Purification and characterization of the mammaglobin/lipophilin B complex, a promising diagnostic marker for breast cancer

The Enigma of Mammaglobin: Redefining the Biomarker Paradigm in Breast Carcinoma

The continuous evolution of cancer biology has led to the discovery of mammaglobin, a potential novel biomarker for breast carcinoma. This review aims to unravel the enigmatic aspects of mammaglobin and elucidate its potential role in redefining the paradigm of breast carcinoma biomarkers. We will thoroughly examine its expression in tumoral and peritumoral tissues and its circulating levels in the blood, thereby providing insights into its possible function in cancer progression and metastasis. Furthermore, the potential application of mammaglobin as a non-invasive diagnostic tool and a target for personalized treatment strategies will be discussed. Given the increasing incidence of breast carcinoma worldwide, the exploration of novel biomarkers such as mammaglobin is crucial in advancing our diagnostic capabilities and treatment modalities, ultimately contributing to improved patient outcomes.

Role of glycosylation in breast cancer progression and metastasis: implications for miRNA, EMT and multidrug resistance

Breast cancer (BC) is one of the leading causes of death in women, globally. A variety of biological processes results in metastasis, a poorly understood pathological phenomenon, causing a high relapse rate. Glycosylation, microribonucleic acids (miRNAs) and epithelial to mesenchymal transition (EMT), have been shown to regulate this cascade where tumor cells detach from their primary site, enter the circulatory system and colonize distant sites. Integrated proteomics and glycomics approaches have been developed to probe the molecular mechanism regulating such metastasis. In this review, we describe specific aspects of glycosylation and its interrelation with miRNAs, EMT and multidrug resistance during BC progression and metastasis. We explore various approaches that determine the role of proteomes and glycosylation in BC diagnosis, therapy and drug discovery.

Mammaglobin-A Expression Is Highly Specific for Tumors Derived from the Breast, the Female Genital Tract, and the Salivary Gland

Human mammaglobin-A (SCGB2A2) is a secretory protein with an unknown function that is used as a diagnostic marker for breast cancer. However, other tumors can also express mammaglobin-A. To comprehensively study patterns of mammaglobin-A expression, a tissue microarray containing 16,328 samples from 128 different tumor types as well as 608 samples of 76 different normal tissue types was analyzed using immunohistochemistry. Mammaglobin-A positivity was found in only a few normal tissues, including luminal cells of the breast as well as endocervical and endometrial glands. In tumor tissues, 37 of 128 tumor categories showed mamma-globin-A staining, 32 of which were derived from one of four organs: breast (6 tumor categories), endometrium (5 tumor categories), ovary (5 tumor categories), and salivary glands (16 tumor categories). Only five additional tumor types showed occasional weak mammaglobin positivity, including medullary thyroid cancer, teratoma of the testis, squamous cell carcinoma of the skin and pharynx, and prostatic adenocarcinoma. Among 1139 evaluable invasive breast carcinomas of no special type, low mammaglobin-A immunostaining was linked to high BRE grade (p = 0.0011), loss of estrogen and progesterone receptor expression (p < 0.0001 each), and triple-negative status (p < 0.0001) but not to patient survival. In endometrial cancer, mammaglobin-A loss was linked to an advanced tumor stage (p = 0.0198). Our data characterize mammaglobin-A as a highly specific marker for tumors derived from either the breast, female genitals, or salivary gland.

Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma

Ductal carcinoma in situ (DCIS) is considered a non-invasive precursor to breast cancer, and although associated with an increased risk of developing invasive disease, many women with DCIS will never progress beyond their in situ diagnosis. The path from normal duct to invasive ductal carcinoma (IDC) is not well understood, and efforts to do so are hampered by the substantial heterogeneity that exists between patients, and even within patients. Here we show gene expression analysis from > 2,000 individually micro-dissected ductal lesions representing 145 patients. Combining all samples into one continuous trajectory we show there is a progressive loss in basal layer integrity heading towards IDC, coupled with two epithelial to mesenchymal transitions, one early and a second coinciding with the convergence of DCIS and IDC expression profiles. We identify early processes and potential biomarkers, including CAMK2N1, MNX1, ADCY5, HOXC11 and ANKRD22, whose reduced expression is associated with the progression of DCIS to invasive breast cancer.

Progression from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) remains poorly understood. Here, the authors analyse over 2700 micro-dissected samples using transcriptomics to identify genes that characterise different stages of DCIS to IDC progression, and identify IDC-associated markers within early-stage lesions.

