Identification of miR‐21 targets in breast cancer cells using a quantitative proteomic approach

MicroRNA (miRNA) play essential roles in biological processes ranging from cellular proliferation to apoptosis. Recently, miRNA have also been implicated in a number of diseases including cancers. However, the targets of most miRNA remain unknown. The majority of reports describing identification of miRNA targets are based on computational approaches or detection of altered mRNA levels despite the fact that most miRNA are thought to regulate their targets primarily at the level of translational inhibition in animals. miR‐21 is a miRNA with oncogenic activity that is involved in various cancer‐related processes such as invasion and migration. Given the importance of miR‐21 in tumorigenesis, we employed a quantitative proteomic strategy to systematically identify potential targets of miR‐21. By knocking down the expression of endogenous miR‐21 in MCF‐7 breast cancer cells, we observed an increase in the abundance of 58 proteins, implying that they could be potential targets of miR‐21. Validation of 12 of these candidate targets in luciferase assays showed that 6 of them were likely direct targets of miR‐21. Importantly, the mRNA of the majority of the candidate targets tested did not show a concomitant increase in abundance. Overall, our results demonstrate that miR‐21 affects the expression of many of its targets through translational inhibition and highlights the utility of proteomic approaches for identifying miRNA targets.     

iTRAQ‐based proteomic analysis of dioscin on human HCT‐116 colon cancer cells

Dioscin shows various pharmacological effects. However, its activity on colorectal cancer is still unknown. The present work showed that dioscin significantly inhibited cell proliferation on human HCT‐116 colon cancer cells, and affected Ca²⁺ release and ROS generation. The content of nitric oxide (NO) and its producer inducible NO synthase (iNOS) associated with DNA damage and aberrant cell signaling were assayed using the kits. DNA damage and cell apoptosis caused by dioscin were also analyzed through single‐cell gel electrophoresis and in situ terminal deoxynucleotidyl transferase dUTP nick‐end labeling assays. The results showed that dioscin increased the levels of NO and inducible NO synthase. The comet length in dioscin‐treated groups was much longer than that of the control group, and the number of terminal deoxynucleotidyl transferase dUTP nick‐end labeling positive cells (apoptotic cells) was significantly increased by the compound (p < 0.01). Furthermore, dioscin caused mitochondrial damage and G2/M cell cycle arrest through transmission electron microscopy and flow cytometry analysis, respectively. To study the cytotoxic mechanism of dioscin, an iTRAQ‐based proteomics approach was used. There were 288 significantly different proteins expressed in response to dioscin, which were connected with each other and were involved in different Kyoto Encyclopedia of Genes and Genomes pathways. Then, some differentially expressed proteins involved in oxidative phosphorylation, Wnt, p53, and calcium signaling pathways were validated by Western blotting and quantitative real‐time PCR assays. Our work elucidates the molecular mechanism of dioscin‐induced cytotoxicity in colon cancer cells, and the identified targets may be useful for treatment of colorectal cancer in future.     

Proteomic analysis in human breast cancer: identification of a characteristic protein expression profile of malignant breast epithelium

Gene expression analysis has become a promising tool in predicting the clinical course of malignant disease and the response to antineoplastic therapy. Surprisingly, only little is known about the protein expression pattern of human tumors. Recent advances in proteomic analysis allow proteins of interest to be identified by their expression and/or modification pattern in 2-DE rather than using the traditional approach of translating gene expression data. To identify a proteomic pattern that is characteristic for malignant breast epithelium, we performed differential 2-DE analysis in sets of microdissected malignant breast epithelia and corresponding adjacent normal breast epithelia from five patients with invasive breast carcinoma. Thirty-two protein spots were found to be selectively regulated in malignant epithelium, and were subjected to MALDI-TOF and/or immunoblotting for protein identification. Thirteen of the identified proteins had previously not been associated with breast cancer. The validity of these findings was confirmed by literature review and immunohistochemistry for identified proteins in an independent cohort of 50 breast cancer specimens. We here describe, for the first time, a proteomic analysis of matched normal and malignant epithelia from invasive breast carcinomas. This strategy leads to a better understanding of oncogenesis at an operational level and helps to characterize the malignant phenotype of individual tumors, and thereby to identify novel targets for antineoplastic therapy.     

