Integrated genomic/proteomic analysis

Identifying kinase targets of PPARγ in human breast cancer

Breast cancer is the most common cancer in women. Despite advances in screening women for genetic predisposition to breast cancer and risk stratification, a majority of women carriers remain undetected until they become affected. Thus, there is a need to develop a cost-effective, rapid, sensitive and non-invasive early-stage diagnostic method. Kinases are involved in all fundamental cellular processes and mutations in kinases have been reported as drivers of cancer. PPARγ is a ligand-activated transcription factor that plays important roles in cell proliferation and metabolism. However, the complete set of kinases modulated by PPARγ is still unknown. In this study, we identified human kinases that are potential PPARγ targets and evaluated their differential expression and gene pair correlations in human breast cancer patient dataset TCGA-BRCA. We further confirmed the findings in human breast cancer cell lines MCF7 and SK-BR-3 using a kinome array. We observed that gene pair correlations are lost in tumours as compared to healthy controls and could be used as a supplement strategy for diagnosis and prognosis of breast cancer.

Using aptamers for cancer biomarker discovery

Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment) SELEX and cell-based SELEX (cell-SELEX). Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics.

Dielectric cell separation of fine needle aspirates from tumor xenografts

As an approach to isolating tumor cells from fine needle biopsy specimens, we investigated a dielectric cell preparation method using an in vivo xenographic tumor model. Cultured human MDA-MB-435 tumor cells were grown as solid tumors in nude mice and fine needle aspiration biopsies were conducted. Biopsied cells were suspended in sucrose medium and collected on slides patterned with microelectrode arrays (electrosmears) energized by electrical signals in the range 10 to 960 kHz. The unlabeled cells adhered to characteristic regions of the slides in accordance with their morphology as a result of dielectric forces. Tumor cells were trapped between 40 and 60 kHz and were separated according to whether they were mitotic, large and complex, or small. Damaged tumor cells were captured at between 60 and 120 kHz; granulocytes between 70 and 90 kHz; lymphocytes between 85 and 105 kHz; healthy erythrocytes between 140 and 180 kHz, and damaged erythrocytes above 180 kHz. Using intrinsic cell characteristics, the electrosmear presented cell subpopulations from fine needle aspiration biopsy specimens in a manner that is compatible with automated slide-based analysis systems. The approach has the potential to facilitate the analysis of the role of cell subpopulations in disease.

Protein expression in the striatum and cortex regions of the brain for a mouse model of Huntington's disease

Liquid chromatography (LC) coupled with mass spectrometry (MS) and database assignment methods have been used to conduct a large-scale proteome survey of the R6/2 mouse model of Huntington's disease (HD). Although the neuropathological mechanisms of HD are not known, the mutant huntingtin gene that causes the disease is thought to alter gene transcription, leading to a cascade of neurotoxic events. In this report, we have focused on characterizing changes in the brain proteome associated with HD pathophysiology. Differences in the relative abundances of proteins (R6/2 compared to wild type) in brain tissue from the striatum and cortex, two primary loci of dysfunction in HD, were assessed by using a label-free approach based on calibrations to internal standards. In total, assignments were made for approximately 400 proteins. A set of criteria was used to establish 160 high confidence assignments, approximately 30% of which appear to show differences in expression relative to wild type (WT) animals. Many of the proteins that were differentially expressed are known to be associated with neurotransmission and likely play key roles in HD etiology. This study is the first to report that the majority of differentially expressed proteins in the striatum are up-regulated, while the majority of the expressed proteins in the cortex are down-regulated. The differentially expressed proteins identified in this proteomic screen may be potential biomarkers and drug targets for HD and may further our understanding of the disease pathology.

