A peptide-centric approach to breast cancer biomarker discovery utilizing label-free multiple reaction monitoring mass spectrometry

We report an approach for multiplex analysis of cancer biomarkers based on the measurement of diagnostic peptides in whole tissue protein digests. Label-free quantitation with MS3 multiple reaction monitoring (MRM) was developed to afford accurate analysis of prospective marker peptides in a panel of breast tumors. This approach provides an economical and robust alternative to stable isotope-based methods. It is equally applicable to the analysis of samples derived from tissue biopsy, aspirate, or plasma and can be easily translated to clinic.     

Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective

Proteomics holds great promise in personalized medicine for cancer in the post-genomic era. In the past decade, clinical proteomics has significantly evolved in terms of technology development, optimization and standardization, as well as in advanced bioinformatics data integration and analysis. Great strides have been made for characterizing a large number of proteins qualitatively and quantitatively in a proteome, including the use of sample fractionation, protein microarrays and MS. It is believed that differential proteomic analysis of high-quality clinical biospecimen (tissue and biofluids) can potentially reveal protein/peptide biomarkers responsible for cancer by means of their altered levels of expression and/or PTMs. Multiple reaction monitoring, a multiplexed platform using stable isotope dilution-MS with sensitivity and reproducibility approaching that of traditional ELISAs commonly used in the clinical setting, has emerged as a potentially promising technique for next-generation high-throughput protein biomarker measurements for diagnostics and therapeutics.     

The human synovial fluid proteome: A key factor in the pathology of joint disease

This review aims to summarise our knowledge to date on the protein complement of the synovial fluid (SF). The tissues, structure and pathophysiology of the synovial joint are briefly described. The salient features of the SF proteome, how it is composed and the influence of arthritic disease are highlighted and discussed. The concentrations of proteins that have been detected and quantified in SF are drawn together from the literature on osteoarthritis, rheumatoid arthritis and juvenile idiopathic arthritis. The measurements are plotted to give a perspective on the dynamic range of protein levels within the SF. Approaches to proteomic analysis of SF to date are discussed along with their findings. From the recent literature reviewed within, it is becoming increasingly clear that analysis of the SF proteome as a whole, could deliver the most valuable differential diagnostic fingerprints of a number of arthritic disorders. Further development of proteomic platforms could characterise prognostic profiles to improve the clinician's ability to resolve unremitting disease by existing and novel therapeutics.     

On-chip cell migration assay for quantifying the effect of ethanol on MCF-7 human breast cancer cells

Ethanol consumption is associated with the risk of breast cancer progression; however, the mechanism of relationship has not yet been fully explained. Research on breast cancer cell migration after ethanol stimulation may give hope for a better understanding of the disease and oncotherapy. Conventional cell migration assays such as Boyden chamber and wound-healing assays are easy to conduct for this purpose; however, these assays have inherent limitations. In this study, we quantified the effect of ethanol on MCF-7 hunam breast cancer cells using a microfluidics-based wound-healing assay. Wounds were prepared by partially digesting a confluent cell sheet using parallel laminar flows in the presence of protease trypsin. The cells at the leading edge of the wound remained intact. Cell image analysis indicates that all the cells cultured in the microdevice took on a good morphology and monolayer growth status. Cell viability assay demonstrates that cell viability decreased with the increase in ethanol concentration and treatment time. For 0, 22, 43, and 65 mmol/l of ethanol, cell viability after being cultured for 24 h was 100%, 99.6%, 99.4%, and 98.4%, respectively. Studying MCF-7 human breast cancer cell migration when treated with different ethanol concentrations revealed that the cell migration distance is directly proportional with ethanol concentration. After being cultured for 24 h at 37°C and 5% CO₂, the maximal cell migration distance was 231, 283, and 332 μm for 22, 43, and 65 mmol/l ethanol, respectively; all results were higher than the blank test (i.e., ethanol-free test, 218 μm). These findings will be beneficial in developing microfluidic device applications for future research on breast tumor therapy in a biomimetic microenvironment and for developing new methods for breast cancer therapy.     