Multiplexed MRM‐based quantitation of candidate cancer biomarker proteins in undepleted and non‐enriched human plasma

An emerging approach for multiplexed targeted proteomics involves bottom‐up LC‐MRM‐MS, with stable isotope‐labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer‐biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM‐based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom‐up workflow) for the 27 biomarker proteins (represented by 57 interference‐free peptides). The linear dynamic range for the MRM assays spanned four orders‐of‐magnitude, with 25 assays covering a 10³–10⁴ range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin‐like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer‐associated protein biomarker panels in human plasma, prior to clinical use.     

Effect of collagen substrates on proteomic modulation of breast cancer cells

We have previously described the occurrence, in breast and colon cancer extra-cellular matrix, of an oncofoetal form of collagen, OF/LB, able to induce an increase in cell proliferation and motility in the breast cancer cell line 8701-BC. It also caused an increased amount of type V collagen which appears to exert an anti-proliferative effect on the same cells. The aim of the present study was to investigate, at the proteomic level, the effect of OF/LB and type V collagens used as substrates for neoplastic cell growth. Due to the complexity of a whole proteomic profile, a subset of significant protein classes was used to assess variations in protein expression levels. For this study we adopted a multivariate statistical procedure that allows a global view of the variations induced by different growth conditions, when several variables have to be analyzed simultaneously. The results of this research indicate that in response to different growth substrates, chaperons and heat shock proteins contributed most to the dissimilarity in levels of expression of the selected protein spots. Moreover, we observed that different isoforms of the same protein showed independent levels of expression from one another in relation to the different collagen treatments.     

Identification of specific reachable molecular targets in human breast cancer using a versatile ex vivo proteomic method

Targeting of tumoral tissues is one of the most promising approaches to improve both the efficacy and safety of anticancer treatments. The identification of valid targets, including proteins specifically and abundantly expressed in cancer lesions, is of utmost importance. Despite state-of-the-art technologies, the discovery of cancer-associated target proteins still faces the limitation, in human tissues, of antigen accessibility to suitable high-affinity ligands such as human mAb bound to bioactive molecules. Terminal perfusion of tumor-bearing mice or ex vivo perfusion of human cancer-bearing organs with a reactive biotin ester solution has successfully led to the identification of novel accessible biomarkers. This methodology is however restricted to perfusable organs, and excludes most of the tissues of interest to targeted therapies, e.g. primary breast cancer and metastases. Herein, we report on the development of a new chemical proteomic method that bypasses the perfusion step and thus offers the potential to identify accessible molecular targets in virtually all types of animal and human tissues. We have validated our new procedure by identifying biomarkers selectively expressed in human breast carcinoma. Overall, this powerful technology may lay the ground not only for custom-made therapies in cancer, but also for the development of therapies that need to be selectively delivered in a specific tissue.     

Quantitative proteome analysis of breast cancer cell lines using 18O-labeling and an accurate mass and time tag strategy

Proteome comparison of cell lines derived from cancer and normal breast epithelium provide opportunities to identify differentially expressed proteins and pathways associated with specific phenotypes. We employed 16O/18O peptide labeling, FT-ICR MS, and an accurate mass and time (AMT) tag strategy to simultaneously compare the relative abundance of hundreds of proteins in non-cancer and cancer cell lines derived from breast tissue. A cell line reference panel allowed relative protein abundance comparisons among multiple cell lines and across multiple experiments. A peptide database generated from multidimensional LC separations and MS/MS analysis was used for subsequent AMT tag-based peptide identifications. This peptide database represented a total of 2299 proteins, including 514 that were quantified in five cell lines using the AMT tag and 16O/18O strategies. Eighty-six proteins showed at least a threefold protein abundance change between cancer and non-cancer cell lines. Hierarchical clustering of protein abundance ratios revealed that several groups of proteins were differentially expressed between the cancer cell lines.     

