Identification of specific nuclear structural protein alterations in human breast cancer

Breast cancer is the most commonly diagnosed type of cancer and a major cause of death in women. Reliable biomarkers are urgently needed to improve early detection or to provide evidence of the prognosis for each individual patient through expression levels in tumor tissue or body fluids. This proteomic analysis focused on the nuclear structure of human breast cancer tissue, which has been shown to be a promising tool for cancer biomarker development. The nuclear matrix composition of human breast cancer (n = 14), benign controls (n = 2), and healthy controls (n = 2) was analyzed by high‐resolution two‐dimensional gel electrophoresis and mass spectrometry. Validation studies were performed in an individual sample set consisting of additional breast cancer tissues (n = 3) and additional healthy control tissues (n = 2) by one‐dimensional immunoblot. In this setting, we identified five proteins that were upregulated in human breast cancer tissue, but absent in the healthy and benign controls (P < 0.001). These spots were also present in the investigated human breast cancer cell lines, but absent in the MCF10a cell line, which represents normal human epithelial breast cells. Two of the breast cancer‐specific proteins have been confirmed to be calponin h2 and calmodulin‐like protein 5 by one‐dimensional immunoblot. This is the first study demonstrating the expression of both proteins in human breast cancer tissue. Further studies are required to investigate the potential role of these proteins as biomarkers for early diagnosis or prognosis in human breast cancer. J. Cell. Biochem. 112: 3176–3184, 2011. © 2011 Wiley Periodicals, Inc.     

ER/PR阳性和阴性乳腺癌的定量蛋白质组学和生物信息学比较研究

目的:建立雌/孕激素受体(ER/PR)阴性和阳性乳腺癌的蛋白质表达谱,寻找ER/PR阴性和阳性乳腺癌中差异表达蛋白,为乳腺癌患者提供新的预后预测指标和治疗新靶点。方法:应用蛋白质组学i TRAQ技术建立ER/PR阳性和阴性乳腺癌的蛋白质差异表达谱,鉴定两组乳腺癌的差异表达蛋白,对部分差异表达蛋白进行生物信息学分析,包括蛋白功能注释和分类GO分析和KEGG通路分析。结果:应用i TRAQ蛋白质组学技术对乳腺癌组织进行了蛋白组学分析,鉴定出ER/PR阳性和阴性组间有差异表达的蛋白4999种,以ER/PR阳性:ER/PR阴性≥3为上调标准,确定ER/PR阳性组上调蛋白101种。以ER/PR阳性:ER/PR阴性≤0.5为下调标准,ER/PR阳性组下调蛋白122种。GO分析结果显示ER/PR受体阴性和阳性乳腺癌的差异表达蛋白的分子功能、生物过程、细胞定位较为复杂,并且在上调蛋白和下调蛋白上存在分布差异。KEGG通路分析发现部分差异表达蛋白涉及201条信号通路。结论:ER/PR阳性和阴性乳腺癌间存在差异表达蛋白,这些蛋白涉及复杂的分子功能、生物过程和信号通路。     

Mitochondrial proteomics with siRNA knockdown to reveal ACAT1 and MDH2 in the development of doxorubicin‐resistant uterine cancer

Mitochondria are key organelles in mammary cells in responsible for a number of cellular functions including cell survival and energy metabolism. Moreover, mitochondria are one of the major targets under doxorubicin treatment. In this study, low‐abundant mitochondrial proteins were enriched for proteomic analysis with the state‐of‐the‐art two‐dimensional differential gel electrophoresis (2D‐DIGE) and matrix‐assistant laser desorption ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) strategy to compare and identify the mitochondrial protein profiling changes in response to the development of doxorubicin resistance in human uterine cancer cells. The mitochondrial proteomic results demonstrate more than fifteen hundred protein features were resolved from the equal amount pooled of three purified mitochondrial proteins and 101 differentially expressed spots were identified. In which, 39 out of these 101 identified proteins belong to mitochondrial proteins. Mitochondrial proteins such as acetyl‐CoA acetyltransferase (ACAT1) and malate dehydrogenase (MDH2) have not been reported with the roles on the formation of doxorubicin resistance in our knowledge. Further studies have used RNA interference and cell viability analysis to evidence the essential roles of ACAT1 and MDH2 on their potency in the formation of doxorubicin resistance through increased cell viability and decreased cell apoptosis during doxorubicin treatment. To sum up, our current mitochondrial proteomic approaches allowed us to identify numerous proteins, including ACAT1 and MDH2, involved in various drug‐resistance‐forming mechanisms. Our results provide potential diagnostic markers and therapeutic candidates for the treatment of doxorubicin‐resistant uterine cancer.     

