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.     

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.     

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 novel serum peptides biomarkers for female breast cancer patients in Western China

This study aimed to identify novel serum peptides biomarkers for female breast cancer (BC) patients. We analyzed the serum proteomic profiling of 247 serum samples from 96 BC patients, 48 additional paired pre‐ and postoperative BC patients, 39 fibroadenoma patients as benign disease controls, and 64 healthy controls, using magnetic‐bead‐based separation followed by MALDI‐TOF MS. ClinProTools software identified 78 m/z peaks that differed among all analyzed groups, ten peaks were significantly different (P < 0.0001), with Peaks 1–6 upregulated and Peaks 7–10 downregulated in BC. Moreover, three peaks of ten (Peak 1, m/z: 2660.11; Peak 2, m/z: 1061.09; Peak 10, m/z: 1041.25) showed a tendency to return to healthy control values after surgery. And these three peptide biomarkers were identified as FGA605‐629, ITIH4 347–356, and APOA2 43–52. Methods used in this study could generate serum peptidome profiles of BC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.     

Crucial considerations for pipelines to validate circulating biomarkers for breast cancer

Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.     

Molecular mapping the presence of druggable targets in preinvasive and precursor breast lesions: A comprehensive review of biomarkers related to therapeutic interventions

The analysis of clinical breast samples using biomarkers is integral to current breast cancer management. Currently, a limited number of targeted therapies are standard of care in breast cancer treatment. However, these targeted therapies are only suitable for a subset of patients and resistance may occur. Strategies to prevent the occurrence of invasive lesions are required to reduce the morbidity and mortality associated with the development of cancer. In theory, application of targeted therapies to pre-invasive lesions will prevent their progression to invasive lesions with full malignant potential. The diagnostic challenge for pathologists is to make interpretative decisions on early detected pre-invasive lesions. Overall, only a small proportion of these pre-invasive lesions will progress to invasive carcinoma and morphological assessment is an imprecise and subjective means to differentiate histologically identical lesions with varying malignant potential. Therefore differential biomarker analysis in pre-invasive lesions may prevent overtreatment with surgery and provide a predictive indicator of response to therapy. There follows a review of established and emerging potential druggable targets in pre-invasive lesions and correlation with lesion morphology.     

Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues,cell lines and conditioned medium

Background

Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures. Circulating biomarkers may serve as a valuable adjunctive tool to imaging.

Results

We developed a broad-based proteomics discovery program, integrating liquid chromatography/mass spectrometry (LC/MS) analyses of freshly resected lung tumor specimens (n = 13), lung cancer cell lines (n = 17), and conditioned media collected from tumor cell lines (n = 7). To enrich for biomarkers likely to be found at elevated levels in the peripheral circulation of lung cancer patients, proteins were prioritized based on predicted subcellular localization (secreted, cell-membrane associated) and differential expression in disease samples. 179 candidate biomarkers were identified. Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189). An 8-marker model was developed (TFPI, MDK, OPN, MMP2, TIMP1, CEA, CYFRA 21–1, SCC) which accurately distinguished subjects with lung cancer (n = 50) from high risk smokers (n = 50) in an independent validation study (AUC = 0.775).

Conclusions

Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers. This unique collection of biomarkers may have clinical utility in lung cancer detection and diagnoses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9090-9) contains supplementary material, which is available to authorized users.     

Pattern of serum immunoreactivity against breast cancer cell lysates may predict severity of disease in breast cancer patients

Humoral tumor-specific immunity has been investigated as a potential tool to identify tumor-associated antigens and evaluate cancer diagnosis and prognosis. Using SDS-PAGE and western blotting techniques we investigated the humoral immune response against tumor cell antigens in 36 breast cancer patients, 17 node-positive (NP) and 19 node-negative (NN). As a source of antigens, we prepared protein lysates from four breast cancer cell lines (AU565, BT474, MCF-7 and MDA-MB-231) which in vitro exhibit different features of invasion, estrogen receptor/progesterone receptor status and HER2/neu expression thereby potentially representing mild to aggressive forms of clinical disease. A higher number of immunocomplexes Ag–Ab were formed when serum from NN patients was immunoreacted against lysates from AU565 and MCF-7 in comparison to serum from NP patients (P < 0.01). BT474 cells were not a good antigenic source. MDA-MB-231 cells could not significantly discriminate between NN and NP patients since both groups showed higher amounts of reactivity against the lysate. However, comparative analysis of protein preparations purified from MCF-7 and MDA-MB-231 cells and immunodetected concomitantly with the same serum samples showed that serum from patients with cancers with worse prognosis (stage, nodality, HER2/neu and hormonal status) reacted more intensely to proteins purified from the relatively more invasive cell line MDA-MB-231 compared to MCF-7. These findings suggest that the study of serum antibody reactivity to antigens purified from breast cancer cell lines with different invasive properties should be further investigated for its potential in providing beneficial prognostic information in breast cancer. Supported by the United States Military Cancer Institute and the Department of Clinical Investigation at Walter Reed Army Medical Center. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or reflecting the views of the Department of the Army or the Department of Defense.     

