Proteomic screening and identification of microRNA‐128 targets in glioma cells

Brain‐enriched miR‐128 is repressed in glioma cells, and could inhibit the proliferation of gliomas by targeting genes such as E2F3a and BMI1. To identify more targets of miR‐128 in glioblastoma multiforme, the pulse stable isotope labeling with amino acids in cell culture (pSILAC) technique was used to test its impact on whole protein synthesis in T98G glioma cells. We successfully identified 1897 proteins, of which 1459 proteins were quantified. Among them, 133 proteins were downregulated after the overexpression of miR‐128. Through predictions using various bioinformatics tools, 13 candidate target genes were chosen. A luciferase assay validated that 11 of 13 selected genes were potential targets of miR‐128, and a mutagenesis experiment confirmed CBFB, CORO1C, GLTP, HnRNPF, and TROVE2 as the target genes. Moreover, we observed that the expression of CORO1C, TROVE2, and HnRNPF were higher in glioma cell lines compared to normal brain tissues and presented a tendency toward downregulation after overexpression of miR‐128 in T98G cells. Furthermore, we have validated that CORO1C, TROVE2, and HnRNPF could inhibit glioma cell proliferation. In sum, our data showed that the integration of pSILAC and bioinformatics analysis was an efficient method for seeking the targets of miRNAs, and plentiful targets of miR‐128 were screened and laid the foundation for research into the miR‐128 regulation network.     

A quantitative proteomics analysis of MCF7 breast cancer stem and progenitor cell populations

Accumulating evidence has demonstrated that breast cancers are initiated and develop from a small population of stem‐like cells termed cancer stem cells (CSCs). These cells are hypothesized to mediate tumor metastasis and contribute to therapeutic resistance. However, the molecular regulatory networks responsible for maintaining CSCs in an undifferentiated state have yet to be elucidated. In this study, we used CSC markers to isolate pure breast CSCs fractions (ALDH+ and CD44+CD24‐ cell populations) and the mature luminal cells (CD49f‐EpCAM+) from the MCF7 cell line. Proteomic analysis was performed on these samples and a total of 3304 proteins were identified. A label‐free quantitative method was applied to analyze differentially expressed proteins. Using the criteria of greater than twofold changes and p value <0.05, 305, 322 and 98 proteins were identified as significantly different in three pairwise comparisons of ALDH+ versus CD44+CD24‐, ALDH+ versus CD49f‐EpCAM+ and CD44+CD24‐ versus CD49f‐EpCAM+, respectively. Pathway analysis of differentially expressed proteins by Ingenuity Pathway Analysis (IPA) revealed potential molecular regulatory networks that may regulate CSCs. Selected differential proteins were validated by Western blot assay and immunohistochemical staining. The use of proteomics analysis may increase our understanding of the underlying molecular mechanisms of breast CSCs. This may be of importance in the future development of anti‐CSC therapeutics.     

Quantitative proteomics of fractionated membrane and lumen exosome proteins from isogenic metastatic and nonmetastatic bladder cancer cells reveal differential expression of EMT factors

Cancer cells secrete soluble factors and various extracellular vesicles, including exosomes, into their tissue microenvironment. The secretion of exosomes is speculated to facilitate local invasion and metastatic spread. Here, we used an in vivo metastasis model of human bladder carcinoma cell line T24 without metastatic capacity and its two isogenic derivate cell lines SLT4 and FL3, which form metastases in the lungs and liver of mice, respectively. Cultivation in CLAD1000 bioreactors rather than conventional culture flasks resulted in a 13‐ to 16‐fold increased exosome yield and facilitated quantitative proteomics of fractionated exosomes. Exosomes from T24, SLT4, and FL3 cells were partitioned into membrane and luminal fractions and changes in protein abundance related to the gain of metastatic capacity were identified by quantitative iTRAQ proteomics. We identified several proteins linked to epithelial–mesenchymal transition, including increased abundance of vimentin and hepatoma‐derived growth factor in the membrane, and casein kinase II α and annexin A2 in the lumen of exosomes, respectively, from metastatic cells. The change in exosome protein abundance correlated little, although significant for FL3 versus T24, with changes in cellular mRNA expression. Our proteomic approach may help identification of proteins in the membrane and lumen of exosomes potentially involved in the metastatic process.     