Analysis of single-cell RNA-sequencing data identifies a hypoxic tumor subpopulation associated with poor prognosis in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of mammary carcinoma characterized by low expression levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Along with the rapid development of the single-cell RNA-sequencing (scRNA-seq) technology, the heterogeneity within the tumor microenvironment (TME) could be studied at a higher resolution level, facilitating an exploration of the mechanisms leading to poor prognosis during tumor progression. In previous studies, hypoxia was considered as an intrinsic characteristic of TME in solid tumors, which would activate downstream signaling pathways associated with angiogenesis and metastasis. Moreover, hypoxia-related genes (HRGs) based risk score models demonstrated nice performance in predicting the prognosis of TNBC patients. However, it is essential to further investigate the heterogeneity within hypoxic TME, such as intercellular communications. In the present study, utilizing single-sample Gene Set Enrichment Analysis (ssGSEA) and cell-cell communication analysis on the scRNA-seq data retrieved from Gene Expression Omnibus (GEO) database with accession number GSM4476488, we identified four tumor subpopulations with diverse functions, particularly a hypoxia-related one. Furthermore, results of cell-cell communication analysis revealed the dominant role of the hypoxic tumor subpopulation in angiogenesis- and metastasis-related signaling pathways as a signal sender. Consequently, regard the TNBC cohorts acquired from The Cancer Genome Atlas (TCGA) and GEO as train set and test set respectively, we constructed a risk score model with reliable capacity for the prediction of overall survival (OS), where ARTN and L1CAM were identified as risk factors promoting angiogenesis and metastasis of tumors. The expression of ARTN and L1CAM were further analyzed through tumor immune estimation resource (TIMER) platform. In conclusion, these two marker genes of the hypoxic tumor subpopulation played vital roles in tumor development, indicating poor prognosis in TNBC patients.

A Network-Based Comparison Between Molecular Apocrine Breast Cancer Tumor and Basal and Luminal Tumors by Joint Graphical Lasso

Joint graphical lasso (JGL) approach is a Gaussian graphical model to estimate multiple graphical models corresponding to distinct but related groups. Molecular apocrine (MA) breast cancer tumor has similar characteristics to luminal and basal subtypes. Due to the relationship between MA tumor and two other subtypes, this paper investigates the similarities and differences between the MA genes association network and the ones corresponding to other tumors by taking advantageous of JGL properties. Two distinct JGL graphical models are applied to two sub-datasets including the gene expression information of the MA and the luminal tumors and also the MA and the basal tumors. Then, topological comparisons between the networks such as finding the shared edges are applied. In addition, several support vector machine (SVM) classification models are performed to assess the discriminating power of some critical nodes in the networks, like hub nodes, to discriminate the tumors sample. Applying the JGL approach prepares an appropriate tool to observe the networks of the MA tumor and other subtypes in one map. The results obtained by comparing the networks could be helpful to generate new insight about MA tumor for future studies.

Vascular syndromes in liver cirrhosis

Liver cirrhosis is associated with multiple vascular syndromes affecting almost all body systems. Many of these syndromes are directly related to impaired liver function and sometimes reversible after liver transplantation while others arise secondary to portal hypertension and ascites. Altered expression of angiogenic and vasoactive compounds (most importantly nitric oxide), endothelial dysfunction, dysregulated neurohormonal control, and systemic inflammatory state play differential roles in mediating homeostatic instability and abnormal vasogenic response. Important vascular features encountered in liver disease include portal hypertension, splanchnic overflow, abnormal angiogenesis and shunts, portopulmonary syndrome, hepatopulmonary syndrome, and systemic hyperdynamic circulation. Redistribution of effective circulatory volume deviating from vital organs and pooling in splanchnic circulation is also encountered in liver patients which may lead to devastating outcomes as hepatorenal syndrome. Etiologically, vascular syndromes are not isolated phenomena and vascular dysfunction in one system may lead to the development of another in a different system. This review focuses on understanding the pathophysiological factors underlying vascular syndromes related to chronic liver disease and the potential links among them. Many of these syndromes are associated with high mortality, thus it is crucial to look for early biomarkers for these syndromes and develop novel preventive and therapeutic strategies.

The Need for Review and Understanding of SELDI/MALDI Mass Spectroscopy Data Prior to Analysis

Multiple studies have reported that surface enhanced laser desorption/ionization time of flight mass spectroscopy (SELDI-TOF-MS) is useful in the early detection of disease based on the analysis of bodily fluids. Use of any multiplex mass spectroscopy based approach as in the analysis of bodily fluids to detect disease must be analyzed with great care due to the susceptibility of multiplex and mass spectroscopy methods to biases introduced via experimental design, patient samples, and/or methodology. Specific biases include those related to experimental design, patients, samples, protein chips, chip reader and spectral analysis. Contributions to biases based on patients include demographics (e.g., age, race, ethnicity, sex), homeostasis (e.g., fasting, medications, stress, time of sampling), and site of analysis (hospital, clinic, other). Biases in samples include conditions of sampling (type of sample container, time of processing, time to storage), conditions of storage, (time and temperature of storage), and prior sample manipulation (freeze thaw cycles). Also, there are many potential biases in methodology which can be avoided by careful experimental design including ensuring that cases and controls are analyzed randomly. All the above forms of biases affect any system based on analyzing multiple analytes and especially all mass spectroscopy based methods, not just SELDI-TOF-MS. Also, all current mass spectroscopy systems have relatively low sensitivity compared with immunoassays (e.g., ELISA). There are several problems which may be unique to the SELDI-TOF-MS system marketed by Ciphergen®. Of these, the most important is a relatively low resolution (±0.2%) of the bundled mass spectrometer which may cause problems with analysis of data. Foremost, this low resolution results in difficulties in determining what constitutes a “peak” if a peak matching approach is used in analysis. Also, once peaks are selected, the peaks may represent multiple proteins. In addition, because peaks may vary slightly in location due to instrumental drift, long term identification of the same peaks may prove to be a challenge. Finally, the Ciphergen® system has some “noise” of the baseline which results from the accumulation of charge in the detector system. Thus, we must be very aware of the factors that may affect the use of proteomics in the early detection of disease, in determining aggressive subsets of cancers, in risk assessment and in monitoring the effectiveness of novel therapies.

