A novel multiplexed immunoassay identifies CEA,IL-8 and prolactin as prospective markers for Dukes’ stages A-D colorectal cancers

Background

Current methods widely deployed for colorectal cancers (CRC) screening lack the necessary sensitivity and specificity required for population-based early disease detection. Cancer-specific protein biomarkers are thought to be produced either by the tumor itself or other tissues in response to the presence of cancers or associated conditions. Equally, known examples of cancer protein biomarkers (e.g., PSA, CA125, CA19-9, CEA, AFP) are frequently found in plasma at very low concentration (pg/mL-ng/mL). New sensitive and specific assays are therefore urgently required to detect the disease at an early stage when prognosis is good following surgical resection. This study was designed to meet the longstanding unmet clinical need for earlier CRC detection by measuring plasma candidate biomarkers of cancer onset and progression in a clinical stage-specific manner. EDTA plasma samples (1 μL) obtained from 75 patients with Dukes’ staged CRC or unaffected controls (age and sex matched with stringent inclusion/exclusion criteria) were assayed for expression of 92 human proteins employing the Proseek® Multiplex Oncology I proximity extension assay. An identical set of plasma samples were analyzed utilizing the Bio-Plex Pro™ human cytokine 27-plex immunoassay.

Results

Similar quantitative expression patterns for 13 plasma antigens common to both platforms endorsed the potential efficacy of Proseek as an immune-based multiplex assay for proteomic biomarker research. Proseek found that expression of Carcinoembryonic Antigen (CEA), IL-8 and prolactin are significantly correlated with CRC stage.

Conclusions

CEA, IL-8 and prolactin expression were found to identify between control (unaffected), non-malignant (Dukes’ A + B) and malignant (Dukes’ C + D) stages.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9081-x) contains supplementary material, which is available to authorized users.     

Immunoreactive hephaestin and ferroxidase activity are present in the cytosolic fraction of rat enterocytes

Discovered over a decade ago, hephaestin (Heph) has been implicated as a ferroxidase (FOX) vital for intestinal iron absorption. Stringent structural or kinetic data derived from purified, native protein is however lacking, leading to the hypothesis that an alternate, undiscovered form of Heph could exist in mammalian enterocytes. This possibility was tested using laboratory rodent and cell culture models. Cytosolic and membrane fractions were obtained from rat enterocytes and purity of the fractions was assessed. Western blot analyses revealed Heph in cytosol obtained by three different methods, ruling out the possibility of a method-induced artifact being the major contributor to this observation. Absence of two different membrane-proteins, ferroportin 1 and Menke's copper ATPase in cytosol, and the absence of lipids in representative cytosolic samples tested by thin layer chromatography, eliminated significant membrane contamination of cytosol. Further, immunohisto- and immunocyto-chemical analyses identified Heph in rat enterocytes and in two intestinal epithelial cell lines, IEC-6 and Caco-2, intracellularly. Additionally, cytosolic Heph increased upon iron-deprivation but more important, decreased significantly upon copper-deprivation, mimicking the response of membrane-bound Heph. Moreover, FOX activity was present in rat cytosol, and was partly inhibited by anti-Heph antibody. Finally, lack of immunodetectable ceruloplasmin (Cp) by western blot precluded Cp as an underlying cause of this activity. These data demonstrate that rat enterocytes contain a soluble/cytosolic form of Heph possibly contributing to the observed FOX activity.     

A motor neuron disease-associated mutation in p150Glued perturbs dynactin function and induces protein aggregation

The microtubule motor cytoplasmic dynein and its activator dynactin drive vesicular transport and mitotic spindle organization. Dynactin is ubiquitously expressed in eukaryotes, but a G59S mutation in the p150Glued subunit of dynactin results in the specific degeneration of motor neurons. This mutation in the conserved cytoskeleton-associated protein, glycine-rich (CAP-Gly) domain lowers the affinity of p150Glued for microtubules and EB1. Cell lines from patients are morphologically normal but show delayed recovery after nocodazole treatment, consistent with a subtle disruption of dynein/dynactin function. The G59S mutation disrupts the folding of the CAP-Gly domain, resulting in aggregation of the p150Glued protein both in vitro and in vivo, which is accompanied by an increase in cell death in a motor neuron cell line. Overexpression of the chaperone Hsp70 inhibits aggregate formation and prevents cell death. These data support a model in which a point mutation in p150Glued causes both loss of dynein/dynactin function and gain of toxic function, which together lead to motor neuron cell death.     