应用二维电泳和质谱技术筛选喉癌及癌旁组织中的差异表达蛋白质

目的分离并鉴定喉癌和癌旁正常粘膜组织的差异表达蛋白质,为喉癌早期临床诊断、治疗提供新的有关的肿瘤生物学标记和靶标。方法收集5对人喉癌组织和对应的癌旁正常粘膜组织,提取组织总蛋白质,采用二维凝胶电泳技术分离蛋白并进行比较。选择在喉癌中明显差异表达的蛋白质点,进行质谱分析。结果获得了分辨率和重复性均较好的凝胶蛋白图谱。筛选出的在喉癌及癌旁正常粘膜组织中明显差异表达的10个蛋白质点,并成功鉴定。其中在喉癌组织中高表达的7个,低表达的3个。结论喉癌组织与癌旁正常粘膜组织蛋白存在明显的差异,筛选并鉴定出的这些蛋白质可能成为喉癌早期临床诊断、治疗的标志物和靶标。     

Establishment of a 2-D human urinary proteomic map in IgA nephropathy

Immunoglobulin A nephropathy (IgAN) is the most common form of immune complex-mediated glomerulonephritis worldwide. Although chronic renal failure develops in considerable numbers of IgAN patients, the exact etiology has not yet been clearly elucidated. To establish the urinary protein map of IgAN, we performed a urinary proteomic analysis. Thirteen patients with IgAN and 12 normal controls were recruited. Morning midstream spot urine samples were used with Centriprep ultrafiltration for concentration and desalting. 2-DE was performed and compared between IgAN and normal control, and urinary proteins were identified by MALDI-TOF MS. A large number of protein spots were identified in IgAN and normal control samples, with means of 311 spots and 174 spots, respectively. Approximately 216 protein spots were detected as differentially expressed in IgAN. Among these, 82 spots were over-expressed, and 134 spots were under-expressed compared to normal controls. A total of 84 differentially expressed spots, representing 59 different proteins, were finally identified in IgAN. We have established a urinary proteomic map of IgAN and this result helps in the identification. Further study is needed to determine the potential pathogenic role of these proteins.     

Searching urinary tumor markers for bladder cancer using a two-dimensional differential gel electrophoresis (2D-DIGE) approach

Aiming at identifying biomarkers for bladder cancer, the urinary proteome was explored through a two-dimensional gel-based proteomic approach (2D-DIGE) coupled with mass spectrometry and database interrogation. The increased expression of proteins differentially expressed between patients with bladder tumors and controls such as Reg-1 and keratin 10 was confirmed to be associated with bladder cancer progression on bladder cancer cell lines by immunoblotting, and bladder tumors by immunohistochemistry. Moreover, the association of these proteins, especially Reg-1, with tumor staging and clinical outcome was confirmed by immunohistochemistry using an independent series of bladder tumors contained in tissue microarrays (n=292). Furthermore, Reg-1 was quantified using an independent series of urinary specimens (n=80) and provided diagnostic utility to discriminate patients with bladder cancer and controls (area under the curve (AUC=0.88)). Thus, the 2D-DIGE approach has identified Reg-1 as a biomarker for bladder cancer diagnostics, staging, and outcome prognosis.     

