Mining of serum glycoproteins by an indirect approach using cell line secretome

Glycosylation is the most important and abundant post-translational modification in serum proteome. Several specific types of glycan epitopes have been shown to be associated with various types of disease. Direct analysis of serum glycoproteins is challenging due to its wide dynamic range. Alternatively, glycoproteins can be discovered in the secretome of model cell lines and then confirmed in blood. However, there has been little experi-mental evidence showing cell line secretome as a tractable target for the study of serum glycoproteins. We used a hydrazine-based glycocapture method to selectively enrich glycoproteins from the secretome of the breast cancer cell line Hs578T. A total of 132 glycoproteins were identified by nanoLC-MS/MS analysis. Among the identified proteins, we selected 13 proteins that had one or more N-glycosylation motifs in the matched peptides, which were included in the Secreted Protein Database but not yet in the Plasma Proteome Database (PPD), and whose antibodies were commercially available. Nine out of the 13 selected proteins were detected from human blood plasma by western analysis. Furthermore, eight proteins were also detected from the plasma by targeted LC-MS/MS, which had never been previously identified by data-dependent LC-MS/MS. Our results provide novel proteins that should be enrolled in PPD and suggest that analysis of cell line secretome with subfractionation is an efficient strategy for discovering disease-relevant serum proteins.     

Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets

A "bottom-up" proteomics approach and a two-dimensional (strong cation exchange followed by reversed-phase) LC-MS/MS strategy on a linear ion trap (LTQ) were utilized to identify and compare expressions of extracellular and membrane-bound proteins in the conditioned media of three breast cell lines (MCF-10A, BT474, and MDA-MB-468). Proteomics analysis of the media identified in excess of 600, 500, and 700 proteins in MCF-10A, BT474, and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6, and 10 (ranging in concentration from 2 to 50 microg/liter) in MDA-MB-468 conditioned medium as validated by ELISA and confidently identified Her-2/neu in BT474 cells. Subcellular localization was determined based on Genome Ontology terms for all the 1,139 proteins of which 34% were classified as extracellular and membrane-bound. Proteomics analysis of MDA-MB-468 cell lysate demonstrated that only 5% of all identified proteins were extracellular. This confirmed our hypothesis that examining the CM of cell lines, as opposed to the cell lysates, leads to a significant enrichment in secreted proteins. Tissue specificity, functional classifications, and spectral counting were performed. Elafin, a protease inhibitor, identified in the conditioned media of BT474 and MDA-MB-468 and the three kallikreins (KLK5, KLK6, and KLK10) were validated using an immunoassay on various serum and biological samples. Some of the secreted proteins identified have established roles in breast cancer development (cell growth, differentiation, and metastasis) and/or are linked to early onset breast cancer. Our approach to mining for low abundance molecules could identify proteins in various stages of breast cancer development. Many of the identified proteins are potentially useful to investigate as circulating serum breast cancer biomarkers.     

Glioblastoma cell secretome: analysis of three glioblastoma cell lines reveal 148 non-redundant proteins

Glioblastoma multiforme (GBM) is the most aggressive among human gliomas with poor prognosis. Study of tumor cell secretome - proteins secreted by cancer cell lines, is a powerful approach to discover potential diagnostic or prognostic biomarkers. Here we report, for the first time, proteins secreted by three GBM cell lines, HNGC2, LN229 and U87MG. Analysis of the conditioned media of these cell lines by LC-MS/MS using ESI-IT mass spectrometer (LTQ) resulted in the confident identification of 102, 119 and 64 proteins, respectively. Integration of the results from all the three cell lines lead to a dataset of 148 non-redundant proteins. Subcellular classification using Genome Ontology indicated that 42% of the proteins identified belonged to extracellular or membrane proteins, viz. Vinculin, Tenascin XB, SERPIN F1 and TIMP-1. 52 proteins matched with the secretomes of 11 major cancer types reported earlier whereas remaining 96 are unique to our study. 25 protein identifications from the dataset represent proteins related to GBM or other cancer tissues as per Human Protein Atlas; at least 22 are detectable in plasma, 11 of them being reported even in cerebrospinal fluid. Our study thus provides a valuable resource of GBM cell secretome with potential for further investigation as GBM biomarkers.     