Proteomics for breast cancer urine biomarkers

Although the survival of breast cancer (BC) patients has increased over the last two decades due to improved screening programs and postoperative adjuvant systemic therapies, many patients die from metastatic relapse. Current biomarkers used in the clinic are not useful for the early detection of BC, or monitoring its progression, and have limited value in predicting response to treatment. The development of proteomic techniques has sparked new searches for novel protein markers for many diseases including BC. Proteomic techniques allow for a high-throughput analysis of samples with the visualization and quantification of thousands of potential protein and peptide markers. Human urine is one of the most interesting and useful biofluids for routine testing and provides an excellent resource for the discovery of novel biomarkers, with the advantage over tissue biopsy samples due to the ease and less invasive nature of collection. In this review, we summarize the results from studies where urine was used as a source for BC biomarker research and discuss urine sample preparation, its advantage, challenges, and limitation. We focus on the gel-based proteomic approaches as well as the recent development of quantitative techniques in BC urine biomarker detection. Finally, the future use of modern proteomic techniques in BC biomarker identification will be discussed.

Upregulation of human mammaglobin reduces migration and invasion of breast cancer cells

Little is known about the biological role of human mammaglobin (hMAM) that is considered as a promising marker for breast cancer. Here, we investigated hMAM's role related to migration and invasion of human breast cancer cells (hBCC). Compared to normal cells, hBCC have high MAM mRNA expression levels. Of the hBCC tested, MAM mRNA expression levels were higher in noninvasive than in invasive cells. Overexpression of hMAM in breast cancer cells decreased migration and invasion, whereas knockdown of hMAM increased both. Taken together, these results suggest that metastasis of hBCC could be controlled by hMAM expression levels.

Secretoglobin expression in ovarian carcinoma: lipophilin B gene upregulation as an independent marker of better prognosis

BACKGROUND

The aim of the present study was to investigate within ovarian carcinoma and normal ovarian biopsies the gene expression of multiple secretoglobin family members relative to mammaglobin B, which we previously reported as a promising novel ovarian carcinoma prognostic marker.

METHODS

Using quantitative real-time Reverse Transcription PCR we tested 53 ovarian carcinoma and 30 normal ovaries for the expression of 8 genes belonging to the secretoglobin family: mammaglobin A, lipophilin A, lipophilin B, uteroglobin, HIN-1, UGRP-1, RYD5 and IIS. Next, we decided to expand the LipB gene expression analysis to a further 48 ovarian carcinoma samples, for a total of 101 tumor tissues of various histologies and to study its protein expression by immunohistochemistry in formalin-fixed paraffin-embedded tumors and normal ovaries. Finally, we correlated lipophilin B gene and protein expression to conventional patient clinico-pathological features and outcome.

RESULTS

We found significant mammaglobin A, lipophilin A, lipophilin B and RYD5 gene overexpression in ovarian carcinomas compared to normal ovaries. Lipophilin B mRNA showed a higher presence in tumors (75.4%) compared to normal ovaries (16.6%) and the most significant correlation with mammaglobin B mRNA (rs =0.77, p < 0.001). By immunohistochemical analysis, we showed higher lipophilin B expression in the cytoplasm of tumor cells compared to normal ovaries (p < 0.001). Moreover, lipophilin B gene overexpression was significantly associated with serous histology (serous vs clear cell p = 0.027; serous vs undifferentiated p = 0.007) and lower tumor grade (p = 0.02). Lower LipB mRNA levels (low versus high tertiles) were associated to a shorter progression-free (p = 0.03, HR = 2.2) and disease-free survival (p = 0.02, HR = 2.5) by univariate survival analysis and, importantly, they remain an independent prognostic marker for decreased disease-free (p = 0.001, HR = 3.9) and progression-free survival (p = 0.004, HR = 2.8) in multivariate Cox regression analysis.

CONCLUSIONS

The present study represents the first quantitative evaluation of secretoglobin gene expression in normal and neoplastic ovarian tissues. Our results demonstrate lipophilin B gene and protein upregulation in ovarian carcinoma compared to normal ovary. Moreover, lipophilin B gene overexpression correlates with a less aggressive tumor phenotype and represents a novel ovarian carcinoma prognostic factor.

Systematic identification and characterization of novel human skin-associated genes encoding membrane and secreted proteins

Through bioinformatics analyses of a human gene expression database representing 105 different tissues and cell types, we identified 687 skin-associated genes that are selectively and highly expressed in human skin. Over 50 of these represent uncharacterized genes not previously associated with skin and include a subset that encode novel secreted and plasma membrane proteins. The high levels of skin-associated expression for eight of these novel therapeutic target genes were confirmed by semi-quantitative real time PCR, western blot and immunohistochemical analyses of normal skin and skin-derived cell lines. Four of these are expressed specifically by epidermal keratinocytes; two that encode G-protein-coupled receptors (GPR87 and GPR115), and two that encode secreted proteins (WFDC5 and SERPINB7). Further analyses using cytokine-activated and terminally differentiated human primary keratinocytes or a panel of common inflammatory, autoimmune or malignant skin diseases revealed distinct patterns of regulation as well as disease associations that point to important roles in cutaneous homeostasis and disease. Some of these novel uncharacterized skin genes may represent potential biomarkers or drug targets for the development of future diagnostics or therapeutics.