A robust hybrid peptide crystal formed with weak hydrogen bonds

In the course of our work relating to the design of a bihelical structure (I) from diphenic anhydride by tethering with cystine di-OMe, stable, hard, and rigid crystals, mp 215-218 degrees C were isolated in low yields ( approximately 2%). The crystal structure established that it was a bis amide (II) arising from diphenic acid and cystine di-OMe [(II), C(22)H(22)N(2)O(6)S(2) (a = 9.897 (1) A, b = 12.210 (1) A, c = 18.192 (1) A, sp. gr. P2(1)2(1)2(1))]. An authentic sample of (II) was subsequently prepared in 47% yields by condensation of diphenic acid dichloride with cystine di-OMe. A most surprising feature of II was, despite its high density, rigidity, and hardness, it did not exhibit any normal hydrogen bonds. The nearest approximation to a "usual" hydrogen bond was the single NH...OC linkage that occurred between molecules along a twofold screw axis. In this linkage, N...O = 3.265 A and H...O = 2.43 A, values that are at least 10% longer than those usually observed in peptides. The rigidity of the crystals appears to depend upon many weak hydrogen bonds of the type CH...O, CH...pi, CH...S, and NH...S working in concert. Even these attractions have separations that are at the high end of the range of previously observed values, although some of the weak hydrogen bonds have been rarely reported and have poorly defined ranges. The attractive effect of each of these weak bonds may be enhanced by the occurrence of a number of them in a parallel fashion like rungs in a ladder.     

Description and recognition of regular and distorted secondary structures in proteins using the automated protein structure analysis method

The Automated Protein Structure Analysis (APSA) method, which describes the protein backbone as a smooth line in three‐dimensional space and characterizes it by curvature κ and torsion τ as a function of arc length s, was applied on 77 proteins to determine all secondary structural units via specific κ(s) and τ(s) patterns. A total of 533 α‐helices and 644 β‐strands were recognized by APSA, whereas DSSP gives 536 and 651 units, respectively. Kinks and distortions were quantified and the boundaries (entry and exit) of secondary structures were classified. Similarity between proteins can be easily quantified using APSA, as was demonstrated for the roll architecture of proteins ubiquitin and spinach ferridoxin. A twenty‐by‐twenty comparison of all α domains showed that the curvature‐torsion patterns generated by APSA provide an accurate and meaningful similarity measurement for secondary, super secondary, and tertiary protein structure. APSA is shown to accurately reflect the conformation of the backbone effectively reducing three‐dimensional structure information to two‐dimensional representations that are easy to interpret and understand. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

Recursive cluster elimination based support vector machine for disease state prediction using resting state functional and effective brain connectivity

Background

Brain state classification has been accomplished using features such as voxel intensities, derived from functional magnetic resonance imaging (fMRI) data, as inputs to efficient classifiers such as support vector machines (SVM) and is based on the spatial localization model of brain function. With the advent of the connectionist model of brain function, features from brain networks may provide increased discriminatory power for brain state classification.

Methodology/Principal Findings

In this study, we introduce a novel framework where in both functional connectivity (FC) based on instantaneous temporal correlation and effective connectivity (EC) based on causal influence in brain networks are used as features in an SVM classifier. In order to derive those features, we adopt a novel approach recently introduced by us called correlation-purged Granger causality (CPGC) in order to obtain both FC and EC from fMRI data simultaneously without the instantaneous correlation contaminating Granger causality. In addition, statistical learning is accelerated and performance accuracy is enhanced by combining recursive cluster elimination (RCE) algorithm with the SVM classifier. We demonstrate the efficacy of the CPGC-based RCE-SVM approach using a specific instance of brain state classification exemplified by disease state prediction. Accordingly, we show that this approach is capable of predicting with 90.3% accuracy whether any given human subject was prenatally exposed to cocaine or not, even when no significant behavioral differences were found between exposed and healthy subjects.

