Protein profile changes in the human breast cancer cell line MCF-7 in response toSEL1L gene induction

EpiHNet: Detecting epistasis by heterogeneous molecule network

Epistasis between single nucleotide polymorphisms (SNPs) plays an important role in elucidating the missing heritability of complex diseases. Diverse approaches have been invented for detecting SNP interactions, but they canonically neglect the important and useful connections between SNPs and other bio-molecules (i.e., miRNAs and lncRNAs). To comprehensively model these disease related molecules, a heterogeneous bio-molecular network based solution EpiHNet is introduced for high-order SNP interactions detection. EpiHNet firstly uses case/control data to construct an SNP statistical network, and meta-path based similarity on the heterogeneous network composed with SNPs, genes, lncRNAs, miRNAs and diseases to define another SNP relational network. The SNP relational network can explore and exploit different associations between molecules and diseases to complement the SNP statistical network and search the significantly associated SNPs. Next, EpiHNet integrates these two networks into a composite network, applies the modularity based clustering with fast search strategy to divide SNP nodes into different clusters. After that, it detects SNP interactions based on SNP combinations derived from each cluster. Synthetic experiments on diverse two-locus and three-locus disease models manifest that EpiHNet outperforms competitive baselines, even without the heterogeneous network. For real WTCCC breast cancer data, EpiHNet also demonstrates expressive results on detecting high-order SNP interactions.

Sensitive profiling of cell surface proteome by using an optimized biotinylation method

Cell surface proteins are responsible for many critical functions. Systematical profiling of these proteins would provide a unique molecular fingerprint to classify cells and provide important information to guide immunotherapy. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of cells. When this protocol was combined with a tip based fractionation scheme, 4510 proteins, including 2055 annotated cell surface-associated proteins, were identified with only 20 microgram protein digest, showing the superior sensitivity of the approach. To enable process 10 times fewer cells, a pipet tip based protocol was developed, which led to the identification of about 600 cell surface-associated proteins. Finally, the new protocol was applied to compare the cell surface proteomes of two breast cancer cell lines, BT474 and MCF7. It was found that many cell surface-associated proteins were differentially expressed. The new protocols were demonstrated to be easy to perform, time-saving, and yielding good selectivity and high sensitivity. We expect this protocol would have broad applications in the future. SIGNIFICANCE: Cell surface proteins confer specific cellular functions and are easily accessible. They are often used as drug targets and potential biomarkers for prognostic or diagnostic purposes. Thus, efficient methods for profiling cell surface proteins are highly demanded. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of starting cells. The new protocol is easier to perform, time-saving and has less protein loss. By using a special pipet tip, sensitive and in-depth cell surface proteome analysis could be achieved. In combination with label-free quantitative MS, the new protocol can be applied to the differential analysis of the cell surface proteomes between different cell lines to find genetically- or drug-induced changes. We expect this protocol would have broad application in cell surface protein studies, including the discovery of diagnostic marker proteins and potential therapeutic targets.

Protein Expression Analysis in Uterine Cervical Cancer for Potential Targets in Treatment

Specific markers in lesions of the human uterine cervix cancer (UCC) are still needed for prognostic, diagnostic and/or therapeutic purposes. In this study we evaluated key molecules at protein level between normal epithelium, cervical intraepithelial neoplasia (CIN1-3) and invasive cancer of a group of molecules previously reported at mRNA level. For that purpose, human formalin-fixed paraffin embedded tissue microarrays (TMAs) were constructed containing 205 Mexican tissue core specimens. Immunohistochemistry and quantitative analysis of histological staining was performed against twenty-two distinct proteins for each core and the processing platform ImageJ. In the progression of the disease we found key statistical differences for the proteins SEL1, Notch3 and SOCS3. High expressions of SEL1L, Notch3 and SOCS3 have potential value to increase the prognostic of UCC in combination with markers such as p16^INK4a. This study identified key drivers in cervical carcinogenesis that should be evaluated for the development of UCC therapies.

Methodology and Applications of Disease Biomarker Identification in Human Serum

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood.