Mammaglobin peptide as a novel biomarker for breast cancer detection

Among the different types of tests used for cancer diagnosis, molecular tests have been increrasingly incorporated because of their ability to detect either expression or functional changes in the molecules associated with the disease. Mammaglobin is a protein found in mammary tissue and can be detected in serum. This protein has been proposed as a biomarker to diagnose breast cancer, given that patients exhibit an increased amount of the protein in serum and tumor tissue, in comparison to healthy individuals. The ELISA test was used in the present study to detect mammaglobin in blood samples from 51 breast cancer patients and 51 control individuals. Antibodies against mamaglobin were generated in rabbits by using the following synthetic peptides: A (amino acids 13 to 21), B (amino acids 31 to 39), C (amino acids 56 to 64) and a D peptide, corresponding to the protein isoform without three amino acids (59, 60 and 61 amino acids) from peptide C. All peptides were immunogenic and allowed generation of antibodies that were able to discriminate patients from controls. The best results were obtained for antiserum B, achieving the best sensitivity (86.3%) and specificity (96%).

Autoantibodies to tumor-associated antigens in breast carcinoma

Autoantibodies (AAbs) to tumor-associated antigens (TAAs) have been identified in the circulation of patients with cancer. This paper will focus on recent knowledge related to circulating AAbs to TAAs in breast carcinoma. So far, the following TAAs have been identified to elicit circulating AAbs in breast carcinoma: p53, MUC-1, heat shock proteins (HSP-27, HSP-60, and HSP-90), HER2/neu/c-erb B2, GIPC-1, c-myc, c-myb, cancer-testis antigens (NY-ESO-1), BRCA1, BRCA2, endostatin, lipophilin B, cyclin B1, cyclin D1, fibulin, insulin-like growth factor binding protein 2 (IGFBP-2), topoisomerase II alpha (TOPO2α), and cathepsin D. Measurement of serum AAbs to one specific TAA only is of little value for screening and early diagnosis of breast carcinoma; however, assessment of AAbs to a panel of TAAs may have promising diagnostic potential.

Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data

Background

Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduction and classification are considerable challenges in statistical machine learning. We therefore propose a novel approach for dimensionality reduction and tested it using published high-resolution SELDI-TOF data for ovarian cancer.

Results

We propose a method based on statistical moments to reduce feature dimensions. After refining and t-testing, SELDI-TOF data are divided into several intervals. Four statistical moments (mean, variance, skewness and kurtosis) are calculated for each interval and are used as representative variables. The high dimensionality of the data can thus be rapidly reduced. To improve efficiency and classification performance, the data are further used in kernel PLS models. The method achieved average sensitivity of 0.9950, specificity of 0.9916, accuracy of 0.9935 and a correlation coefficient of 0.9869 for 100 five-fold cross validations. Furthermore, only one control was misclassified in leave-one-out cross validation.

Conclusion

The proposed method is suitable for analyzing high-throughput proteomics data.

Increased expression of histone proteins during estrogen-mediated cell proliferation

BACKGROUND

There is concern about the potential risk posed by compounds with estrogen-like activity present in the environment. As previous studies have shown that combined exposure to such compounds results in dose additivity, it should be possible to assess estrogen exposure with suitable biomarkers of effect.

OBJECTIVES

Our goal was to identify candidate protein biomarkers of effect for estrogenic compounds.

METHODS

In the search for biomarkers, we assessed the effect of several estrogenic compounds on the expression profile of proteins in breast-derived cell lines varying in their estrogen receptor (ER) phenotype using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. We identified responsive proteins, after separating them by SDS-polyacrylamide gel electrophoresis, and analyzing the trypsin-digested proteins by tandem mass spectrometry.

RESULTS

The estrogenic compounds 17beta-estradiol, genistein, bisphenol A, and endosulfan produced similar protein profile changes in MCF-7 cells (phenotype: ERalpha(+)/ERbeta(+)), but had no effect on MDA-MB-231 (ERalpha(-)/ERbeta(+)), MCF-10F (ERalpha(-)/ERbeta(+)), or MCF-10A (ERalpha(-)/ERbeta(-)) cells. The most responsive proteins in MCF-7 cells were identified as histones H2A, H2B, H3, and H4. Histone levels were not increased in cell lines that showed no proliferative response to estrogens despite their rapid intrinsic growth rate in culture.

CONCLUSION

Our results indicate that ER-mediated cell proliferation results in up-regulation of core histone proteins.

Mammaglobin as a potential molecular target for breast cancer drug delivery

BACKGROUND

Mammaglobin (MAM) has been used as a specific molecular marker for breast cancer diagnosis. Recently, several groups of researchers proposed a number of therapeutic strategies targeting this molecule. Some of the strategies are based upon an essential but not demonstrated hypothesis - mammaglobin is associated with the surface of breast cancer cells, which strongly disputes the therapeutic strategies.