Incorporating high-throughput proteomics experiments into structural biology pipelines: identification of the low-hanging fruits

The last years have seen the emergence of many large-scale proteomics initiatives that have identified thousands of new protein interactions and macromolecular assemblies. However, unfortunately, only a few among the discovered complexes meet the high-quality standards required to be promptly used in structural studies. This has thus created an increasing gap between the number of known protein interactions and complexes and those for which a high-resolution 3-D structure is available. Here, we present and validate a computational strategy to distinguish those complexes found in high-throughput affinity purification experiments that will stand the best chances to successfully express, purify and crystallize with little further intervention. Our method suggests that there are some 50 complexes recently discovered in yeast that could readily enter the structural biology pipelines.     

Identification of estrogen-responsive proteins in MCF-7 human breast cancer cells using label-free quantitative proteomics

17beta-Estradiol (E(2)) is a key regulatory steroid hormone that is involved in the control of a number of developmental and other functions. The aim of the present work was to identify estrogen-dependent proteomic changes by determining the levels of expressed proteins in MCF-7 human breast cancer cells following treatment with E(2). A number of methods exist for differential analysis of complex proteomic mixtures. Here, a label-free mass spectrometric approach comparing the ion intensities of tryptic peptides was adopted, which was combined with prefractionation of whole cell lysate proteins by 1-D SDS-PAGE. Using this approach, 60 proteins were found to be affected by E(2). These comprised 55 up-regulated and five down-regulated proteins. These proteins varied widely in their physiochemical properties with pIs of 4-12 and molecular weights of 9-500 kDa. Pathway analysis revealed that the majority of changes were related and together describe an up-regulated pathway consistent with the events of cell proliferation. The quantitative approach used here is relatively straightforward, avoids the use of costly labelling reagents, was reproducible within acceptable limits and has a linear response over a useful concentration range.     

Subcellular proteomics revealed the epithelial-mesenchymal transition phenotype in lung cancer

Subcellular proteomics was used to compare the protein profiles between human lung adenocarcinoma A549 cells and human bronchial epithelial (HBE) cells. In total, 106 differential proteins were identified and the altered expression levels of partial identified proteins were confirmed by Western blot analysis. Importantly, pathway analysis and biological validation revealed epithelial-mesenchymal transition (EMT) phenotype shift in A549 cells as compared with HBE cells. The EMT phenotype of A549 cells can be increased by self-producing TGF-β1 and significantly decreased by silencing heterogeneous nuclear ribonucleoprotein (hnRNPK) expression. As EMT has been considered as an important event during malignant tumor progression and metastasis, investigating EMT and deciphering the related pathways may lead to more efficient strategies to fight lung cancer progression. By integrating the subcellular proteomic data with EMT-related functional studies, we revealed new insights into the EMT progress of lung carcinogenesis, providing clues for further investigations on the discovery of potential therapeutic targets.     

Investigation of ovarian cancer associated sialylation changes in N-linked glycopeptides by quantitative proteomics

ABSTRACT: BACKGROUND: In approximately 80% of patients, ovarian cancer is diagnosed when the patient is already in the advanced stages of the disease. CA125 is currently used as the marker for ovarian cancer; however, it lacks specificity and sensitivity for detecting early stage disease. There is a critical unmet need for sensitive and specific routine screening tests for early diagnosis that can reduce ovarian cancer lethality by reliably detecting the disease at its earliest and treatable stages. Results: In this study, we investigated the N-linked sialylated glycopeptides in serum samples from healthy and ovarian cancer patients using Lectin-directed Tandem Labeling (LTL) and iTRAQ quantitative proteomics methods. We identified 45 N-linked sialylated glycopeptides containing 46 glycosylation sites. Among those, ten sialylated glycopeptides were significantly up-regulated in ovarian cancer patients' serum samples. LC-MS/MS analysis of the non-glycosylated peptides from the same samples, western blot data using lectin enriched glycoproteins of various ovarian cancer type samples, and PNGase F (+/-) treatment confirmed the sialylation changes in the ovarian cancer samples. Conclusion: Herein, we demonstrated that several proteins are aberrantly sialylated in N-linked glycopeptides in ovarian cancer and detection of glycopeptides with abnormal sialylation changes may have the potential to serve as biomarkers for ovarian cancer.     