Mapping the human plasma proteome by SCX-LC-IMS-MS

The advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhance the accuracy and coverage of proteome maps of such fluids. Here, we describe the combination of strong-cation-exchange and reversed-phase liquid chromatographies with ion mobility and mass spectrometry as a means of characterizing the complex mixture of proteins associated with the human plasma proteome. The increase in separation capacity associated with inclusion of the ion mobility separation leads to generation of one of the most extensive proteome maps to date. The map is generated by analyzing plasma samples of five healthy humans; we report a preliminary identification of 9087 proteins from 37,842 unique peptide assignments. An analysis of expected false-positive rates leads to a high-confidence identification of 2928 proteins. The results are catalogued in a fashion that includes positions and intensities of assigned features observed in the datasets as well as pertinent identification information such as protein accession number, mass, and homology score/confidence indicators. Comparisons of the assigned features reported here with other datasets shows substantial agreement with respect to the first several hundred entries; there is far less agreement associated with detection of lower abundance components.

A Brief Update of Glucocorticoid Receptor Variants and Obesity Risk

Excess body fat, obesity, is one of the most common disorders in clinical practice. Obese individuals are at increased risk for physical ailments, such as type 2 diabetes, coronary heart disease, hypertension, and several types of cancer. The location of the body fat is a major determinant of the degree of excess morbidity and mortality due to obesity. More specifically, the amount of subcutaneous truncal or abdominal fat, and the amount of visceral fat located in the abdominal cavity independently predicts obesity-related adverse health outcomes. The obesity gene map shows putative loci on all chromosomes except Y. More than 300 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. These genes can be divided into two broad categories: (a) rare gene variants that have a strong influence, and (b) common gene variants that have a weaker influence on obesity phenotypes. Studies in humans have suggested a positive association between obesity, hypertension, and insulin resistance, with alleles at the glucocorticoid receptor gene. In this article, we will estimate the risk by which such gene polymorphism mediates a role in obesity.

Proteomic research in renal transplantation

Expression proteomics is a valuable tool for biomarker discovery. Currently there is a great deal of interest in the development of urine biomarkers for detection of renal allograft rejection as an alternative to percutaneous needle biopsy, which is the "gold standard." Needle biopsy is costly and associated with significant patient morbidity and mortality. This review will discuss the author's current work in proteomics-based urine biomarker discovery, as well as alternative approaches used by other groups that use SELDI mass spectrometry. The current state of urine transplant biomarkers will be discussed, and in conclusion there will be a brief discussion of how urine biomarkers will be used for transplant patient management once they are validated and analyte-specific assays are developed.

Proteome analysis of the causative agent of Chagas disease: Trypanosoma cruzi

Trypanosoma cruzi, the causative agent of Chagas disease, has evolved particular mechanisms of gene regulation. Gene expression is regulated firstly at post-transcriptional level. This feature makes proteomic methods a promising tool for studying adaptative changes in these parasites. In this work we generated a reproducible method for protein analysis by two-dimensional electrophoresis coupled to mass spectrometry, and a protein map for T. cruzi. Western-blot analysis supported the identity of some of the proteins. This work points to proteomic approach as a powerful tool to study differential expression, stress response or drug resistance in T. cruzi.

Fully automated online multi-dimensional protein profiling system for complex mixtures

For high throughput proteome analysis of highly complex protein mixtures, we have constructed a fully automated online system for multi-dimensional protein profiling, which utilizes a combination of two-dimensional liquid chromatography and tandem mass spectrometry (2D-LC-MS-MS), based on our well-established offline system described previously [K. Fujii, T. Nakano, T. Kawamura, F. Usui, Y. Bando, R. Wang, T. Nishimura, J. Proteome Res. 3 (2004) 712]. A two-valve switching system on a programmable auto sample injector is utilized for online two-dimensional chromatography with strong cation-exchange (SCX) and reversed-phase (RP) separations. The SCX separation is carried out during the equilibration of RP chromatography and the entire sequence of analysis was performed under fully automated conditions within 4 h, based on six SCX fractionations, and 40 min running time for the two-dimensional RP chromatography. In order to evaluate its performance in the detection and identification of proteins, digests of six standard proteins and yeast 20S proteasome have been analyzed and their results were compared to those obtained by the one-dimensional reversed-phase chromatography system (ID-LC-MS-MS). The 2D-LC-MS-MS system demonstrated that both the number of peptide fragments detected and the protein coverage had more than doubled. Furthermore, this multi-dimensional protein profiling system was also applied to the human 26S proteasome, which is one of the highly complex protein mixtures. Consequently, 723 peptide fragments were identified as 31 proteasome components, together with other coexisting proteins in the sample. The identification could be comprehensively performed with a 63% sequence coverage on an average, and additionally, with modifications at the N-terminus. These results indicated that the online 2D-LC-MS-MS system being described here is capable of analyzing highly complex protein mixtures in a high throughput manner, and that it would be applicable to dynamic proteomics.