High-throughput measurement of Ca by accelerator mass spectrometry to quantitate small changes in individual human bone turnover rates

Biochemical markers of bone turnover suffer from large analytical and natural fluctuations (20–30%), making small differences in bone resorption impossible to resolve. This limits the clinical utility of such markers for individuals with the skeletal complications associated with many disease states (e.g., metastatic cancer, renal failure, osteoporosis). We are developing the capability to measure small changes (5–10%) in bone turnover rate in vivo by tagging the living skeleton with ⁴¹Ca. Among the stable and radioactive calcium isotopes, only ⁴¹Ca is useful for direct quantitation of bone turnover because it is extremely rare in nature and radiologically benign (10⁵ years half-life, pure electron capture decay). The ratio of this tracer to total calcium remains quantifiable in body fluids and excreta via accelerator mass spectrometry (AMS) for many years following a single physiological-sized oral or intravenous dose. The highly automated AMS instrumentation and streamlined sample preparation allows a single operator to prepare or run more than 100 samples per day—significantly more than other ⁴¹Ca programs worldwide. We intend to exploit these measurements for earlier diagnosis of pathological processes and interactive intervention with therapeutic agents, allowing modulation of these agents to obtain the best individual result for a patient.     

Expression of tropomyosin alpha 4 chain is increased in esophageal squamous cell carcinoma as evidenced by proteomic profiling by two-dimensional electrophoresis and liquid chromatography-mass spectrometry/mass spectrometry

To identify proteins associated with esophageal carcinogenesis, we performed protein profiling of 16 esophageal squamous cell carcinomas (ESCCs) and paired noncancerous tissues by 2-DE and MS/MS. In cancerous tissues, three spots showed significant up-regulation in the amount of protein, while eight spots were significantly down-regulated. The identities of the spots were determined by PMF with LC-MS/MS and were confirmed by immunoblotting. The up-regulated proteins were tropomyosin alpha 4 chain, transgelin, and pyruvate kinase. The down-regulated proteins were serum albumin precursor, isoforms of annexin A1, tropomyosin beta chain, 14-3-3 protein sigma, and isoforms of serotransferrin precursor. In all 16 cases, up-regulation of the tropomyosin alpha 4 chain was confirmed by immunoblotting. Localization of the tropomyosin alpha 4 chain in ESCC cells and adjacent fibroblasts was confirmed by immunohistochemistry.     

Computer-aided thermodynamics of fcc solid ternary Fe–Co–Cr alloys by Knudsen cell mass spectrometry

The fcc solid ternary Fe–Co–Cr alloys have been investigated thermodynamically by means of computer-aided Knudsen cell mass spectrometry. The “Digital Intensity Ratio” (DIR) method has been applied for the determination of the thermodynamic excess properties. The ternary thermodynamically adapted power (TAP) series concept is used for the algebraic representation of the molar excess properties. The corresponding TAP parameters as well as the values of the molar excess Gibbs energies G^E, of the molar heats of mixing H^E, of the molar excess entropies S^E, and of the thermodynamic activities at 1673 K are presented.     

相似度算法在手写签名质谱成像鉴定中的应用研究

质谱成像技术无需任何样品预处理,即可获取待测样品的分子信息和分布情况。本文采用表面解吸常压化学电离质谱(SDAPCI-MS)技术对手写签名样品进行检测,通过对所得的质谱特征峰信号进行成像处理,获取书写油墨分布的强度信息。实验结果表明真实签名和伪造签名因为笔压轻重不同而油墨分布位置不同,据此能够区分签名的真伪。应用相似度算法对手写签名的特征成像数据进行分析,在样品量较少的情况下,能够客观的比较真迹之间以及真迹和伪迹之间的相似程度,进而实现对真伪签名的准确鉴定。本方法操作简便,耗时较短,对手写笔迹的鉴定具有重要的借鉴意义。     

Comparative proteome profiling of MCF10A and 184A1 human breast epithelial cells emphasized involvement of CDK4 and cyclin D3 in cell proliferation