SILAC‐based quantitative proteomic analysis of secretome of Marc‐145 cells infected with porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent of PRRS, which causes severe reproductive failure in sows, respiratory disease in young and growing pigs, and enormous economic losses to the global swine industry. In this study, SILAC combined with MS/MS was used to quantitatively identify the secretory proteins differentially expressed in PRRSV‐infected Marc‐145 cells compared with mock‐infected controls. In total, we identified 204 secretory proteins showing significant differences in infected cells (163 upregulated, 41 downregulated). Intensive bioinformatic analysis of secretome data revealed that PRRSV infection strongly activated nonclassical protein secretion, especially vesicle‐mediated release of exosomal proteins, including different danger‐associated molecular pattern molecules and the majority of secreted proteins involved in protein binding and transport, regulation of response to stimulus, metabolic processes, and immune responses. According to the functional proteins analysis, we speculate that proteins functioning in binding, transport, and the immune response are exploited by PRRSV to facilitate virus replication and immune evasion. Our study for the first time analyzes the secretory protein profile of PRRSV‐infected Marc‐145 cells and provides valuable insight into the host response to PRRSV infection.     

Scanning of novel cancer/testis proteins by human testis proteomic analysis

The testes are where spermatogenesis, the sperm‐generating process that is unique to men, occurs. Importantly, human spermatogenesis and tumorigenesis share key similarities. Until now, only a few proteins in the human testis have been identified due to limitations of available technology. In this paper, using an advanced proteomics platform, we have identified 7346 unique proteins within the human testis with a high degree of confidence. Immunohistochemistry data from the Human Protein Atlas database show over 90% (1833/2020) of identified proteins can be detected in the human testis using specific antibodies. To make the data widely available to the scientific community, an online Human Testis Proteome Database (HTPD, http://reprod.njmu.edu.cn/htpd/ ) was built. Many of the identified human testicular proteins are associated with human infertility, especially human testicular predominantly expressed proteins. We characterized six novel cancer/testis genes (TMPRSS12, TPPP2, PRSS55, DMRT1, PIWIL1, HEMGN), which map to cancer‐associated genetic variants positions, in both the cancer and testis tissues using genome‐wide analyses. Our results provide a molecular connection between spermatogenesis and tumorigenesis and broaden the range of cancer antigen choice available for immunotherapy.     

Proteomic characterization of Her2/neu-overexpressing breast cancer cells

The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with MS/MS, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in mouse mammary tumor virus-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray data sets revealed a 23-gene signature, which can be used to predict the probability of metastasis-free survival in breast cancer patients.     

Anti-growth factor activities of benzothiophenes in human breast cancer cells

We have tested the effects of two Eli-Lilly compounds, LY 117, 018 and raloxifene, on E2-regulated and IGF-I-induced proliferation or AP-1 activity in human breast cancer cells. We now demonstrate that both molecules have strong antiestrogenic and anti-growth factor inhibitory effects in MCF7 cells. They were as potent as ICI 182, 780 and more efficient than OH-Tam to prevent estradiol action whereas their inhibition on IGF-I stimulation was less than with ICI 182, 780 and equivalent to that of OH-Tam. Moreover, raloxifene was the most efficient molecule to prevent IGF-I-induced AP-1 activity, with a significant effect observed with a concentration as low as 5 × 10⁻¹¹ M in the presence of IGF-I alone. Similar dose–response curves were obtained with a combined treatment of IGF-I and E2 with a 2 log shift. Their action on IGF-I-induced proliferation was completely abrogated in MCF7 transfectants in which the expression of an antiestrogen-regulated protein tyrosine phosphatase, PTPL1, was abolished by antisense RNA transfection. Accordingly, they were both able to dose-dependently regulate the expression of PTPL1 and to interfere with the PI3-K/Akt pathway by drastically decreasing Akt phosphorylation exclusively in wild-type PTPL1 expressing cells.

Our data altogether demonstrate that raloxifene has a potent inhibitory effect on IGF-I action, with a drastic effect on AP-1 triggered responses as well as on Akt phosphorylation, suggesting that it might be a useful therapeutic agent in tumors in which these signalling pathways become constitutively active.     

A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non‐invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically‐derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC.     