Quantitative proteomes and in vivo secretomes of progressive and regressive UV-induced fibrosarcoma tumor cells: mimicking tumor microenvironment using a dermis-based cell-trapped system linked to tissue chamber

The alterations of tumor proteome and/or in vivo secretome created by host-tumor cell interaction may be crucial factors for tumors to undergo progression or regression in a host system. Two UV-induced fibrosarcoma tumor cell lines (UV-2237 progressive cells and UV-2240 regressive cells) were used as models to address this issue. Hundreds of proteins including in vivo secretome have been identified and quantified via an isotope-coded protein label (ICPL) in conjunction with high-throughput NanoLC-LTQ MS analysis. A newly designed technology using a dermis-based cell-trapped system was employed to encapsulate and grow 3-D tumor cells. A tissue chamber inserted with a tumor cell-trapped dermis was implanted into mice to mimic the tumor microenvironment. The in vivo secretome created by host-tumor interaction was characterized from samples collected from tissue chamber fluids via ICPL labeling mass spectrometric analysis. Twenty-five proteins including 14-3-3 proteins, heat shock proteins, profilin-1, and a fragment of complement C3 with differential expression in proteomes of UV-2237 and UV-2240 cells were revealed. Three secreted proteins including myeloperoxidase, alpha-2-macroglobulin, and a vitamin D-binding protein have different abundances in the in vivo secretome in response to UV-2237 and UV-2240 cells. Differential tumor proteomes and in vivo secretome were thus accentuated as potential therapeutic targets to control tumor growth.     

Invasiveness of transformed human breast epithelial cell lines is related to cathepsin B and inhibited by cysteine proteinase inhibitors

The activities'of the lysosomal cysteine proteinases cathepsin B and L are regulated by their endogenous inhibitors, stefins A and B, and cystatin C, and their imbalance may be associated with increased invasiveness and development of the malignant cell phenotype. The aim of this study was to investigate mRNA, protein and activity levels of the above proteins in relation to in vitro invasiveness and to the reported in vivo tumorigenicity of four human breast tumor cell lines: the spontaneously immortalized cell line MCF10A, its c-Ha-ras transfectant MCF10AT, and two tumorigenic derivative cell lines, MCF10AT-Ca1a and MCF10AT-Ca1d. Invasiveness did not correlate with tumorigenicity, since the MCF10AT cell was the most invasive and the remaining three were at about half of its level. Cathepsin B expression paralleled the in vitro invasiveness through matrigel at all levels of expression, but cathepsin L did not. Stefin levels were elevated several-fold in the tumorigenic cell lines, but not in MCF10AT. The hypothesis that cathepsin B plays an active role in the invasion of breast cancer cell lines was confirmed by the fact that synthetic cysteine proteinase inhibitors, particularly those selective for cathepsin B, significantly reduced the invasion of the MCF10AT cells.     

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.     

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.     

Nuclear receptors agonists exert opposing effects on the inflammation dependent survival of breast cancer stem cells

Recent literature highlights the importance of pro-inflammatory cytokines in the biology of breast cancer stem cells (CSCs), unraveling differences with respect to their normal counterparts. Expansion of mammospheres (MS) is a valuable tool for the in vitro study of normal and cancer mammary gland stem cells. Here, we expanded MSs from human breast cancer and normal mammary gland tissues, as well from tumorigenic (MCF7) and non-tumorigenic (MCF10) breast cell lines. We observed that agonists for the retinoid X receptor (6-OH-11-O-hydroxyphenanthrene), retinoic acid receptor (all-trans retinoic acid (RA)) and peroxisome proliferator-activated receptor (PPAR)-γ (pioglitazone (PGZ)), reduce the survival of MS generated from breast cancer tissues and MCF7 cells, but not from normal mammary gland or MCF10 cells. This phenomenon is paralleled by the hampering of pro-inflammatory Nuclear Factor-κB (NF-κB)/Interleukin-6 (IL6) axis that is hyperactive in breast cancer-derived MS. The hindrance of such pathway associates with the downregulation of MS regulatory genes (SLUG, Notch3, Jagged1) and with the upregulation of the differentiation markers estrogen receptor-α and keratin18. At variance, the PPARα agonist Wy14643 promotes MS formation, upregulating NF-κB/IL6 axis and MS regulatory genes. These data reveal that nuclear receptors agonists (6-OH-11-O-hydroxyphenanthrene, RA, PGZ) reduce the inflammation dependent survival of breast CSCs and that PPARα agonist Wy14643 exerts opposite effects on this phenotype.     