Conclusions/Significance

The framework adopted in this work is quite general in nature with prenatal cocaine exposure being only an illustrative example of the power of this approach. In any brain state classification approach using neuroimaging data, including the directional connectivity information may prove to be a performance enhancer. When brain state classification is used for disease state prediction, our approach may aid the clinicians in performing more accurate diagnosis of diseases in situations where in non-neuroimaging biomarkers may be unable to perform differential diagnosis with certainty.     

In vitro expansion of Ag-specific T cells by HLA-A*0201-transfected K562 cells for immune monitoring

BACKGROUND: Development of a practical and sensitive assay for evaluating immune responses against cancer Ag has been a challenge for immune monitoring of patients. We have established a reproducible method using peptide-pulsed K562-A*0201 cells as APC to expand Ag-specific T cells in vitro. This method may be applied for monitoring T-cell responses in cancer immunotherapy clinical trials. METHODS: Autologous PBMC from HLA-A*0201+ healthy donors and patients with melanoma were stimulated with peptide-pulsed K562-A*0201 cells under varying conditions. We investigated (1) different culture conditions, including the requirements for serum and cytokines for expansion of CD8+ T lymphocytes; (2) a range of peptide concentrations for Ag loading; (3) phenotypic characterization of responding T cells; and (4) APC:responder ratios and their effects on T-cell expansion. We validated these conditions by ELISPOT and intracellular cytokine staining (ICS) assays using peptides from influenza, Epslein-Barr Virus (EBV) and tyrosinase. RESULTS: Conditions for optimal T-cell expansion using K562-A*0201 APC included input of 2 x 10(6) PBMC, a 10 microg/mL peptide concentration to pulse K562-A*0201 cells, a 1:30 APC:responder T-cell ratio and culture in 10% autologous plasma supplemented with IL-2 and IL-15. In these conditions, Ag-specific T cells expanded >100-fold over a 10-day culture period (peak at day 12). DISCUSSION: This bulk culture method is simple and reliable for expanding human Ag-specific T cells using peptide-pulsed K562-A*0201 cells. This HLA-matched APC line can be adapted to other HLA haplotypes, and has advantages for monitoring clinical trials of immunotherapy with limited availability of autologous APC and PBMC from patients.     

Classification of large array surface myoelectric potentials from subjects with and without low back pain.

An algorithm was developed and tested for differentiating between the spatial distribution of large arrays of surface electromyographic (LASE) data from subjects with and without low back pain (LBP). The surface EMG data from 62 channels were collected from the low back of 161 healthy and 44 acute (less than 6-weeks) LBP subjects in three minimum stress postural positions including standing, 20 degrees of trunk flexion (at hip joint) and standing with arms extended forward holding a 1.36kg (3lb) weight in each hand. These data were statistically analyzed and the spatial distribution of the root mean square (RMS) values was used in a multivariate quadratic discriminant model to reclassify the healthy and acute LBP subjects. The most predictive results were obtained from the 'flexion' group of experiments and correctly reclassified 95.5% (42/44) of the acute LBP subjects and 99.4% (160/161) of the healthy subjects. The success rate of this reclassification based on surface distribution of myoelectric potentials was found to be better than the reported patient classifications based on a smaller set of electrode pairs using fewer subjects [Peach JP, McGill SM, Classification of low back pain with use of spectral electromyogram parameters. Spine 23(10):1998;1117-23; Roy SH, De Luca CJ, Emley M, Oddsson LI, Buijs RJ, Levins JA, Newcombe DS, Jabre JF. Classification of back muscle impairment based on the surface electromyographic signal. J Rehabil Res Dev 34(4):1997;405-14 [review]]. The results indicated the potential of the model for clinical patient classification.