Proteomic analysis of cervical cancer cells treated with suberonylanilide hydroxamic acid

Suberonylanilide hydroxamic acid (SAHA) is an orally administered histone deacetylase inhibitor (HDACI) that has shown significant antitumour activity in a variety of tumour cells. To identify proteins involved in its antitumour activity, we utilized a proteomic approach to reveal protein expression changes in the human cervical cancer cell line HeLa following SAHA treatment. Protein expression profiles were analysed by 2-dimensional polyacrylamide gel electrophoresis (2-DE) and protein identification was performed on a MALDI-Q-TOF MS/MS instrument. As a result, a total of nine differentially expressed proteins were visualized by 2-DE and Coomassie brilliant blue (CBB) staining. Further, all the changed proteins were positively identified via mass spectrometry (MS)/MS analysis. Of these, PGAM1 was significantly downregulated in HeLa cells after treatment with SAHA. Moreover, PGAM1 has been proven to be downregulated in another cervical cancer cell line (CaSki) by western blot analysis. Together, using proteomic tools, we identified several differentially expressed proteins that underwent SAHA-induced apoptosis. These changed proteins may provide some clues to a better understanding of the molecular mechanisms underlying SAHA-induced apoptosis in cervical cancer.     

Investigation of serum proteome alterations in human glioblastoma multiforme

Glioblastoma multiforme (GBM) or grade IV astrocytoma is the most common and lethal adult malignant brain tumor. The present study was conducted to investigate the alterations in the serum proteome in GBM patients compared to healthy controls. Comparative proteomic analysis was performed employing classical 2DE and 2D‐DIGE combined with MALDI TOF/TOF MS and results were further validated through Western blotting and immunoturbidimetric assay. Comparison of the serum proteome of GBM and healthy subjects revealed 55 differentially expressed and statistically significant (p <0.05) protein spots. Among the identified proteins, haptoglobin, plasminogen precursor, apolipoprotein A‐1 and M, and transthyretin are very significant due to their functional consequences in glioma tumor growth and migration, and could further be studied as glioma biomarkers and grade‐specific protein signatures. Analysis of the lipoprotein pattern indicated elevated serum levels of cholesterol, triacylglycerol, and low‐density lipoproteins in GBM patients. Functional pathway analysis was performed using multiple software including ingenuity pathway analysis (IPA), protein analysis through evolutionary relationships (PANTHER), database for annotation, visualization and integrated discovery (DAVID), and GeneSpring to investigate the biological context of the identified proteins, which revealed the association of candidate proteins in a few essential physiological pathways such as intrinsic prothrombin activation pathway, plasminogen activating cascade, coagulation system, glioma invasiveness signaling, and PI3K signaling in B lymphocytes. A subset of the differentially expressed proteins was applied to build statistical sample class prediction models for discrimination of GBM patients and healthy controls employing partial least squares discriminant analysis (PLS‐DA) and other machine learning methods such as support vector machine (SVM), Decision Tree and Naïve Bayes, and excellent discrimination between GBM and control groups was accomplished.     

Different techniques for urinary protein analysis of normal and lung cancer patients

Many components in urine are useful in clinical diagnosis and urinary proteins are known as important components to define many diseases such as proteinuria, kidney, bladder and urinary tract diseases. In this study, we focused on the comparison of different sample preparation methods for isolating urinary proteins prior to protein analysis of pooled healthy and lung cancer patient samples. Selective method was used for preliminary investigation of some putative urinary protein markers. Urine samples were passed first through a gel filtration column (PD-10 desalting column) to remove high salts and subsequently concentrated. Remaining interferences were removed by ultrafiltration or four precipitation methods. The analysis of urinary proteins by high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis showed many similarities in profiles among preparation methods and a few profiles were different between normal and lung cancer patients. In contrast, the results of two-dimensional gel electrophoresis (2-DE) showed more distinctly different protein patterns. Our finding showed that the sequential preparation of urinary proteins by gel filtration and ultrafiltration could retain most urinary proteins which demonstrated the highest protein spots on 2-D gels and able to identify preliminary urinary protein markers related to cancer. Although sequential preparation of urine samples by gel filtration and protein precipitation resulted in low amounts of proteins on 2-D gels, high Mr proteins were easily detected. Therefore, there are alternative choices for urine sample preparation for studying the urinary proteome and identifying urinary protein markers important for further preclinical diagnostic and therapeutic applications.     