RESULTS

We conducted a computer-based predictive analysis and identified a small fragment at the N-end of MAM as a potential transmembrane domain. We provided several evidences to demonstrate the presence of the membrane-associated MAM. We isolated the membrane protein components from known MAM positive breast cancer cells (MDA-MB361 and MDA-MB415). We showed that about 22-64% of MAM proteins, depending upon the types of the cancer cells, directly attached on the membrane of breast cancer cells, by Western blotting assays. To directly visualize the presence of the membrane-bound MAM protein, we incubated the MAM positive cancer cells with FITC labeled anti-MAM antibody, and observed clear fluorescent signals on the surface of the cells. In studying the MAM protein distribution in human breast cancer tissues, we first identified two immunostain patterns that are associated with the membrane-bound MAM: the membrane stain pattern and luminary surface stain pattern. To test whether the membrane-associated MAM can serve as a molecular target for drug delivery, we conjugated anti-MAM antibody to human low-density lipoprotein (LDL) and loaded doxorubicin (Dox) in the core of LDL. Specific binding and cytotoxicity of the MAM targeted and Dox loaded LDL was tested in the MAM positive breast cancer cells in vitro.

CONCLUSION

We first showed that some of MAM protein directly associated with the surface of breast cancer cells. The membrane-associated MAM protein may be utilized as a useful molecular marker for breast cancer targeted drug delivery.

Practical approaches to proteomic biomarkers within prostate cancer radiotherapy trials

INTRODUCTION

Proteomic biomarkers may be useful for monitoring therapeutic response and to triage cancer patients to best therapy.

OBJECTIVES

In this review, we highlight the importance of specimen acquisition, preparation and analysis in radiotherapy proteomic studies. We also discuss practical approaches for the design and execution of clinical proteomic studies using our recent experience based on specimens accrued during prostate cancer radiation therapy.

DISCUSSION AND CONCLUSIONS

Numerous proteomic methods are being employed, including high-throughput mass spectrometry and immunoassays, and using solid tissues, blood and urine for analysis. Given the potential complexity of cytokine and other protein responses, there is a need to assess proteomic signatures within serial samples as longitudinal studies during a course of fractionated radiotherapy (RT).

Implications of applied research for prognosis and therapy of breast cancer

Breast cancer is the one of leading causes of cancer-related deaths in women within economically developed regions of the world. The heterogeneity of the natural history of breast cancer complicates patient management in that there is tremendous variability in response to treatment and for survival. More recently, several biomarkers (hormone receptor status and HER2 expression) have been added to the risk evaluation and therapeutic assessments. Evolving knowledge of molecular biology and newer techniques, such as genomics and proteomics, offer the potential to better define the biologic nature of the disease process, both for risk and therapy. This review discusses classical as well as new prognostic and predictive techniques. These are leading to a paradigm shift from empirical treatment to an individually tailored approach, which may soon become a realistic option for patients, based on specific molecular profiles.

Overexpression of mammaglobin B in epithelial ovarian carcinomas

OBJECTIVE

Mammaglobin B is a uteroglobin gene family member recently found highly differentially expressed in serous papillary ovarian cancer by gene expression profiling. In order to evaluate its potential as a novel ovarian cancer biomarker, in this study we quantified and compared Mammaglobin B expression in various histologic types of epithelial ovarian carcinomas (EOC).

METHODS

Mammaglobin B expression was evaluated by real-time PCR and/or immunohistochemistry in fresh-frozen biopsies and paraffin-embedded tissues derived from a total of 137 patients including 69 primary EOC with different histologies, 28 serous papillary omental metastasis, 8 borderline tumors, 26 benign cystadenomas and 14 normal ovaries.

RESULTS

High levels of Mammaglobin B gene expression were detected in 100% (68 out of 68) of the ovarian cancer biopsies tested by real-time PCR. In contrast, normal human ovarian surface epithelium (HOSE) expressed negligible levels of Mammaglobin B mRNA (EOC versus HOSE, p<0.01). Although Mammaglobin B gene expression levels were higher in endometrioid, mucinous and undifferentiated tumors when compared to serous papillary tumors, clear cell tumors and those with mixed histology, these differences were not statistically significant. In agreement with real-time PCR results, EOC were found to express significantly higher levels of Mammaglobin B protein when compared to normal ovaries and benign cystadenomas (p<0.01). However, only 29 out of 68 (42%) of the EOC samples found positive for Mammaglobin B by real-time PCR showed immunoreactivity by IHC.

CONCLUSIONS

Mammaglobin B gene is highly expressed in EOC and may represent a novel molecular marker for multiple histological types of ovarian cancer. Additional studies to evaluate the clinical utility of Mammaglobin B as a diagnostic and/or therapeutic target in ovarian cancer are warranted.