Characterization of the secretome of chickpea suspension culture reveals pathway abundance and the expected and unexpected secreted proteins

The secretome of an organism is defined as a set of secreted proteins that encompasses all proteins exported to the extracellular space. To better understand the chickpea secretome, we used callus culture to isolate and identify secreted proteins as a step toward determining their functions. Proteins in the extracellular media of the suspension culture were examined using SDS-PAGE and mass spectrometry (LC-MS/MS). Proteomic analysis led to the identification of 773 proteins, presumably involved in a variety of functions including metabolism, signal transduction, transport, and cell defense, in addition to maintaining redox status of extracellular space. Bioinformatic analysis confirmed 724 proteins, accounting for 94% of the identified proteins, as constituents of the secretome. Analysis of the secretome revealed the presence of several proteins of unknown function and a large number of classical and nonclassical secreted proteins. This represents the first comprehensive secretome of a legume genome, which is yet to be sequenced. Comparative analysis of the chickpea secretome with those of Medicago, Arabidopsis, and rice revealed that the majority of identified proteins are seemingly species-specific. This study demonstrates that characterization of the chickpea secretome in vitro can be used to identify secreted proteins, which has implications for systems biology research.     

Combined Inhibition of ErbB1/2 and Notch Receptors Effectively Targets Breast Ductal Carcinoma In Situ (DCIS) Stem/Progenitor Cell Activity Regardless of ErbB2 Status

Pathways involved in DCIS stem and progenitor signalling are poorly understood yet are critical to understand DCIS biology and to develop new therapies. Notch and ErbB1/2 receptor signalling cross talk has been demonstrated in invasive breast cancer, but their role in DCIS stem and progenitor cells has not been investigated. We have utilised 2 DCIS cell lines, MCF10DCIS.com (ErbB2-normal) and SUM225 (ErbB2-overexpressing) and 7 human primary DCIS samples were cultured in 3D matrigel and as mammospheres in the presence, absence or combination of the Notch inhibitor, DAPT, and ErbB1/2 inhibitors, lapatinib or gefitinib. Western blotting was applied to assess downstream signalling. In this study we demonstrate that DAPT reduced acini size and mammosphere formation in MCF10DCIS.com whereas there was no effect in SUM225. Lapatinb reduced acini size and mammosphere formation in SUM225, whereas mammosphere formation and Notch1 activity were increased in MCF10DCIS.com. Combined DAPT/lapatinib treatment was more effective at reducing acini size in both DCIS cell lines. Mammosphere formation in cell lines and human primary DCIS was reduced further by DAPT/lapatinib or DAPT/gefitinib regardless of ErbB2 receptor status. Our pre-clinical human models of DCIS demonstrate that Notch and ErbB1/2 both play a role in DCIS acini growth and stem cell activity. We report for the first time that cross talk between the two pathways in DCIS occurs regardless of ErbB2 receptor status and inhibition of Notch and ErbB1/2 was more efficacious than either alone. These data provide further understanding of DCIS biology and suggest treatment strategies combining Notch and ErbB1/2 inhibitors should be investigated regardless of ErbB2 receptor status.     

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome.     

Comparison of normal and breast cancer cell lines using proteome, genome, and interactome data

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled identification of 2235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multistep search strategy was used to identify post-translational modifications, revealing several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal and cancer cell lines.     

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.     

Secretion of novel SEL1L endogenous variants is promoted by ER stress/UPR via endosomes and shed vesicles in human cancer cells

We describe here two novel endogenous variants of the human endoplasmic reticulum (ER) cargo receptor SEL1LA, designated p38 and p28. Biochemical and RNA interference studies in tumorigenic and non-tumorigenic cells indicate that p38 and p28 are N-terminal, ER-anchorless and more stable relative to the canonical transmembrane SEL1LA. P38 is expressed and constitutively secreted, with increase after ER stress, in the KMS11 myeloma line and in the breast cancer lines MCF7 and SKBr3, but not in the non-tumorigenic breast epithelial MCF10A line. P28 is detected only in the poorly differentiated SKBr3 cell line, where it is secreted after ER stress. Consistently with the presence of p38 and p28 in culture media, morphological studies of SKBr3 and KMS11 cells detect N-terminal SEL1L immunolabeling in secretory/degradative compartments and extracellularly-released membrane vesicles. Our findings suggest that the two new SEL1L variants are engaged in endosomal trafficking and secretion via vesicles, which could contribute to relieve ER stress in tumorigenic cells. P38 and p28 could therefore be relevant as diagnostic markers and/or therapeutic targets in cancer.     