Identification of potential immunotherapy biomarkers for breast cancer by bioinformatics analysis

Breast cancer is a serious malignancy with a high incidence worldwide and a tendency to relapse. We used integrated bioinformatics analysis to identify potential biomarkers in breast carcinoma in the present study. Microarray data, 127breast tumor samples and 23 non-tumor samples, received from the Gene Expression Omnibus (GEO) dataset; 121 differentially expressed genes (DEGs) were selected. Functional analysis using DAVID revealed that these DEGs were highly gathered in endodermal cell differentiation and proteinaceous extracellular matrix. Five bioactive compounds (prostaglandin J2, tanespimycin, semustine, 5182598, and flunarizine) were identified using Connectivity Map. We used Cytoscape software and STRING dataset to structure a protein–protein interaction (PPI) network. The expression of CD24, MMP1, SDC1, and SPP1 was much higher in breast carcinoma tissue than in Para cancerous tissues analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) and ONCOMINE. Overexpression ofCD24, MMP1, SDC1, and SPP1 indicated the poor prognosis in breast carcinoma patients analyzed by Kaplan–Meier (KM) Plotter. Immunohistochemistry microarray was used to further confirm that protein expression of CD24, MMP1, SDC1, and SPP1 was much higher in tumor sections than in Para cancerous tissues. Hub genes expression at the protein level was correlated tothe breast cancer subtype and grade. Furthermore, immunity analysis showed that CD24, MMP1, SDC1, and SPP1 were potentially associated with five immune cell types infiltration (CD8+ T cells, CD4+ T cells, neutrophils, macrophages,and dendritic cells) by TIMER. Thus, this study indicates potential biomarkers that could have applications in the development of immune therapy for breast cancer. However, further studies are required for verifying these results in vivo and vitro.     

Mass spectrometry‐based secretome analysis of non‐small cell lung cancer cell lines

Tyrosine kinase inhibitors, such as erlotinib, display reliable responses and survival benefits for the treatment of human non‐small cell lung cancer (NSCLC) patients. However, primary or acquired resistance limits their therapeutic success. In this study, we conducted in‐depth mass spectrometric analyses of NSCLC cell secretomes. To identify secreted proteins that are differentially regulated in erlotinib‐sensitive (PC‐9) and ‐resistant (PC‐9ER) NSCLC cell lines, SILAC experiments were performed. On average, 900 proteins were identified in each sample with low variations in the numbers of identified proteins. Fourteen proteins were found to be differently regulated among erlotinib‐sensitive and ‐resistant NSCLC cell lines, with five proteins (tissue‐type plasminogen activator, epidermal growth factor receptor, urokinase‐type plasminogen activator, platelet‐derived growth factor D, and myeloid‐derived growth factor) showing the most prominent regulation. Tissue‐type plasminogen activator (t‐PA) was up to 10‐times upregulated in erlotinib‐resistant NSCLC cells compared with erlotinib‐sensitive cells. T‐PA is an established tumor marker for various cancer types and seems to be a promising prognostic marker to differentiate erlotinib‐sensitive from erlotinib‐resistant NSCLC cells. To gain further insights into t‐PA‐regulated pathways, a t‐PA variant was expressed in E. coli cells and its interactions with proteins secreted from erlotinib‐sensitive and ‐resistant NCSLC cells were studied by a combined affinity enrichment chemical cross‐linking/mass spectrometry (MS) approach. Fourteen proteins were identified as potential t‐PA interaction partners, deserving a closer inspection to unravel the mechanisms underlying erlotinib resistance in NSCLC cells.     

Quantitative analysis of cytochrome P450 isoforms in human liver microsomes by the combination of proteomics and chemical probe‐based assay