CENP-F expression is associated with poor prognosis and chromosomal instability in patients with primary breast cancer

DNA microarrays have the potential to classify tumors according to their transcriptome. Tissue microarrays (TMAs) facilitate the validation of biomarkers by offering a high-throughput approach to sample analysis. We reanalyzed a high profile breast cancer DNA microarray dataset containing 96 tumor samples using a powerful statistical approach, between group analyses. Among the genes we identified was centromere protein-F (CENP-F), a gene associated with poor prognosis. In a published follow-up breast cancer DNA microarray study, comprising 295 tumour samples, we found that CENP-F upregulation was significantly associated with worse overall survival (p<0.001) and reduced metastasis-free survival (p<0.001). To validate and expand upon these findings, we used 2 independent breast cancer patient cohorts represented on TMAs. CENP-F protein expression was evaluated by immunohistochemistry in 91 primary breast cancer samples from cohort I and 289 samples from cohort II. CENP-F correlated with markers of aggressive tumor behavior including ER negativity and high tumor grade. In cohort I, CENP-F was significantly associated with markers of CIN including cyclin E, increased telomerase activity, c-Myc amplification and aneuploidy. In cohort II, CENP-F correlated with VEGFR2, phosphorylated Ets-2 and Ki67, and in multivariate analysis, was an independent predictor of worse breast cancer-specific survival (p=0.036) and overall survival (p=0.040). In conclusion, we identified CENP-F as a biomarker associated with poor outcome in breast cancer and showed several novel associations of biological significance.

Lipophilin B: A gene preferentially expressed in breast tissue and upregulated in breast cancer

Lipophilin B (LPB), which is also known as BU101, is a secretoglobin which exists in vivo as a complex with the mammary-specific protein, mammaglobin A (MGA). The aim of our study was to investigate the expression of LPB in a panel of breast and nonbreast tissues and compare its expression with that of MGA. Using RT-PCR, LPB mRNA was detected in 16/25 (64%) of normal breast specimens, 23/30 (77%) of fibroadenomas, 102/156 (65%) of primary breast cancers and in 8/36 (22%) nonbreast tissues. Levels of expression of LPB mRNA were significantly higher in breast cancers compared to both normal breast tissues (p = 0.02) and nonbreast tissue (p < 0.001). In the primary breast cancers, expression of LPB mRNA was positively correlated with the estrogen receptor (p = 0.045) but inversely related to both tumor grade (p < 0.001) and proliferation rates (p = 0.0345). Compared to MGA, expression of LPB was more sensitive but less specific for breast cancer. Using Western blotting, LPB migrated with an approximate molecular mass of 7-8 kDa, the expected molecular mass of free LPB. Immunohistochemical analysis of breast cancers showed that LPB expression was predominantly confined to the cytoplasm of tumor cells. We conclude that expression of LPB is preferentially but not exclusively restricted to breast tissue. Since LPB was expressed relatively specifically in breast tissue and was significantly upregulated in breast carcinomas, it is a promising candidate biomarker for breast cancer.

Molecular biomarkers for cancer detection in blood and bodily fluids

Cancer is a major and increasing public health problem worldwide. Traditionally, the diagnosis and staging of cancer, as well as the evaluation of response to therapy have been primarily based on morphology, with relatively few cancer biomarkers currently in use. Conventional biomarker studies have been focused on single genes or discrete pathways, but this approach has had limited success because of the complex and heterogeneous nature of many cancers. The completion of the human genome project and the development of new technologies have greatly facilitated the identification of biomarkers for assessment of cancer risk, early detection of primary cancers, monitoring cancer treatment, and detection of recurrence. This article reviews the various approaches used for development of such markers and describes markers of potential clinical interest in major types of cancer. Finally, we discuss the reasons why so few cancer biomarkers are currently available for clinical use.

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry serum protein profiling to identify nasopharyngeal carcinoma

BACKGROUND

Diagnosis of nasopharyngeal carcinoma (NPC) at an early disease stage is important for successful treatment and improving the outcome of patients. The use of serum protein profiles and a classification tree algorithm were explored to distinguish NPC from noncancer.

METHODS

Serum samples were applied to metal affinity protein chips to generate mass spectra by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Protein peak identification and clustering were performed using the Biomarker Wizard software. Proteomic spectra of serum samples from 50 NPC patients and 54 noncancer controls were used as a training set and a classification tree with 6 distinct protein masses was generated by using Biomarker Pattern software. The validity of the classification tree was then challenged with a blind test set including another 20 NPC patients and 25 noncancer controls.

RESULTS

The software identified an average of 93 mass peaks/spectrum and 6 of the identified peaks were used to construct the classification tree. The classification tree correctly determined 83% (123 of 149) of the test samples with 83% (58 of 70) of the NPC samples and 82% (65 of 79) of the noncancer samples. In a combination of the serum protein profiles with Epstein-Barr (EBV) nuclear antigen 1 (EBNA1 IgA) test, the diagnostic sensitivity and specificity were increased to 99% and 96%, respectively.

CONCLUSIONS

The results suggest that SELDI-TOF-MS serum protein profiles could discriminate NPC from noncancer. The combination of serum protein profiles with an EBV antibody serology test could further improve the accuracy of NPC screening.

Expression analysis of mammaglobin A (SCGB2A2) and lipophilin B (SCGB1D2) in more than 300 human tumors and matching normal tissues reveals their co-expression in gynecologic malignancies

Background

Mammaglobin A (SCGB2A2) and lipophilin B (SCGB1D2), two members of the secretoglobin superfamily, are known to be co-expressed in breast cancer, where their proteins form a covalent complex. Based on the relatively high tissue-specific expression pattern, it has been proposed that the mammaglobin A protein and/or its complex with lipophilin B could be used in breast cancer diagnosis and treatment. In view of these clinical implications, the aim of the present study was to analyze the expression of both genes in a large panel of human solid tumors (n = 309), corresponding normal tissues (n = 309) and cell lines (n = 11), in order to evaluate their tissue specific expression and co-expression pattern.