Identification of annexin II as a novel secretory biomarker for breast cancer

Early prediction of metastatic breast cancer is important for improvement of prognosis and survival rate. The present study aimed to identify secreted protein biomarkers for detection of invasive breast cancer. To this end, we performed a comparative proteomic analysis by a combination of 2DE and MALDI‐TOF MS analysis of conditioned media from invasive H‐Ras MCF10A human breast epithelial cells and noninvasive MCF10A and N‐Ras MCF10A cells. We identified a list of 25 proteins that were strongly detected in media of H‐Ras MCF10A and focused on annexin II, which was shown to be involved in cell motility. Invasive triple‐negative human breast carcinoma cells, Hs578T, and MDA‐MB‐231, showed increased levels of annexin II in media, demonstrating that secretion of annexin II correlated well with the invasive phenotype of cells. We demonstrated a crucial role of annexin II in breast cell invasion/migration and actin cytoskeleton reorganization required for filopodia formation. Annexin II levels in the plasma samples and breast cancer tissues of breast cancer patients were significantly higher than those of normal groups, providing a clinical relevance to our in vitro findings. Taken together, we identified annexin II as a novel secretory biomarker candidate for invasive breast cancer, especially estrogen receptor‐negative breast cancer.     

Functional genomics and proteomics approaches to study the ERBB network in cancer

Substantial progress in functional genomic and proteomic technologies has opened new perspectives in biomedical research. The sequence of the human genome has been mostly determined and opened new visions on its complexity and regulation. New technologies, like RNAi and protein arrays, allow gathering knowledge beyond single gene analysis. Increasingly, biological processes are studied with systems biological approaches, where qualitative and quantitative data of the components are utilized to model the respective processes, to predict effects of perturbations, and to then refine these models after experimental testing. Here, we describe the potential of applying functional genomics and proteomics, taking the ERBB family of growth-factor receptors as an example to study the signaling network and its impact on cancer.     

QIKS – Quantitative identification of kinase substrates

Signaling networks regulate cellular responses to external stimuli through post‐translational modifications such as protein phosphorylation. Phosphoproteomics facilitate the large‐scale identification of kinase substrates. Yet, the characterization of critical connections within these networks and the identification of respective kinases remain the major analytical challenge. To address this problem, we present a novel approach for the identification of direct kinase substrates using chemical genetics in combination with quantitative phosphoproteomics. Quantitative identification of kinase substrates (QIKS) is a novel‐screening platform developed for the proteome‐wide substrate‐analysis of specific kinases. Here, we aimed to identify substrates of mitogen‐activated protein kinase/Erk kinase (Mek1), an essential kinase in the mitogen‐activated protein kinase cascade. An ATP analog‐sensitive mutant of Mek1 (Mek1‐as) was incubated with a cell extract from Mek1 deficient cells. Phosphorylated proteins were analyzed by LC‐MS/MS of IMAC‐enriched phosphopeptides, labeled differentially for relative quantification. The identification of extracellular regulated kinase 1/2 as the sole cytoplasmic substrates of MEK1 validates the applicability of this approach and suggests that QIKS could be used to identify substrates of a wide variety of kinases.     

Life‐style changes of a halophilic archaeon analyzed by quantitative proteomics

Quantitative proteomics based on isotopic labeling has become the method of choice to accurately determine changes in protein abundance in highly complex mixtures. Isotope‐coded protein labeling (ICPL), which is based on the nicotinoylation of proteins at lysine residues and free N‐termini was used as a simple, reliable and fast method for the comparative analysis of three different cellular states of the halophilic archaeon Halobacterium salinarum through pairwise comparison. The labeled proteins were subjected to SDS‐PAGE, in‐gel digested and the proteolytic peptides were separated by LC and analyzed by MALDI‐TOF/TOF MS. Automated quantitation was performed by comparing the MS peptide signals of ¹²C and ¹³C nicotinoylated isotopic peptide pairs. The transitions between (i) aerobic growth in complex versus synthetic medium and (ii) aerobic versus anaerobic/phototrophic growth, both in complex medium, provide a wide span in nutrient and energy supply for the cell and thus allowed optimal studies of proteome changes. In these two studies, 559 and 643 proteins, respectively, could be quantified allowing a detailed analysis of the adaptation of H. salinarum to changes of its living conditions. The subtle cellular response to a wide variation of nutrient and energy supply demonstrates a fine tuning of the cellular protein inventory.     