Cytochrome P450 (CYP) is one of the most important drug‐metabolizing enzyme families, which participates in the biotransformation of many endogenous and exogenous compounds. Quantitative analysis of CYP expression levels is important when studying the efficacy of new drug molecules and assessing drug–drug interactions in drug development. At present, chemical probe‐based assay is the most widely used approach for the evaluation of CYP activity although there are cross‐reactions between the isoforms with high sequence homologies. Therefore, quantification of each isozyme is highly desired in regard to meeting the ever‐increasing requirements for carrying out pharmacokinetics and personalized medicine in the academic, pharmaceutical, and clinical setting. Herein, an absolute quantification method was employed for the analysis of the seven isoforms CYP1A2, 2B6, 3A4, 3A5, 2C9, 2C19, and 2E1 using a proteome‐derived approach in combination with stable isotope dilution assay. The average absolute amount measured from twelve human liver microsomes samples were 39.3, 4.3, 54.0, 4.6, 10.3, 3.0, and 9.3 (pmol/mg protein) for 1A2, 2B6, 3A4, 3A5, 2C9, 2C19, and 2E1, respectively. Importantly, the expression level of CYP3A4 showed high correlation (r = 0.943, p < 0.0001) with the functional activity, which was measured using bufalin—a highly selective chemical probe we have developed. The combination of MRM identification and analysis of the functional activity, as in the case of CYP3A4, provides a protocol which can be extended to other functional enzyme studies with wide application in pharmaceutical research.     

Expanding the protein catalogue in the proteome reference map of human breast cancer cells

In this report we present a catalogue of 162 proteins (including isoforms and variants) identified in a prototype of proteomic map of breast cancer cells. This work represents the prosecution of previous studies describing the protein complement of breast cancer cells of the line 8701-BC, which has been well characterized for several parameters, providing to be a useful model for the study of breast cancer-associated candidate biomarkers. In particular, 110 spots were identified ex novo by PMF, or validated following previous gel matching identification method; 30 were identified by N-terminal microsequencing and the remaining by gel matching with maps available from our former work. As a consequence of the expanded number of proteins, we have updated our previous classification extending the number of protein groups from 4 to 13. In order to facilitate comparative proteome studies of different kinds of breast cancers, in this report we provide the whole complement of proteins so far identified and grouped into the new classification. A consistent number of them were not described before in other proteomic maps of breast cancer cells or tissues, and therefore they represent a valuable contribution for breast cancer protein databases and for future application in basic and clinical researches.     

Use of serological proteomic methods to find biomarkers associated with breast cancer

New technologies for the detection and therapy of early stage breast cancer are urgently needed. Pathological changes in breast might be reflected in proteomic patterns in serum. A proteomic tool was used to identify proteomic patterns in serum that distinguishes neoplastic from non-neoplastic disease within the breast. Preliminary results derived from the serum analysis from 54 unaffected women and 76 patients with breast cancer were analyzed by two-dimensional (2-D) electrophoresis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry, HSP27 was found up-regulated while 14-3-3 sigma was down-regulated in the serum of breast cancer patients. The two protein biomarkers were then used to classify an independent set of 104 masked serum samples. The results showed that the protein pattern on 2-D gels can completely segregate the serum of breast cancer from non-cancer. The discriminatory pattern correctly identified all 69 breast cancer cases in the masked set. Of the 35 cases of non-malignant disease, 34 were recognized as non-cancer. These findings justify a prospective population-based assessment of proteomic technology as a screening or diagnostic tool for breast cancer in high-risk and general populations. These two protein biomarkers could also be used as targets for further study in drug design and breast cancer therapy.     

Estrogen regulation and ion dependence of taurine uptake by MCF-7 human breast cancer cells

It has been reported that estrogen receptor-positive MCF-7 cells express TauT, a Na⁺-dependent taurine transporter. However, there is a paucity of information relating to the characteristics of taurine transport in this human breast cancer cell line. Therefore, we have examined the characteristics and regulation of taurine uptake by MCF-7 cells. Taurine uptake by MCF-7 cells showed an absolute dependence upon extracellular Na⁺. Although taurine uptake was reduced in Cl^- free medium a significant portion of taurine uptake persisted in the presence of NO₃ ^-. Taurine uptake by MCF-7 cells was inhibited by extracellular β-alanine but not by L-alanine or L-leucine. 17β-estadiol increased taurine uptake by MCF-7 cells: the V_max of influx was increased without affecting the K_m. The effect of 17β-estradiol on taurine uptake by MCF-7 cells was dependent upon the presence of extracellular Na⁺. In contrast, 17β-estradiol had no significant effect on the kinetic parameters of taurine uptake by estrogen receptor-negative MDA-MB-231 cells. It appears that estrogen regulates taurine uptake by MCF-7 cells via TauT. In addition, Na⁺-dependent taurine uptake may not be strictly dependent upon extracellular Cl^-.