The Application of Clinical Proteomics to Cancer and other Diseases

The term "clinical proteomics" refers to the application of available proteomics technologies to current areas of clinical investigation. The ability to simultaneously and comprehensively examine changes in large numbers of proteins in the context of disease or other changes in physiological conditions holds great promise as a tool to unlock the solutions to difficult clinical research questions. Proteomics is a rapidly growing field that combines high throughput analytical methodologies such as two-dimensional gel electrophoresis and SELDI mass spectrometry methods with complex bioinformatics to study systems biology--the system of interest is defined by the investigator. Even with all its potential, however, studies must be carefully designed in order to differentiate true clinical differences in protein expression from differences originating from variation in sample collection, variation in experimental condition, and normal biological variability. Proteomic analyses are already widely in use for clinical studies ranging from cancer to other diseases such as cardiovascular disease, organ transplant, and pharmacodynamic studies.

Proteomics of light-harvesting proteins in different plant species. Analysis and comparison by liquid chromatography-electrospray ionization mass spectrometry. Photosystem I

The light-harvesting proteins (Lhca) of photosystem I (PSI) from four monocot and five dicot species were extracted from plant material, separated by reversed-phase high-performance liquid chromatography (HPLC) and subsequently identified on the basis of their intact molecular masses upon on-line hyphenation with electrospray ionization mass spectrometry. Although their migration behavior in gel electrophoresis was very similar, the elution times among the four antenna types in reversed-phase-HPLC differed significantly, even more than those observed for the light-harvesting proteins of photosystem II. Identification of proteins is based on the good agreement between the measured intact molecular masses and the values calculated on the basis of their nucleotide-derived amino acid sequences, which makes the intact molecular masses applicable as intact mass tags. These values match excellently for Arabidopsis, most probably because of the availability of high-quality DNA sequence data. In all species examined, the four antennae eluted in the same order, namely Lhca1 > Lhca3 > Lhca4 > Lhca2. These characteristic patterns enabled an unequivocal assignment of the proteins in preparations from different species. Interestingly, in all species examined, Lhca1 and Lhca2 were present in two or three isoforms. A fifth antenna protein, corresponding to the Lhca6 gene, was found in tomato (Lycopersicon esculentum). However PSI showed a lower heterogeneity than photosystem II. In most plant species, Lhca2 and Lhca4 proteins are the most abundant PSI antenna proteins. The HPLC method used in this study was found to be highly reproducible, and the chromatograms may serve as a highly confident fingerprint for comparison within a single and among different species for future studies of the PSI antenna.

Clinical proteomics for cancer biomarker discovery and therapeutic targeting

As we emerge into the post-genome era, proteomics finds itself as the driving force field as we translate the nucleic acid information archive into understanding how the cell actually works and how disease processes operate. Even so, the traditionally held view of proteomics as simply cataloging and developing lists of the cellular protein repertoire of a cell are now changing, especially in the sub-discipline of clinical proteomics. The most relevant information archive to clinical applications and drug development involves the elucidation of the information flow of the cell; the "software" of protein pathway networks and circuitry. The deranged circuitry of the cell as the drug target itself as well as the effect of the drug on not just the target, but also the entire network, is what we now are striving towards. Clinical proteomics, as a new and most exciting sub-discipline of proteomics, involves the bench-to-bedside clinical application of proteomic tools. Unlike the genome, there are potentially thousands of proteomes: each cell type has its own unique proteome. Moreover, each cell type can alter its proteome depending on the unique tissue microenvironment in which it resides, giving rise to multiple permutations of a single proteome. Since there is no polymerase chain reaction equivalent to proteomics- identifying and discovering the "wiring diagram" of a human diseased cell in a biopsy specimen remains a daunting challenge. New micro-proteomic technologies are being and still need to be developed to drill down into the proteomes of clinically relevant material. Cancer, as a model disease, provides a fertile environment to study the application of proteomics at the bedside. The promise of clinical proteomics and the new technologies that are developed is that we will detect cancer earlier through discovery of biomarkers, we will discover the next generation of targets and imaging biomarkers, and we can then apply this knowledge to patient-tailored therapy.