Profiling of the human monocytic cell secretome by quantitative label-free mass spectrometry identifies stimulus-specific cytokines and proinflammatory proteins

The immune response to pathogens or injury relies on the concerted release of cytokines and proteins with biological activity important for host protection, host defense, and wound healing. Consequently, the secretome of immune cells provides a promising resource for discovery of specific molecular markers and targets for pharmacological intervention. Here, we employ label-free MS for unbiased, quantitative profiling of the human monocytic cell secretome under different proinflammatory stimuli. The quantitative secretome profiles reveal the highly stimulus-dependent cellular response and differential, specific secretion of more than 200 proteins, including important proinflammatory proteins and cytokines.     

Coupling proteomics and transcriptomics in the quest of subtype‐specific proteins in breast cancer

Breast‐cancer subtypes present with distinct clinical characteristics. Therefore, characterization of subtype‐specific proteins may augment the development of targeted therapies and prognostic biomarkers. To address this issue, MS‐based secretome analysis of eight breast cancer cell lines, corresponding to the three main breast cancer subtypes was performed. More than 5200 non‐redundant proteins were identified with 23, four, and four proteins identified uniquely in basal, HER2‐neu‐amplified, and luminal breast cancer cells, respectively. An in silico mRNA analysis using publicly available breast cancer tissue microarray data was carried out as a preliminary verification step. In particular, the expression profiles of 15 out of 28 proteins included in the microarray (from a total of 31 in our subtype‐specific signature) showed significant correlation with estrogen receptor (ER) expression. A MS‐based analysis of breast cancer tissues was undertaken to verify the results at the proteome level. Eighteen out of 31 proteins were quantified in the proteomes of ER‐positive and ER‐negative breast cancer tissues. Survival analysis using microarray data was performed to examine the prognostic potential of these selected candidates. Three proteins correlated with ER status at both mRNA and protein levels: ABAT, PDZK1, and PTX3, with the former showing significant prognostic potential.     

Honokiol inhibits HepG2 migration via down‐regulation of IQGAP1 expression discovered by a quantitative pharmaceutical proteomic analysis

Honokiol (HNK), a natural small molecular product, inhibited proliferation of HepG2 cells and exhibited anti‐tumor activity in nude mice. In this article, we applied a novel sensitive stable isotope labeling with amino acids in cell culture‐based quantitative proteomic method and a model of nude mice to investigate the correlation between HNK and the hotspot migration molecule Ras GTPase‐activating‐like protein (IQGAP1). The quantitative proteomic analysis showed that IQGAP1 was 0.53‐fold down‐regulated under 10 μg/mL HNK exposure for 24 h on HepG2 cells. Migration ability of HepG2 cells under HNK treatment was correlated with its expression level of IQGAP1. In addition, the biochemical validation on HepG2 cells and the tumor xenograft model further demonstrated that HNK decreased the expression level of IQGAP1 and its upstream proteins Cdc42/Rac1. These data supported that HNK can modulate cell adhesion and cell migration by acting on Cdc42/Rac1 signaling via IQGAP1 interactions with its upstream Cdc42/Rac1 proteins, which is a new molecular mechanism of HNK to exert its anti‐tumor activity.     

Subcellular proteomics of cell differentiation: quantitative analysis of the plasma membrane proteome of Caco-2 cells

Human colorectal carcinoma (Caco-2) cells undergo in culture spontaneous enterocytic differentiation, characterized by polarization and appearance of the functional apical brush border membrane. To provide insights into the biology of differentiation, we have performed a comparative proteomic analysis of the plasma membranes from proliferating cells (PCs) and the apical membranes from differentiated cells (DCs). Proteins were resolved by SDS-PAGE, in-gel digested and analyzed by RP-LC and MS/MS. Alternatively, proteins were digested in solution, and tryptic peptides were labeled with isotopic tags and analyzed by 2-D LC followed by MS/MS. Among the 1125 proteins identified in both proteomes, 76 were found to be significantly increased in the membranes of DCs and 61 were increased in PCs. Majority of the proteins increased in the apical membranes were metabolic enzymes, proteins involved in the maintenance of cellular structure, transmembrane transporters, and proteins regulating vesicular transport. In contrast, majority of the proteins increased in the membranes of PCs were involved in gene expression, protein synthesis, and folding. Both groups contained many novel proteins with yet to be identified functions, which could provide potential new markers of the intestinal cells or of colorectal cancer.