Discovery of IL-18 as a novel secreted protein contributing to doxorubicin resistance by comparative secretome analysis of MCF-7 and MCF-7/Dox

Background

Resistance to chemotherapy is the major cause of failure in breast cancer treatment. Recent studies suggest that secreted proteins may play important roles in chemoresistance. We sought to systematically characterize secreted proteins associated with drug resistance, which may represent potential serum biomarkers or novel drug targets.

Methodology/Principal Findings

In the present work, we adopted the proteomic strategy of one-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry to compare the secretome of MCF-7 and doxorubicin-resistant MCF-7/Dox. A total of 2,084 proteins were identified with at least two unique peptides in the conditioned media of two cell lines. By quantification with label-free spectral counting, 89 differentially expressed secreted proteins (DESPs) between the two cell lines were found. Among them, 57 DESPs were first found to be related to doxorubicin resistance in this work, including 24 extracellular matrix related proteins, 2 cytokines and 31 unclassified proteins. We focused on 13 novel DESPs with confirmed roles in tumor metastasis. Among them, the elevated expression of IL-18 in doxorubicin-resistant cell lines and breast tumor tissues was validated and its role in doxorubicin resistance was further confirmed by cell viability experiments in the presence or absence of this protein.

Conclusions/Significance

Comparative analysis of the secretome of MCF-7 and MCF-7/Dox identified novel secreted proteins related to chemotherapy resistance. IL-18 was further validated to contribute to doxorubicin resistance, in addition to its confirmed role in breast cancer metastasis. Due to its dual roles in both drug resistance and tumor metastasis, IL-18 may represent a useful drug target for breast cancer therapy.     

Identification of proteins secreted by head and neck cancer cell lines using LC-MS/MS: Strategy for discovery of candidate serological biomarkers

In search of blood-based biomarkers that would enhance the ability to diagnose head and neck/oral squamous cell carcinoma (HNOSCC) in early stages or predict its prognosis, we analyzed the HNOSCC secretome (ensemble of proteins secreted and/or shed from the tumor cells) for potential biomarkers using proteomic technologies. LC-MS/MS was used to identify proteins in the conditioned media of four HNOSCC cell lines (SCC4, HSC2, SCC38, and AMOSIII); 140 unique proteins were identified on the basis of 5% global false discovery rate, 122 of which were secretory proteins, with 29 being previously reported to be overexpressed in HNOSCC in comparison to normal head and neck tissues. Of these, five proteins including α-enolase, peptidyl prolyl isomerase A/cyclophilin A, 14-3-3 ζ, heterogeneous ribonucleoprotein K, and 14-3-3 σ were detected in the sera of HNOSCC patients by Western blot analysis. Our study provides the evidence that analysis of head and neck cancer cells' secretome is a viable strategy for identifying candidate serological biomarkers for HNOSCC. In future, these biomarkers may be useful in predicting the likelihood of transformation of oral pre-malignant lesions, prognosis of HNOSCC patients and evaluate response to therapy using minimally invasive tests.     

Pitfalls and opportunities in the characterization of unconventionally secreted proteins by secretome analysis

Proteins are released from cells by different secretory pathways. The secretory pathway via the ER-Golgi route - realized by a signal sequence - is referred to as “classical secretion”. In contrast, alternative secretory pathways were summarized as “unconventional protein secretion”. Until now, unconventional protein secretion was lacking attention due to the absence of detailed mechanistic insight and limited experimental access. However, there is a growing number of experimental data showing that a large proportion of secreted proteins is released by these alternative routes. Secretomics - the analysis of all secreted proteins of a cell population - offers the opportunity to gain more functional insight into unconventional protein secretion. Several pitfalls in secretome analysis starting with the analyzed cell model and sample preparation to data analysis have to be considered for detailed characterization of the secretome. Here, we highlight the investigation of secretomes by quantitative LC-MS/MS analysis and discuss pitfalls and opportunities in the characterization of unconventionally secreted proteins by secretome analysis.     

