protein biomarkers of early glycation, advanced glycation, oxidation and nitrosation in cellular and extracellular proteins by tandem mass spectrometry multiple reaction monitoring

Glycation of proteins forms fructosamines and AGEs (advanced glycation end products). Oxidative and nitrosative stress leads to the formation of oxidative and nitrosative modifications. The modified amino acid residues formed in these processes are biomarkers of protein damage: some are risk markers and some may be risk factors for disease development. We developed a method for the concurrent quantitative measurement of 16 biomarkers indicative of protein glycation, oxidation and nitrosation damage using LC-MS/MS (LC with tandem MS detection). Underivatized analytes were detected free in physiological fluids and in enzymatic hydrolysates of cellular and extracellular proteins. Hydroimidazolones were the most important glycation biomarkers, and methionine sulphoxide was the most important oxidative biomarker quantitatively; 3-nitrotyrosine was the biomarker of nitrosation. Quantitative screening showed high levels of AGEs in cellular protein and moderate levels in protein of blood plasma. Levels of 3-nitrotyrosine were typically 100-fold lower than this. The major glycation adducts in blood plasma had high renal clearances in normal healthy human subjects, whereas methionine sulphoxide and 3-nitrotyrosine had low renal clearances due to further metabolism. Physiological AGEs in blood plasma were eliminated from the circulation in the kidney and not in the liver. LC-MS/MS peptide mapping was also used to locate the protein biomarkers. These studies reveal that advanced glycation is a significant modification of cellular and extracellular protein. The enzymatic defences against glycation, antioxidants and proteasomal protein degradation inside cells are probable factors regulating biomarker levels of cellular protein.