XPF -673C>T variation is associated with the susceptibility to breast cancer

PurposeXPF variations might decrease the DNA repair capacity and further contribute to cancer development. This study aimed to investigate the association of XPF polymorphisms with risk of developing breast cancer.MethodsTCGA, the Human Protein Atlas and Kaplan-Meier plotter were used to analyze the expression of XPF in breast cancer tissues and its effect on the survival of breast cancer patients. The expression of XPF in breast cancer tissues was detected by qRT-PCR. This case-control study included 467 breast cancer patients and 467 healthy controls. The genotype of genetic variation was detected by polymerase chain reaction restriction fragment length polymorphism. Odds ratios and 95 % confidence intervals were calculated. Correlations between XPF variation and clinicopathological parameters were assessed through Kendall’s Tau-b test. The relationship between XPF gene function variation and XPF gene expression was analyzed by GTEx.ResultsThe expression of XPF in breast cancer tissues is higher than that in normal tissues. Breast cancer patients with high XPF expression have a higher relapse free survival rate (HR = 0.88, 95 % CI = 0.80−0.97), but have no effect on the overall survival rate (logrank P = 0.28). XPF -673C > T variant can reduce the risk of breast cancer patients (OR = 0.35, 95 %CI = 0.20−0.63 for codominant mode; OR = 0.66, 95 %CI = 0.51−0.85 for dominant model; OR = 0.40, 95 %CI = 0.23−0.70 for recessive model). The XPF 11985 GG genotype reduced the risk of early breast cancer (OR = 0.49, 95 %CI = 0.24−0.97), but not the risk of advanced breast cancer (OR = 1.20, 95 % CI = 0.58−2.48). XPF 11985A > G variant can also reduce the risk of ERBB2 expression in patients (OR = 0.50, 95 %CI = 0.27−0.94). There is no correlation between XPF -673C > T/XPF11985A > G variants and ER and PR. XPF -673C > T variant can reduce XPF expression (P < 0.05).ConclusionsGenetic variations of XPF gene may affect its expression and the risk of breast cancer in the Chinese population.     

Identification of tumor-associated plasma biomarkers using proteomic techniques: from mouse to human

In an effort to identify tumor-associated proteins from plasma of tumor-bearing mice that may be used as diagnostic biomarkers, we developed a strategy that combines a tumor xenotransplantation model in nude mice with comparative proteomic technology. Five human cancer cell lines (SC-M1, HONE-1, CC-M1, OECM1, GBM 8401) derived from stomach, nasopharyngeal, colon, oral and brain cancers were subcutaneously inoculated into nude mice and compared to control nude mice injected with phosphate-buffered saline. One month later, plasma from mice inoculated with cancer cells was collected for proteomic analysis using two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS). Comparison of plasma 2-DE maps from tumor-bearing mice with those produced from control mice revealed the overexpression of several mouse acute phase proteins (APPs) such as haptoglobin. Another APP, serum amyloid A (SAA), was found only in mice bearing tumors induced by the stomach cancer cell line SC-M1, which has not previously been demonstrated in xenotransplatation experiment. Furthermore, by using immunohistochemistry, SAA and haptoglobin were found to originate from the mouse hosts and not from the human cancer cell line donors. The protein alterations were further confirmed on patients with stomach cancers where up-regulated levels of SAA were also observed. These results indicate that APPs may be used as nonspecific tumor-associated serum markers. SAA in particular may serve as a potential marker for detecting stomach cancer. Taken together, the combination of the xenotransplatation model in nude mice and proteomics analysis provided a valuable impact for clinical applications in cancer diagnostics. In addition, our findings demonstrate that a panel of APPs might serve as screening biomarkers for early cancer detection.     

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.     