An improved syngeneic orthotopic murine model of human breast cancer progression

Breast cancer drug development costs nearly $610 million and 37 months in preclinical mouse model trials with minimal success rates. Despite these inefficiencies, there are still no consensus breast cancer preclinical models. Murine mammary adenocarcinoma 4T1-luc2 cells were implanted subcutaneous (SQ) or orthotopically percutaneous (OP) injection in the area of the nipple, or surgically into the chest 2nd mammary fat pad under direct vision (ODV) in Balb/c immunocompetent mice. Tumor progression was followed by in vivo bioluminescence and direct measurements, pathology and survival determined, and tumor gene expression analyzed by genome-wide microarrays. ODV produced less variable-sized tumors and was a reliable method of implantation. ODV implantation into the chest 2nd mammary pad rather than into the abdominal 4th mammary pad, the most common implantation site, better mimicked human breast cancer progression pattern, which correlated with bioluminescent tumor burden and survival. Compared to SQ, ODV produced tumors that differentially expressed genes whose interaction networks are of importance in cancer research. qPCR validation of 10 specific target genes of interest in ongoing clinical trials demonstrated significant differences in expression. ODV implantation into the chest 2nd mammary pad provides the most reliable model that mimics human breast cancer compared from subcutaneous implantation that produces tumors with different genome expression profiles of clinical significance. Increased understanding of the limitations of the different preclinical models in use will help guide new investigations and may improve the efficiency of breast cancer drug development .

Proteomic analysis of breast cancer tissues to identify biomarker candidates by gel-assisted digestion and label-free quantification methods using LC-MS/MS

This study presents a proteomic method that differentiates between matched normal and breast tumor tissues from ductal carcinoma in situ (DCIS) and invasive carcinoma from Korean women, to identify biomarker candidates and to understand pathogenesis of breast cancer in protein level. Proteins from tissues obtained by biopsy were extracted by RIPA buffer, digested by the gel-assisted method, and analyzed by nano-UPLC-MS/MS. From proteomic analysis based on label-free quantitation strategy, a non-redundant list of 298 proteins was identified from the normal and tumor tissues, and 244 proteins were quantified using IDEAL-Q software. Hierarchical clustering analysis showed two patterns classified as two groups, invasive carcinoma and DCIS, suggesting a difference between two carcinoma at the protein expression level as expected. Differentially expressed proteins in tumor tissues compared to the corresponding normal tissues were related to three biological pathways: antigen-processing and presentation, glycolysis/gluconeogenesis, and complement and coagulation cascades. Among them, the up-regulation of calreticulin (CRT) and protein disulfide isomerase A3 (PDIA3) was confirmed by Western blot analysis. In conclusion, this study showed the possibility of identifying biomarker candidates for breast cancer using tissues and might help to understand the pathophysiology of this cancer at the protein level.

Mining protein lists from proteomics studies: applications for drug discovery

IMPORTANCE OF THE FIELD

In recent years, proteomics has become a common technique applied to a wide spectrum of scientific problems, including the identification of diagnostic biomarkers, monitoring the effects of drug treatments or identification of chemical properties of a protein or a drug. Although being significantly different in scientific essence, the ultimate result of the majority of proteomics studies is a protein list. Thousands of independent proteomics studies have reported protein lists in various functional contexts.

AREAS COVERED IN THIS REVIEW

We review here the spectrum of scientific problems where proteomics technology was applied recently to deliver protein lists. The available bioinformatics methods commonly used to understand the properties of the protein lists are compared.

WHAT THE READER WILL GAIN

The types and common functional properties of the reported protein lists are discussed. The range of scientific problems where this knowledge could be potentially helpful with a focus on drug discovery issues is explored.

TAKE HOME MESSAGE

Reported protein lists represent a valuable resource which can be used for a variety of goals, ranging from biomarkers discovery to identification of novel therapeutic implications of known drugs.