Methods

For gene and protein expression analyses, northern blot, dot blot hybridization of matched tumor/normal arrays (cancer profiling arrays), quantitative RT-PCR, non-radioisotopic RNA in situ hybridization and immunohistochemistry were used.

Results

Cancer profiling array data demonstrated that mammaglobin A and lipophilin B expression is not restricted to normal and malignant breast tissue. Both genes were abundantly expressed in tumors of the female genital tract, i.e. endometrial, ovarian and cervical cancer. In these four tissues the expression pattern of mammaglobin A and lipophilin B was highly concordant, with both genes being down-, up- or not regulated in the same tissue samples. In breast tissue, mammaglobin A expression was down-regulated in 49% and up-regulated in 12% of breast tumor specimens compared with matching normal tissues, while lipophilin B was down-regulated in 59% and up-regulated in 3% of cases. In endometrial tissue, expression of mammaglobin A and lipophilin B was clearly up-regulated in tumors (47% and 49% respectively). Both genes exhibited down-regulation in 22% of endometrial tumors. The only exceptions to this concordance of mammaglobin A/lipophilin B expression were normal and malignant tissues of prostate and kidney, where only lipophilin B was abundantly expressed and mammaglobin A was entirely absent. RNA in situ hybridization and immunohistochemistry confirmed expression of mammaglobin A on a cellular level in endometrial and cervical cancer and their corresponding normal tissues.

Conclusion

Altogether, these data suggest that expression of mammaglobin A and lipophilin B might be controlled in different tissues by the same regulatory transcriptional mechanisms. Diagnostic assays based on mammaglobin A expression and/or the mammaglobin A/lipophilin B complex appear to be less specific for breast cancer, but with a broader spectrum of potential applications, which includes gynecologic malignancies.

The emerging importance of DNA mapping and other comprehensive screening techniques, as tools to identify new drug targets and as a means of (cancer) therapy personalisation

Every human being is genetically unique and this individuality is not only marked by morphologic and physical characteristics but also by an individual's response to a particular drug. Single nucleotide polymorphisms (SNPs) are largely responsible for one's individuality. A drug may be ineffective in one patient, whereas the exact same drug may cure another patient. Recent advances in DNA mapping and other screening technologies have provided researchers and drug developers with crucial information needed to create drugs that are specific for a given individual. In the future, physicians will be able to prescribe individualised drugs adjusted to, for example, activities of specific enzymatic pathways that would either be targeted by these drugs, or would be responsible for drug conversion or inactivation. Furthermore, the mapping of the human genome allows broader development and application of drugs that act on the level of gene transcription rather than as simple biochemical inhibitors or activators of certain enzymes. Such new approaches will maximise desired therapeutic results and may completely eliminate severe side effects. To illustrate the potential of genetic translational research, the authors discuss available analytical methodologies such as; gene arrays, flow cytometry-based screening for SNPs, proteomics, metabolomics, real-time PCR, and other methods capable of detecting both SNPs, as well as more profound changes in cell metabolism. Finally, the authors provide several examples that focus mostly on targeting protein-DNA interactions, but also other processes.

Proteomic analysis of nipple aspirate fluid from women with early-stage breast cancer using isotope-coded affinity tags and tandem mass spectrometry reveals differential expression of vitamin D binding protein

Background

Isotope-coded affinity tag (ICAT) tandem mass spectrometry (MS) allows for qualitative and quantitative analysis of paired protein samples. We sought to determine whether ICAT technology could quantify and identify differential expression of tumor-specific proteins in nipple aspirate fluid (NAF) from the tumor-bearing and contralateral disease-free breasts of patients with unilateral early-stage breast cancer.

Methods

Paired NAF samples from 18 women with stage I or II unilateral invasive breast carcinoma and 4 healthy volunteers were analyzed using ICAT labeling, sodium dodecyl sulfate-polyacrylamide gel (SDS-PAGE), liquid chromatography, and MS. Proteins were identified by sequence database analysis. Western blot analysis of NAF from an independent sample set from 12 women (8 with early-stage breast cancer and 4 healthy volunteers) was also performed.

Results

353 peptides were identified from tandem mass spectra and matched to peptide sequences in the National Center for Biotechnology Information database. Equal numbers of peptides were up- versus down-regulated. Alpha2HS-glycoprotein [Heavy:Light (H:L) ratio 0.63] was underexpressed in NAF from tumor-bearing breasts, while lipophilin B (H:L ratio 1.42), beta-globin (H:L ratio 1.98), hemopexin (H:L ratio 1.73), and vitamin D-binding protein precursor (H:L ratio 1.82) were overexpressed. Western blot analysis of pooled samples of NAF from healthy volunteers versus NAF from women with breast cancer confirmed the overexpression of vitamin D-binding protein in tumor-bearing breasts.

Conclusion

ICAT tandem MS was able to identify and quantify differences in specific protein expression between NAF samples from tumor-bearing and disease-free breasts. Proteomic screening techniques using ICAT and NAF may be used to find markers for diagnosis of breast cancer.