In‐depth characterization of the secretome of mouse CNS cell lines by LC‐MS/MS without prefractionation

Microglia, astrocytes, and neurons, which have important functions in the central nervous system (CNS), communicate mutually to generate a signal through secreted proteins or small molecules, but many of which have not been identified. Because establishing a reference for the secreted proteins from CNS cells could be invaluable in examining cell‐to‐cell communication in the brain, we analyzed the secretome of three murine CNS cell lines without prefractionation by high‐resolution mass spectrometry. In this study, 2795 proteins were identified from conditioned media of the three cell lines, and 2125 proteins were annotated as secreted proteins by bioinformatics analysis. Further, approximately 500 secreted proteins were quantifiable as differentially expressed proteins by label‐free quantitation. As a result, our secretome references are useful datasets for the future study of neuronal diseases. All MS data have been deposited in the ProteomeXchange with identifier PXD001597 ( http://proteomecentral.proteomexchange.org/dataset/PXD001597 ).     

Proteomic profiling identifies breast tumor metastasis-associated factors in an isogenic model

A combination of LC and MS was applied to an isogenic breast tumor metastasis model to identify proteins associated with a cellular phenotype. Chromatofocusing followed by nonporous-RP-HPLC/ESI-TOF MS was applied to cell lysates of a pair of monoclonal cell lines from the human breast carcinoma cell line MDA-MB-435 that have different metastatic phenotypes in immune-compromised mice. This method was developed to separate proteins based on pI and hydrophobicity. The high resolution and mass accuracy of ESI-TOF measurements provided a good correlation of theoretical MW and experimental Mr values of intact proteins measured in mass maps obtained in the pH range 3.8-6.4. The isolated proteins were digested by trypsin and analyzed by MALDI-TOF MS, MALDI-QIT-TOF MS, and monolith-based HPLC/MS/MS. The unique combination of the techniques provided valuable information including quantitation and modification of proteins. We identified 89 selected proteins, of which 43 were confirmed as differentially expressed. Metastasis-associated proteins included galectin-1, whereas annexin I and annexin II were associated with the nonmetastatic phenotype. In this study, we demonstrate that combining a variety of MS tools with a multidimensional liquid-phase separation provides the ability to map cellular protein content, to search for modified proteins, and to correlate protein expression with cellular phenotype.     

Nek2A contributes to tumorigenic growth and possibly functions as potential therapeutic target for human breast cancer

Nek2A (NIMA-related kinases 2A) has been known as an important centrosome regulatory factor. The aim of this study was to investigate the expression of Nek2A and the role it played in different stages of breast cancer. We detected the expression of Nek2A in both mRNA and protein levels in MCF10 cell lines including MCF-10A, MCF-10DCIS.com, MCF-10CA1a and in human breast samples which contained normal breast tissue (NBT), breast ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). Our study revealed that the mRNA and protein expression of Nek2A were significantly up-regulated in MCF-10DCIS.com and MCF-10CA1a cell lines as well as in human primary breast cancer tissue (DCIS and IDC). Our study also presented a correlation between Nek2A mRNA expression and some clinic pathological factors. We found that Nek2A mRNA expression was associated with molecular subtypes, ER, PR and Ki-67 immunoreactivity (P<0.05) in DCIS and associated with histological grade, lymph node metastasis, molecular subtypes, c-erbB-2, and Ki-67 expression (P<0.05) in IDC. In addition, we observed that ectopic expression of Nek2A in "normal" immortalized MCF-10A breast epithelial cell resulted in increased Nek2A which lead to abnormal centrosomes. Furthermore, knockdown of Nek2A in MCF-10DCIS.com could remarkably inhibit cell proliferation and induce cell cycle arrest in MCF-10DCIS.com cell line. These data suggested that Nek2A might bear a close relationship with development and progression of breast carcinoma, and highlighted its role as a novel potential biomarker for diagnosis and a possible therapeutic target for human breast cancer especially for DCIS.