Protein disulfide isomerase in redox cell signaling and homeostasis

Thiol proteins may potentially act as redox signaling adaptor proteins, adjusting reactive oxygen species intermediates to specific signals and redox signals to cell homeostasis. In this review, we discuss redox effects of protein disulfide isomerase (PDI), a thioredoxin superfamily oxidoreductase from the endoplasmic reticulum (ER). Abundantly expressed PDI displays ubiquity, interactions with redox and nonredox proteins, versatile effects, and several posttranslational modifications. The PDI family contains >20 members with at least some apparent complementary actions. PDI has oxidoreductase, isomerase, and chaperone effects, the last not directly dependent on its thiols. PDI is a converging hub for pathways of disulfide bond introduction into ER-processed proteins, via hydrogen peroxide-generating mechanisms involving the oxidase Ero1α, as well as hydrogen peroxide-consuming reactions involving peroxiredoxin IV and the novel peroxidases Gpx7/8. PDI is a candidate pathway for coupling ER stress to oxidant generation. Emerging information suggests a convergence between PDI and Nox family NADPH oxidases. PDI silencing prevents Nox responses to angiotensin II and inhibits Akt phosphorylation in vascular cells and parasite phagocytosis in macrophages. PDI overexpression spontaneously enhances Nox activation and expression. In neutrophils, PDI redox-dependently associates with p47phox and supports the respiratory burst. At the cell surface, PDI exerts transnitrosation, thiol reductase, and apparent isomerase activities toward targets including adhesion and matrix proteins and proteases. Such effects mediate redox-dependent adhesion, coagulation/thrombosis, immune functions, and virus internalization. The route of PDI externalization remains elusive. Such multiple redox effects of PDI may contribute to its conspicuous expression and functional role in disease, rendering PDI family members putative redox cell signaling adaptors.

Comparison of functional proteomic analyses of human breast cancer cell lines T47D and MCF7

T47D and MCF7 are two human hormone-dependent breast cancer cell lines which are widely used as experimental models for in vitro and in vivo (tumor xenografts) breast cancer studies. Several proteins involved in cancer development were identified in these cell lines by proteomic analyses. Although these studies reported the proteomic profiles of each cell line, until now, their differential protein expression profiles have not been established. Here, we used two-dimensional gel and mass spectrometry analyses to compare the proteomic profiles of the two cell lines, T47D and MCF7. Our data revealed that more than 164 proteins are differentially expressed between them. According to their biological functions, the results showed that proteins involved in cell growth stimulation, anti-apoptosis mechanisms and cancerogenesis are more strongly expressed in T47D than in MCF7. These proteins include G1/S-specific cyclin-D3 and prohibitin. Proteins implicated in transcription repression and apoptosis regulation, including transcriptional repressor NF-X1, nitrilase homolog 2 and interleukin-10, are, on the contrary, more strongly expressed in MCF7 as compared to T47D. Five proteins that were previously described as breast cancer biomarkers, namely cathepsin D, cathepsin B, protein S100-A14, heat shock protein beta-1 (HSP27) and proliferating cell nuclear antigen (PCNA), are found to be differentially expressed in the two cell lines. A list of differentially expressed proteins between T47D and MCF7 was generated, providing useful information for further studies of breast cancer mechanisms with these cell lines as models.

mSEL-1L (Suppressor/enhancer Lin12-like) protein levels influence murine neural stem cell self-renewal and lineage commitment

Murine SEL-1L (mSEL-1L) is a key component of the endoplasmic reticulum-associated degradation pathway. It is essential during development as revealed by the multi-organ dysfunction and in uterus lethality occurring in homozygous mSEL-1L-deficient mice. Here we show that mSEL-1L is highly expressed in pluripotent embryonic stem cells and multipotent neural stem cells (NSCs) but silenced in all mature neural derivatives (i.e. astrocytes, oligodendrocytes, and neurons) by mmu-miR-183. NSCs derived from homozygous mSEL-1L-deficient embryos (mSEL-1L(-/-) NSCs) fail to proliferate in vitro, show a drastic reduction of the Notch effector HES-5, and reveal a significant down-modulation of the early neural progenitor markers PAX-6 and OLIG-2, when compared with the wild type (mSEL-1L(+/+) NSCs) counterpart. Furthermore, these cells are almost completely deprived of the neural marker Nestin, display a significant decrease of SOX-2 expression, and rapidly undergo premature astrocytic commitment and apoptosis. The data suggest severe self-renewal defects occurring in these cells probably mediated by misregulation of the Notch signaling. The results reported here denote mSEL-1L as a primitive marker with a possible involvement in the regulation of neural progenitor stemness maintenance and lineage determination.