Isoforms of photosystem II antenna proteins in different plant species revealed by liquid chromatography-electrospray ionization mass spectrometry

The high selectivity offered by reversed-phase high-performance liquid chromatography on-line coupled to electrospray ionization mass spectrometry has been utilized to characterize the major and minor light-harvesting proteins of photosystem II (Lhcb). Isomeric forms of the proteins, revealed either on the basis of different hydrophobicity enabling their chromatographic separation or on the basis of different molecular masses identified within one single chromatographic peak, were readily identified in a number of monocot and dicot species. The presence of several Lhcb1 isoforms (preferably in dicots) can explain the tendency of dicot Lhcb1 to form trimeric aggregates. The Lhcb1 molecular masses ranged from 24,680 to 25,014 among different species, whereas within the same species, the isoforms differed by 14-280 mass units. All Lhcb1 proteins appear to be highly conserved among different species such that they belong to a single gene group that has several different gene family members. In all species examined, the number of isoforms corresponded more or less to the genes cloned previously. Two isoforms of Lhcb3 were found in petunia and tomato. For Lhcb6, the most divergent of all light-harvesting proteins, the greatest number of isoforms was found in petunia, tobacco, tomato, and rice. Lhcb2, Lhcb4, and Lhcb5 were present in only one form. The isoforms are assumed to play an important role in the adaptation of plants to environmental changes.

Molecular profiling of human cancer

Traditionally, tumours have been categorized on the basis of histology. However, the staining pattern of cancer cells viewed under the microscope is insufficient to reflect the complicated underlying molecular events that drive the neoplastic process. By surveying thousands of genes at once, using DNA arrays, it is now possible to read the molecular signature of an individual patient's tumour. When the signature is analysed with clustering algorithms, new classes of cancer emerge that transcend distinctions based on histological appearance alone. Using DNA arrays, protein arrays and appropriate experimental models, the ultimate goal is to move beyond correlation and classification to achieve new insights into disease mechanisms and treatment targets.

In-situ sampling and separation of RNA from individual mammalian cells

In this investigation RNA was directly sampled and separated at the single-cell level (without extraction) by capillary electrophoresis (CE). Laser-induced fluorescence (LIF) was employed to detect ethidium bromide-labeled RNA molecules under native conditions. Hydroxypropylmethylcellulose was used as a matrix for molecular sieving. Additives to the polymer solution included poly(vinylpyrrolidone) to eliminate the electroosmotic flow and mannitol to enhance the separation. Peak identities were confirmed as RNA by enzymatic treatment with RNase I. The individual Chinese Hamster Ovary (CHO-K1) cells were injected into a capillary and the cells were lysed online with sodium dodecyl sulfate (SDS) solutions before running electrophoresis. Low molecular mass (LMM) RNAs as well as larger fragments (tentatively identified as 18S and 28S ribosomal RNA by comparison with the literature) were detected with this system, which corresponds to a detected amount of approximately equals 10-20 pg of RNA/cell. A Proteinase K study showed that proteins incorporated with RNA molecules were eliminated by SDS treatment and thus did not influence the migration of RNA. Experiments were also performed with this technique to detect nucleic acid damage. Changes in the peak pattern were detected in the cells treated with hydrogen peroxide, which meant that strand breaks occurred in DNA and RNA. It was found that 60 mM caused the most severe damage to the nucleic acids.