Profiling signatures of ovarian cancer tumour suppression using 2D-DIGE and 2D-LC-MS/MS with tandem mass tagging

Epithelial ovarian cancer (EOC) is the most common form of gynaecological malignancy in the developed world and has a poor prognosis due to its late detection. Identifying molecular markers of the disease may provide novel approaches to screening and could enable targeted treatment and the design of novel therapies. Although blood is recognized as a highly important source of disease-related biomarkers, the complexity and dynamic range of protein abundance in body fluids has hampered proteomic biomarker discovery and alternative approaches using cell models may be more successful. Herein, we have utilized two cellular models of EOC, where transfer of normal chromosome 18 material into the EOC cell lines TOV-112D and TOV-21G induced in vitro and in vivo suppression of their tumourigenic phenotype. A combination of quantitative two-dimensional difference gel electrophoresis (2D-DIGE) and two-dimensional-liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) with tandem mass tagging (TMT) was employed to examine the whole cell, secreted and crude membrane proteomes of the parental and hybrid cell models to identify differentially expressed proteins as potential markers of tumour suppression. Protein changes of interest were confirmed by immunoblotting in additional hybrid and revertant cell lines where incorporated chromosome 18 material was lost. One candidate marker was also tested in sera from a set of ovarian cancer cases and controls. We have identified a list of promising candidate biomarkers for further testing and functional characterization.     

Selection of putative colorectal cancer markers by applying PCA on the soluble proteome of tumors: NDK A as a promising candidate

Aiming to find new tumor markers for colorectal cancer (CRC), we applied proteomic methodologies to compare the soluble sub-proteome of healthy and tumoral colorectal mucosa. Out of 91 differentially expressed proteins, 23 were selected by principal component analysis (PCA) as the major contributors to the overall difference detected. After MS/MS analysis, 16 proteins were identified. From those, we chose 14-3-3-zeta/delta, retinoblastoma-binding protein 4 (RBBP-4), DJ-1, and nucleoside diphosphate kinase A (NDK A) for further studies, on the basis of their levels and known implication in cancer. Specific immunodetection demonstrated only the NDK A levels allowed to differentiate healthy mucosa from tumor tissue in all the patients. Hence, we used the colon cancer cell line Caco-2 to study the relationship between NDK A and colon cell tumorigenesis, finding it over-expressed in undifferentiated (tumor-like) cells regarding the differentiated ones. Noticeably, we also found increased levels of the NDK A in the secretome of tumor-like cells and, as expected, indications of higher levels of NDK A in the serum of CRC patients. In conclusion, the four validated proteins could constitute a panel of tissue markers for CRC, being the NDK A the most interesting candidate for further serum biomarker studies.     

Proteomic analysis of selected prognostic factors of breast cancer

The incidence of breast cancer is on the rise but as yet there is no guaranteed beneficial treatment for many of the sufferers. The treatments specific for breast and other hormone-sensitive cancers work well at times, however, the population of women that they will benefit is relatively small. Many are limited to surgical, chemotherapy, and radiotherapy options. Here, using two-dimensional electrophoresis (2-DE) in conjunction with a silver stain and Western blotting approach, we attempt to locate selected known prognostic markers for breast cancer. With these results, we can exclude these proteins from the future search for potential pharmaceutical targets, using the same techniques. The proteins that were located include the estrogen receptor-alpha, beta-casein, cytokeratin 7, calponin and bax. For each protein an estimated M(r) and pI was gained. Each protein was found in multiple variants. By locating these proteins the number of unknown proteins found on the 2-DE gel has been reduced, helping the future search for novel markers that are shown as being differentially expressed between healthy and cancerous tissue samples.     