KEGG spider: interpretation of genomics data in the context of the global gene metabolic network

KEGG spider is a web-based tool for interpretation of experimentally derived gene lists in order to gain understanding of metabolism variations at a genomic level. KEGG spider implements a 'pathway-free' framework that overcomes a major bottleneck of enrichment analyses: it provides global models uniting genes from different metabolic pathways. Analyzing a number of experimentally derived gene lists, we demonstrate that KEGG spider provides deeper insights into metabolism variations in comparison to existing methods.

The antibody MAB8051 directed against osteoprotegerin detects carbonic anhydrase II: implications for association studies with human cancers

A commonly used monoclonal antibody targeting osteoprotegerin (OPG), MAB8051, detects a truncated protein species in breast and prostate cancer cell lysates. OPG expression has been reported to contribute to cell survival of both of these cancers. We hypothesised that the truncated protein represented a unique tumour-associated OPG isoform. However, here we show that the truncated protein identified by MAB8051 in cancer cell lines is carbonic anhydrase II (CA II), also implicated in tumour biology. We clearly demonstrate cross-reactivity of this OPG antibody in western blots. OPG and CA II RNA-interference studies confirmed the identity of the bands. We show almost identical staining patterns between MAB8051 and CA II immunohistochemistry of different human tissue types and human tumour types using serial sections. We conclude that care should be exercised using this antibody for immunohistochemistry studies, without additional in situ hybridisation, or parallel use of other OPG-specific antibodies.

Proteomic analysis of human very low-density lipoprotein by two-dimensional gel electrophoresis and MALDI-TOF/TOF

Biochemical studies of lipoproteins have shed light on their composition, highly contributing to the comprehension of their function. Due to the complexity of their structure, however, an in-depth structural analysis, in terms of components and PTMs, may still unravel important players in physiological and pathological processes of lipid metabolism. In this study, we performed a protein map of very low-density lipoprotein (VLDL) using a 2-DE MALDI-TOF/TOF proteomic approach. Several VLDL-associated apolipoproteins were identified, including five isoforms of apoE, three isoforms of apoC-IV, and one isoform each of apoC-III, apoM, apoA-I, and apoA-IV. Notably, we also identified seven isoforms of apoL-I and two isoforms of prenylcysteine lyase as new VLDL-associated proteins. Furthermore, we were able to identify PTM of apoE, which was found to be differently O-glycosylated at Thr212 residue, and PTM of apoL-I which we described, for the first time, to be phosphorylated at Ser296. While the physiological relevance of our finding remains to be assessed, we believe that our results will be useful as reference for future studies of VLDL structure in specific physiopathological conditions.

Breast cancer proteomics: clinical perspectives

Breast cancer is the one of leading causes of cancer-related deaths in women within economically developed regions of the world. A major focus of present research into this malignancy is the identification of new biomarkers and drug targets to improve detection and treatment. Proteomics represents one of the latest technological developments in this context. It aims to analyse the complex circuitry of the breast cancer proteome. Here, the authors review how breast cancer proteomics has progressed so far, with emphasis on its potential application to clinically relevant scenarios.