Multi-parametric MRI lesion heterogeneity biomarkers for breast cancer diagnosis

PurposeTo identify intra-lesion imaging heterogeneity biomarkers in multi-parametric Magnetic Resonance Imaging (mpMRI) for breast lesion diagnosis.MethodsDynamic Contrast Enhanced (DCE) and Diffusion Weighted Imaging (DWI) of 73 female patients, with 85 histologically verified breast lesions were acquired. Non-rigid multi-resolution registration was utilized to spatially align sequences. Four (4) DCE (2^nd post-contrast frame, Initial-Enhancement, Post-Initial-Enhancement and Signal-Enhancement-Ratio) and one (1) DWI (Apparent-Diffusion-Coefficient) representations were analyzed, considering a representative lesion slice. 11 1^st-order-statistics and 16 texture features (Gray-Level-Co-occurrence-Matrix (GLCM) and Gray-Level-Run-Length-Matrix (GLRLM) based) were derived from lesion segments, provided by Fuzzy C-Means segmentation, across the 5 representations, resulting in 135 features. Least-Absolute-Shrinkage and Selection-Operator (LASSO) regression was utilized to select optimal feature subsets, subsequently fed into 3 classification schemes: Logistic-Regression (LR), Random-Forest (RF), Support-Vector-Machine-Sequential-Minimal-Optimization (SVM-SMO), assessed with Receiver-Operating-Characteristic (ROC) analysis.ResultsLASSO regression resulted in 7, 6 and 7 features subsets from DCE, DWI and mpMRI, respectively. Best classification performance was obtained by the RF multi-parametric scheme (Area-Under-ROC-Curve, (AUC) ± Standard-Error (SE), AUC ± SE = 0.984 ± 0.025), as compared to DCE (AUC ± SE = 0.961 ± 0.030) and DWI (AUC ± SE = 0.938 ± 0.032) and statistically significantly higher as compared to DWI. The selected mpMRI feature subset highlights the significance of entropy (1^st-order-statistics and 2^nd-order-statistics (GLCM)) and percentile features extracted from 2^nd post-contrast frame, PIE, SER maps and ADC map.ConclusionCapturing breast intra-lesion heterogeneity, across mpMRI lesion segments with 1^st-order-statistics and texture features (GLCM and GLRLM based), offers a valuable diagnostic tool for breast cancer.     

Glutathione S-transferase T1 polymorphism is associated with breast cancer susceptibility

The association between present/null polymorphism of glutathione S-transferase T1 (GSTT1) and breast cancer risk are still inconclusive. We performed a meta-analysis to derive a more precise estimation of the relationship. A total of 48 studies including 17,254 cases and 21,163 controls were involved in this meta-analysis. When all studies were pooled into the meta-analysis, significantly elevated breast cancer risk was associated with null genotype (OR = 1.138, 95% CI = 1.051–1.232). When stratified by ethnicity, significantly increased risks were found for Caucasians (OR = 1.185, 95% CI = 1.075–1.306), but no statistically significantly increased risks were found in Asians (OR = 1.017, 95% CI = 0.846–1.223) and Africans (OR = 1.160, 95% CI = 0.815–1.650). In the subgroup analysis by controls source, statistically significantly elevated risks were both found in population-based studies (OR = 1.123, 95% CI = 1.014–1.243) and hospital-based studies (OR = 1.181, 95% CI = 1.056–1.321). When stratified by menopausal status, no statistically significantly increased risks were found in premenopausal women (OR = 1.115, 95% CI = 0.925–1.345) and postmenopausal women (OR = 1.077, 95% CI = 0.992–1.169). In summary, this meta-analysis suggests that the GSTT1 null genotype is a risk allele for breast cancer development. However, large sample and representative population-based studies with homogeneous breast cancer patients and well matched controls are warranted to confirm this finding.     

Urinary estrogen metabolites and breast cancer: differential pattern of risk found with pre- versus post-treatment collection