Acquiring high proliferation rate is crucial for carcinogenic transformation of cells. We report here proteome profiling of human breast epithelial cells with low (184A1) and high (MCF10A) proliferation rates. We identified 183 proteins in 184A1 and 318 proteins in MCF10A cells. These datasets provide the most comprehensive proteome annotations of 184A1 and MCF10A cells. Proteins were taken for identification from 2-D gels in a systematic and unbiased way. Functional clustering of the identified proteins showed similarities in distribution of proteins to the same functional domains, indicating similarities in proteomes of 184A1 and MCF10A cells. Among observed differences in protein expression, we validated correlation of expression of endogenous cyclin-dependent kinase 4 (CDK4), cyclin D3, cdc25B, and p38γ with cell proliferation. Furthermore, down-regulation of CDK4 and cyclin D3 with specific siRNA inhibited cell proliferation, which emphasized the role of CDK4 and cyclin D3 in enhancement of cell proliferation rate of human breast epithelial cells.     

Analysis of mass spectrometry data of cerebral stroke samples: an evolutionary computation approach to resolve and quantify peptide peaks

A preliminary investigation of cerebral stroke samples injected into a mass spectrometer is performed from an evolutionary computation perspective. The detection and resolution of peptide peaks is pursued for the purpose of automatically and accurately determining unlabeled peptide quantities. A theoretical peptide peak model is proposed and a series of experiments are then pursued (most within a distributed computing environment) along with a data preprocessing strategy that includes (i) a deisotoping step followed by (ii) a peak picking procedure, followed by (iii) a series of evolutionary computation experiments oriented towards the investigation of their capability for achieving the aforementioned goal. Results from four different genetic algorithms (GA) and one differential evolution (DE) algorithm are reported with respect to their ability to find solutions that fit within the framework of the presented theoretical peptide peak model. Both unconstrained and constrained (as determined by a course grained preprocessing stage) solution space experiments are performed for both types of evolutionary algorithms. Good preliminary results are obtained.     

A qualitative proteome investigation of the sediment portion of human urine: Implications in the biomarker discovery process

Inherent to the biomarker discovery process is a comparative analysis of physiological states. It is therefore critical that the proteome detection protocol does not bias the analysis. With urine, the sediment portion, obtained upon thawing frozen urine, is routinely discarded prior to proteome analysis. However, our results demonstrate that such a practice inadvertently induces bias, having significant implications in the biomarker discovery process. We present the first proteome investigation of human urinary sediments, identifying 60 proteins in this phase by MS. Many sediment proteins were also detected in the urinary supernatant, indicating that several proteins partition between the two phases. This partitioning is dependant on the pH of the sample, as well as the degree of sample agitation. As a consequence of discarding the sediment portion of urine, the concentration of potential candidate biomarkers in the supernatant phase will be altered or, in other instances, may be completely removed from the sample. To minimize this, the pH of all samples should first be normalized, and the samples vigorously vortexed prior to discarding the sediments. For more comprehensive biomarker investigations, we suggest that urinary sediments be analyzed along with the supernatant proteins.     

Automated breast cancer detection by thermography : performance goal and diagnostic feature identification

This paper presents the methodology used for establishing a performance goal and identifying the diagnostic features in a program to develop an automated system for breast cancer detection based on thermographic principles. The receiver operating characteristic (ROC) curve approach is used to evaluate both observer classification and classification rules based on an observer's evaluation of diagnostic features. The multivariate logistic function is applied to two sets of observer evaluated feature sets using 623 normal and 122 breast cancer diagnosed subjects. It is shown that the observer outperforms the multivariate logistic function classifier based on the diagnostic features.     

Analysis of the human immune response to vaccinia by use of a novel protein microarray suggests that antibodies recognize less than 10% of the total viral proteome

Control of smallpox by mass vaccination was one of the most effective public health measures ever employed for eradicating a devastating infectious disease. However, new methods are needed for monitoring smallpox immunity within current vulnerable populations, and for the development of replacement vaccines for use by immunocompromized or low-responding individuals. As a measure for achieving this goal, we developed a protein microarray of the vaccinia virus proteome by using high-throughput baculovirus expression and purification of individual elements. The array was validated with therapeutic-grade, human hyperimmune sera, and these data were compared to results obtained from individuals vaccinated against smallpox using Dryvax. A high level of reproducibility with a very low background were apparent in repetitive assays that confirmed previously reported antigens and identified new proteins that may be important for neutralizing viral infection. Our results suggest that proteins recognized by antibodies from all vaccinees constituted <10% of the total vaccinia proteome.     