Proteomic analysis of the airway surface liquid: modulation by proinflammatory cytokines

The airway surface is covered by a fluid, the airway surface liquid, interposed between the mucous layer and the epithelium. The airway surface liquid contains proteins, secreted by different cell types, that may have pro-/anti-inflammatory or bactericidal functions or have a role in the mucociliary clearance. We have used a proteomics approach to identify the proteins secreted by an isolated in vitro model of human airway epithelium, at resting and under proinflammatory conditions, as a strategy to define the factors involved in epithelial barrier function. To this aim, we have analyzed the airway surface liquid from human bronchial epithelial cells grown as polarized monolayers in the presence and absence of inflammatory stimuli such as IL-4, IL-1β, TNF-α, and IFN-γ. Two-dimensional electrophoresis followed by mass spectrometry analysis has allowed the identification of ∼175 secreted protein spots, among which are immune-related proteins, structural proteins, an actin severer, some protease inhibitors, and a metalloproteinase. Comparisons between treated and untreated conditions have shown that the expression of several proteins was significantly modified by the different cytokines. Our results indicate that the surface epithelium is an active player in the epithelial barrier function and that inflammatory conditions may modulate protein secretion.

Altered gene expression in mice selected for high maternal aggression

We previously applied selective breeding on outbred mice to increase maternal aggression (maternal defense). In this study, we compared gene expression within a continuous region of the central nervous system (CNS) involved in maternal aggression (hypothalamus and preoptic regions) between lactating selected (S) and nonselected control (C) mice (n= 6 per group). Using microarrays representing over 40,000 genes or expressed sequence tags, two statistical algorithms were used to identify significant differences in gene expression: robust multiarray and the probe logarithmic intensity error method. Approximately 200 genes were identified as significant using an intersection from both techniques. A subset of genes was examined for confirmation by real-time polymerase chain reaction (PCR). Significant decreases were found in S mice for neurotensin and neuropeptide Y receptor Y2 (both confirmed by PCR). Significant increases were found in S mice for neuronal nitric oxide synthase (confirmed by PCR), the K+ channel subunit, Kcna1 (confirmed by PCR), corticotrophin releasing factor binding protein (just above significance using PCR; P= 0.051) and GABA A receptor subunit 1A (not confirmed by PCR, but similar direction). S mice also exhibited significantly higher levels of the neurotransmitter receptor, adenosine A1 receptor and the transcription factors, c-Fos, and Egr-1. Interestingly, for 24 genes related to metabolism, all were significantly elevated in S mice, suggesting altered metabolism in these mice. Together, this study provides a list of candidate genes (some previously implicated in maternal aggression and some novel) that may play an important role in the production of this behavior.

SEL1L a multifaceted protein playing a role in tumor progression

Since the cloning in 1997 of SEL1L, the human ortholog of the sel-1 gene of C. elegans, most studies have focused on its role in cancer progression and have provided significant evidences to link its increased expression to a decrease in tumor aggressiveness. SEL1L resides on a "Genome Desert area" on chromosome 14q24.3-31 and is highly conserved in evolution. The function of the SEL1L encoded protein is still very elusive although, several evidences from lower organisms indicate that it plays a major role in protein degradation using the ubiquitin-proteosome system. SEL1L has a very complex structure made up of modules: genomically it consists of 21 exons featuring several alternative transcripts encoding for putative protein isoforms. This structural complexity ensures protein flexibility and specificity, indeed the protein was found in different sub-cellular compartments and may turn on a particular transcript in response to specific stimuli. The overall architecture of SEL1L guarantees an exquisite regulation in the expression of the gene.