INTRODUCTION: The products of estrogen metabolism may affect breast carcinogenesis. The 16alpha-hydroxyestrone (16-OHE) metabolite has a higher affinity for the estrogen receptor (ER) than the 2-hydroxyestrone (2-OHE) metabolite, while conjugated 2-OHE metabolite may inhibit angiogenesis. We investigated the association between the relative concentrations of these metabolites in urine (2-OHE/16-OHE) and breast cancer in a case-control study of Chinese women living in Shanghai. METHODS: Incident breast cancer cases between 25 and 65 years of age (n=110) were identified from hospital or population tumor registries in Shanghai, China. Controls (n=110) were randomly selected from a complete registry of the Shanghai population, and individually matched to cases by menopausal status, age, and pre-treatment or post-treatment urine collection time. Urine samples were collected prior to any breast cancer treatment or surgery among 78 case-control pairs, while urine was collected after surgery, and perhaps other treatments, among 32 case-control pairs. A commercial enzyme-immunoassay kit was used to measure urinary estrogen metabolite concentrations. Conditional logistic regression was used to calculate odds ratios summarizing the 2-OHE/16-OHE and breast cancer association within subjects providing either pre-treatment or post-treatment urine samples. RESULTS: Subjects with a higher urinary 2-OHE/16-OHE ratio were less likely to be diagnosed with breast cancer, but only when urine samples were collected prior to breast cancer treatment (OR(Tertile3(T3)versusTertile1(T1))=0.5, 95% CI (0.2, 1.1)). In contrast, a higher 2-OHE/16-OHE ratio was significantly associated with breast cancer among subjects providing urine specimens after treatment initiation (OR(T3versusT1)=8.7, 95% CI (1.6, 47.1)). This observed cross-over modification occurred within both pre-menopausal and post-menopausal women, and independent of body mass index or recent dietary intake. CONCLUSION: Cross-study differences in urine collection protocols may explain observed inconsistencies in the 2-OHE/16-OHE and breast cancer association. Our case-control analysis using pre-treatment urine samples suggested that a lower 2-OHE/16-OHE ratio was associated with an increased risk of pre-menopausal and post-menopausal breast cancer diagnosis among Chinese women.     

Discovery of urine biomarkers for bladder cancer via global metabolomics

Bladder cancer (BC) is latent in its early stage and lethal in its late stage. Therefore, early diagnosis and intervention are essential for successful BC treatment. Considering the limitations of current diagnostic tools, noninvasive biomarkers that are both highly sensitive and specific are needed to improve the overall survival and quality of life of patients. With the advent of systems biology, “-omics” technologies have been developed over the past few decades. As a promising member, global metabolomics has increasingly been found to have clear potential for biomarker discovery. However, urinary metabolomics studies related to BC have lagged behind those of other urinary cancers, and major findings have not been systematically reported. The objective of this review is to comprehensively list the currently identified potential urinary metabolite biomarkers for BC.     

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.     

Common plasma protein marker LCAT in aggressive human breast cancer and canine mammary tumor

Breast cancer is one of the most frequently diagnosed cancers. Although biomarkers are continuously being discovered, few specific markers, rather than classification markers, representing the aggressiveness and invasiveness of breast cancer are known. In this study, we used samples from canine mammary tumors in a comparative approach. We subjected 36 fractions of both canine normal and mammary tumor plasmas to high-performance quantitative proteomics analysis. Among the identified proteins, LCAT was selectively expressed in mixed tumor samples. With further MRM and Western blot validation, we discovered that the LCAT protein is an indicator of aggressive mammary tumors, an advanced stage of cancer, possibly highly metastatic. Interestingly, we also found that LCAT is overexpressed in high-grade and lymphnode-positive breast cancer in silico data. We also demonstrated that LCAT is highly expressed in the sera of advanced-stage human breast cancers within the same classification. In conclusion, we identified a possible common plasma protein biomarker, LCAT, that is highly expressed in aggressive human breast cancer and canine mammary tumor.     

miRNA expression profiling for identification of potential breast cancer biomarkers

To identify micro RNA (miRNA) biomarker candidates for early detection of breast cancer and detection of minimal residual breast cancer, we performed miRNA expression profiling in pooled RNA samples from breast tumors, and from bone marrow mononuclear cells, peripheral blood mononuclear cells and plasma from healthy controls. We found substantially higher levels of five miRNAs in the breast tumors compared to the normal samples. However, validation of these miRNA levels, and seven other candidates selected from the literature, in individual samples from healthy controls and patients with non-metastatic breast cancer did not suggest further examination of their biomarker potential.     

Overexpression of annexin A2 is associated with abnormal ubiquitination in breast cancer

Abnormal expression of annexin A2 contributes to metastasis and infiltration of cancer cells.To elucidate the cause of abnormal expression of annexin A2,Western blotting,immunoproteomics and immunohistochemical staining were performed to analyze differentially ubiquitinated proteins between fresh breast cancer tissue and its adjacent normal breast tissue from five female volunteers.We detected an ubiquitinated protein that was up-regulated in the cancer tissue,which was further identified as annexin A2 by mass spectrometry.These results suggest that abnormal ubiquitination and/or degradation of annexin A2 may lead to presence of annexin A2 at high level,which may further promote metastasis and infiltration of the breast cancer cells.