Modulation of cancer cell line differentiation: A neglected proteomic analysis with potential implications in pathophysiology, diagnosis, prognosis, and therapy of cancer

The recent development of compounds that induce cell differentiation in various types of cancer cells has enabled the molecular mechanisms governing this kind of induced cancer regression to be investigated. Moreover, this approach to investigating the pathophysiology of neoplasia represents a promising experimental model for proteomic analysis of cancer cells. Modulating neoplastic cell differentiation grade may reveal cytodifferentiation-related protein expression changes, and doing so in vitro has the advantage of less biological variation. Hence, this analysis brings attention to molecular targets of the so-called differentiating factors (i.e., retinoids, hybrid polar compounds, tyrosine kinase inhibitors, etc.) as well as proteins that are frequently associated with differentiation/dedifferentiation processes. The in vitro study of these proteins and of their pathogenetic roles in cancer may ultimately result in the discovery of cancer biomarkers with diagnostic, prognostic, and therapeutic applications.     

The mass appraisal of the real estate by computational intelligence

Mass appraisal is the systematic appraisal of groups of properties as of a given date using standardized procedures and statistical testing. Mass appraisal is commonly used to compute real estate tax. There are three traditional real estate valuation methods: the sales comparison approach, income approach, and the cost approach. Mass appraisal models are commonly based on the sales comparison approach. The ordinary least squares (OLS) linear regression is the classical method used to build models in this approach. The method is compared with computational intelligence approaches – support vector machine (SVM) regression, multilayer perceptron (MLP), and a committee of predictors in this paper. All the three predictors are used to build a weighted data-depended committee. A self-organizing map (SOM) generating clusters of value zones is used to obtain the data-dependent aggregation weights. The experimental investigations performed using data cordially provided by the Register center of Lithuania have shown very promising results. The performance of the computational intelligence-based techniques was considerably higher than that obtained using the official real estate models of the Register center. The performance of the committee using the weights based on zones obtained from the SOM was also higher than of that exploiting the real estate value zones provided by the Register center.     

Explanation and reliability of prediction models: the case of breast cancer recurrence

In this paper, we describe the first practical application of two methods, which bridge the gap between the non-expert user and machine learning models. The first is a method for explaining classifiers’ predictions, which provides the user with additional information about the decision-making process of a classifier. The second is a reliability estimation methodology for regression predictions, which helps the users to decide to what extent to trust a particular prediction. Both methods are successfully applied to a novel breast cancer recurrence prediction data set and the results are evaluated by expert oncologists.     

Endogeneous peptide profiling of cerebrospinal fluid by MALDI-TOF mass spectrometry: Optimization of magnetic bead-based peptide capture and analysis of preanalytical variables

Cerebrospinal fluid (CSF) perfuses the brain and spinal cord. CSF contains peptides and proteins important for brain physiology and potentially also relevant to brain pathology. High-throughput endogeneous peptide profiling by MS is an emerging approach for disease diagnosis and biomarker discovery. A magnetic bead-based method for off-line serum peptide capture coupled to MALDI-TOF-MS has been introduced recently. In this study, we optimize the peptide capture method for profiling of CSF and investigate the effect of a number of preanalytical variables. The CSF profiles contain ～100 reliably detected peptides at m/z 800-4000 with reproducible ion intensities (average 7% CV). The investigated preanalytical variables include: time at room temperature (RT) before storage, storage temperature, freeze-thawing cycles, and blood contamination. The CSF peptidome (<20?kDa) is relatively stable and can withstand a few hours at RT and several freeze-thaw cycles. Several peptides sensitive to storage at -20°C, including Cystatin C, were assigned based on mass or identified by MS/MS. Hemoglobin α and β chains were detected in blood contaminated samples, at levels invisible to the eye (0.01%). These peptides may be used for quality control in a MALDI-TOF-MS screening strategy to select high quality samples for in-depth proteomics analysis in disease studies.