Sel1-like repeat proteins in signal transduction

Solenoid proteins, which are distinguished from general globular proteins by their modular architectures, are frequently involved in signal transduction pathways. Proteins from the tetratricopeptide repeat (TPR) and Sel1-like repeat (SLR) families share similar alpha-helical conformations but different consensus sequence lengths and superhelical topologies. Both families are characterized by low sequence similarity levels, rendering the identification of functional homologous difficult. Therefore current knowledge of the molecular and cellular functions of the SLR proteins Sel1, Hrd3, Chs4, Nif1, PodJ, ExoR, AlgK, HcpA, Hsp12, EnhC, LpnE, MotX, and MerG has been reviewed. Although SLR proteins possess different cellular functions they all seem to serve as adaptor proteins for the assembly of macromolecular complexes. Sel1, Hrd3, Hsp12 and LpnE are activated under cellular stress. The eukaryotic Sel1 and Hrd3 proteins are involved in the ER-associated protein degradation, whereas the bacterial LpnE, EnhC, HcpA, ExoR, and AlgK proteins mediate the interactions between bacterial and eukaryotic host cells. LpnE and EnhC are responsible for the entry of L. pneumophila into epithelial cells and macrophages. ExoR from the symbiotic microorganism S. melioti and AlgK from the pathogen P. aeruginosa regulate exopolysaccaride synthesis. Nif1 and Chs4 from yeast are responsible for the regulation of mitosis and septum formation during cell division, respectively, and PodJ guides the cellular differentiation during the cell cycle of the bacterium C. crescentus. Taken together the SLR motif establishes a link between signal transduction pathways from eukaryotes and bacteria. The SLR motif is so far absent from archaea. Therefore the SLR could have developed in the last common ancestor between eukaryotes and bacteria.

SEL1L affects human pancreatic cancer cell cycle and invasiveness through modulation of PTEN and genes related to cell-matrix interactions

Previously, it was reported that SEL1L is able to decrease the aggressive behavior of human pancreatic tumor cells both in vitro and in vivo. To gain insights into the involvement of SEL1L in tumor invasion, we performed gene expression analysis on the pancreatic cancer cell line Suit-2 subjected to two complementary strategies: upregulation and downregulation of SEL1L expression by stable transfection of the entire cDNA under an inducible promoter and by RNA-mediated interference. SuperArray and real-time analysis revealed that SEL1L modulates the expression of the matrix metalloproteinase inhibitors TIMP1 (P < .04-.03) and TIMP2 (P < .03-.05), and the PTEN gene (P < .03-.05). Gene expression modulations correlate with the decrease in invasive ability (P < .05) and in accumulation of SEL1L-expressing cells in G1. Taken together, our data indicate that SEL1L alters the expression of mediators involved in the remodeling of the extracellular matrix by creating a microenvironment that is unfavorable to invasive growth and by affecting cell cycle progression through promotion of G1 accumulation.

Proteome profile of the MCF7 cancer cell line: a mass spectrometric evaluation

The development of novel proteomic technologies that will enable the discovery of disease specific biomarkers is essential in the clinical setting to facilitate early diagnosis and increase survivability rates. We are reporting a shotgun two-dimensional (2D) strong cationic exchange/reversed-phase liquid chromatography/electrospray ionization tandem mass spectrometry (SCX/RPLC/ESI-MS/MS) protocol for the analysis of proteomic constituents in cancerous cells. The MCF7 breast cancer cell line was chosen as a model system. A series of optimization steps were performed to improve the LC/MS experimental setup, sample preparation, data acquisition and database search protocols, and a data filtering strategy was developed to enable confident identification of a large number of proteins and potential biomarkers. This research has resulted in the identification of >2000 proteins using multiple filtering and p-value sorting. Approximately 1600-1900 proteins had p < 0.001, and, of these, approximately 60% were matched by >or=2 unique peptides. Alternatively, >99% of the proteins identified by >or=2 unique peptides had p < 0.001. When searching the data against a reversed database of proteins, the rate of false positive identifications was 0.1% at the peptide level and 0.4% at the protein level. The typical reproducibility in detecting overlapping proteins across replicate runs exceeded 90% for proteins matched by >or=2 unique peptides. According to their biological function, approximately 200 proteins were involved in cancer-relevant cellular processes, and over 25 proteins were previously described in the literature as putative cancer biomarkers, as they were found to be differentially expressed between normal and cancerous cell states. Among these, biomarkers such PCNA, cathepsin D, E-cadherin, 14-3-3-sigma, antigen Ki-67, TP53RK, and calreticulin were identified. These data were generated by subjecting to MS analysis approximately 42 microg of sample, analyzing 16 SCX peptide fractions, and interpreting approximately 55,000 MS2 spectra. Total MS time required for analysis was 40 h.