Proteomic analysis of maternal serum in down syndrome: identification of novel protein biomarkers

Down syndrome (DS) is the most prevalent chromosomal disorder, accounting for significant morbidity and mortality. Definitive diagnosis requires invasive amniocentesis, and current maternal serum-based testing requires a false-positive rate of about 5% to detect 85% of affected pregnancies. We have performed a comprehensive proteomic analysis to identify potential serum biomarkers to detect DS. First- and second-trimester maternal serum samples of DS and gestational age-matched controls were analyzed using multiple, complementary proteomic approaches, including fluorescence 2-dimensional gel electrophoresis (2D-DIGE), 2-dimensional liquid chromatography-chromatofocusing (2D-CF), multidimensional protein identification technology (MudPIT; LC/LC-MS/MS), and MALDI-TOF-MS peptide profiling. In total, 28 and 26 proteins were differentially present in first- and second-trimester samples, respectively. Of these, 19 were specific for the first trimester and 16 for the second trimester, and 10 were differentially present in both trimesters. Analysis of MALDI-TOF-MS peptide profiles with pattern-recognition software also discriminated between DS and controls in both trimesters, with an average recognition capability approaching 96%. A majority of the biomarkers identified are serum glycoproteins that may play a role in cellular differentiation and growth of fetus. Further characterization and quantification of these markers in a larger cohort of subjects may provide the basis for new tests for improved DS screening.     

Possible target‐related proteins and signal network of bufalin in A549 cells suggested by both iTRAQ‐based and label‐free proteomic analysis

Bufalin (BF) exhibited antiproliferation and antimigration effects on human A549 lung cancer cells. To search its target‐related proteins, protein expression profiles of BF‐treated and control cells were compared using two quantitative proteomic methods, iTRAQ‐based and label‐free proteomic analysis. A total of 5428 proteins were identified in iTRAQ‐based analysis while 6632 proteins were identified in label‐free analysis. The number of common identified proteins of both methods was 4799 proteins. By application of 1.20‐fold for upregulated and 0.83‐fold for downregulated cutoff values, 273 and 802 differentially expressed proteins were found in iTRAQ‐based and label‐free analysis, respectively. The number of common differentially expressed proteins of both methods was 45 proteins. Results of bioinformational analysis using Metacore^TM showed that the two proteomic methods were complementary and both suggested the involvement of oxidative stress and regulation of gene expression in the effects of BF, and fibronectin‐related pathway was suggested to be an important pathway affected by BF. Western blotting assay results confirmed BF‐induced change in levels of fibronectin and other related proteins. Overexpression of fibronectin by plasmid transfection ameliorated antimigration effects of BF. Results of the present study provided information about possible target‐related proteins and signal network of BF.     

Comprehensive quantitative lipidomic approach to investigate serum phospholipid alterations in breast cancer

Introduction

Globally, breast cancer is the most common cancer in women and ranks second most common cause of cancer related mortality. Although efforts are made by researchers in molecular characterization of breast cancer using “-OMIC’S” approaches, limited work has explored to understand the phospholipid alterations in breast cancer.

Objectives

This study aims to explore five classes of serum phospholipid alterations in breast cancer towards discrimination of breast cancer from benign and healthy controls.

Methods

Twenty eight each of breast cancer patients and age-matched benign and healthy control serum samples were used to identify alterations of phospholipids using liquid chromatography-multiple reaction monitoring-mass spectrometry. Both multivariate and univariate statistical analyses were applied to investigate breast cancer associated phospholipid alterations. Differentially expressed phospholipid species were further confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Results

Among the identified and quantified 200 phospholipids, 25 phospholipids were found to be statistically significant (VIP > 1.4 and ANOVA p < 0.05) in the serum of women with breast cancer when compared with benign and healthy controls. Comparison of serum phospholipids of breast cancer patients and healthy controls revealed 12 phospholipids were found to be differentially expressed in which six were up-regulated and six were down-regulated. While comparative analysis of breast cancer serum against benign showed an increased concentration of six phospholipids in breast cancer samples. Further, significantly altered phospholipids were structurally characterized by enhanced product ion scanning.

Conclusion

Our results demonstrate that some of the differentially regulated phospholipids identified in our study such as PE (14:1/16:0), PC (18:0/18:0), LPE 14:0, PE (20:0/22:2) could be a panel of potential signature which can discriminate breast cancer from benign and healthy controls. These findings also provide insight into lipidomic information that can be used for monitoring of breast cancer progression.

     

Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection

Introduction

MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls.

Methods

We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718).

Results

Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202.

Conclusions

MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use.