SELDI-TOF-MS proteomics of breast cancer

The detection, diagnosis, and management of breast cancer rely on an integrated approach using clinical history, physical examination, imaging, and histopathology. The discovery and validation of novel biomarkers will aid the physician in more effectively achieving this integration. This review discusses efforts in surface-enhanced laser desorption/ionization (SELDI)-based proteomics to address various clinical questions surrounding breast cancer, including diagnosis, monitoring, and stratification for treatment. Emphasis is placed on examining how study design and execution influence the discovery and validation process, which is critical to the proper development of potential clinical tests.

Lycopene

Oxidative stress is now recognized as an important etiological factor in the causation of several chronic diseases including cancer, cardiovascular diseases, osteoporosis, and diabetes. Antioxidants play an important role in mitigating the damaging effects of oxidative stress on cells. Lycopene, a carotenoid antioxidant, has received considerable scientific interest in recent years. Epidemiological, tissue culture, and animal studies provide convincing evidence supporting the role of lycopene in the prevention of chronic diseases. Human intervention studies are now being conducted to validate epidemiological observations and to understand the mechanisms of action of lycopene in disease prevention. To obtain a better understanding of the role of lycopene in human health, this chapter reviews the most recent information pertaining to its chemistry, bioavailability, metabolism, role in the prevention of prostate cancer and cancer of other target organs, its role in cardiovascular diseases, osteoporosis, hypertension, and male infertility. A discussion of the most relevant molecular markers of cancer is also included as a guide to future researchers in this area. The chapter concludes by reviewing global intake levels of lycopene, suggested levels of intake, and future research directions.

Identification of mammaglobin as a novel serum marker for breast cancer

PURPOSE

Early detection of breast cancer has implications for the management and treatment of patients with this disease. Currently, there exist no highly sensitive and specific serologic biomarkers for detection of breast cancer. Mammaglobin is predicted to be a secreted protein, and expression of this gene seems to be highly specific in breast cancer. The present studies were undertaken to develop the mammaglobin protein as a serum biomarker for detection of breast cancer.

EXPERIMENTAL DESIGN

We characterized the mammaglobin protein as a secreted, 14- to 21-kDa species, which is likely post-translationally processed based on its predicted 7-kDa size. Immunostaining for mammaglobin was conducted. An ELISA was developed for the detection of the mammaglobin protein in serum, and levels were compared between women with and without breast cancer. A receiver operating characteristic curve was used to show sensitivity and specificity for cut points on the continuous mammaglobin scale.

RESULTS

The protein was detectable by immunostaining in 72% of breast tumors and not in other tumor types. The ELISA was highly sensitive and specific for detection of mammaglobin protein in tissue culture fluids of breast cancer cells and sera of breast cancer patients. The ELISA differentiated healthy women from those with breast cancer with accurate, repeatable results across time and under varying storage conditions.

CONCLUSION

Our results indicate that mammaglobin, as measured by the ELISA, holds significant promise for breast cancer screening with the realistic potential to impact management of this disease.

SELDI-TOF mass spectrometry for cancer biomarker discovery and serum proteomic diagnostics

Proteomics is more than the identification of proteins that are altered in expression as a consequence of disease. Among the tools critical for the detection, treatment and monitoring of disease are biomarkers. The necessity for new methods to identify and validate biomarkers is underscored by the increased survival of patients diagnosed at early stages of cancer. Serum proteomic pattern diagnostics is a new technique in which proteomic signatures are used as a diagnostic classifier. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry has shown promise as a modality for biomarker discovery of early-stage cancers. Mass spectrometry-derived protein signatures have been modeled and are now moving into validation. Further sequencing of these key features can lead to new insights into disease etiology and intervention.

PEA3, AP-1, and a unique repetitive sequence all are involved in transcriptional regulation of the breast cancer-associated gene, mammaglobin

The breast cancer-associated gene mammaglobin is a member of the secretoglobin protein family and has demonstrated its utility as a breast cancer marker. However, the transcriptional regulation of mammaglobin has not been well-characterized. In this report, we used luciferase reporter assays to identify the 200 bp directly 5' of the transcriptional start site as the minimal promoter region of mammaglobin. Sequence scanning indicated that two PEA3 transcription sites were possibly involved in mammaglobin transcription. By transfecting a PEA3 expression vector into breast cancer cell lines MDA-MB-415 and MCF-7, we determined that exogenous PEA3 was able to drive transcription. Mutational analysis indicated that each PEA3 site was functional. Our reporter system and electrophorectic mobility shift assays (EMSAs) also identified the involvement of a unique repetitive element in mammaglobin transcription. Finally, AP-1 was determined via luciferase assays to be involved in regulating non-PEA3 dependent transcription. Elucidating these cis-acting elements will impact our understanding of transcription of normal breast and breast cancer-associated genes.

Proteomic analysis for the early detection and rational treatment of cancer--realistic hope?

Proteomics is an emerging field in medical science focused on the library of proteins specific to a given biosystem, the proteome, and understanding relationships therein. This field incorporates technologies that can be applied to serum and tissue in order to extract important biological information to aid clinicians and scientists in understanding the dynamic biology of their system of interest, such as a patient with cancer. These tools include laser capture microdissection, tissue lysate arrays and mass spectrometry approaches. These new technologies are more potent coupled with advanced bioinformatics analysis. They are used to characterize the content of, and changes in, the proteome induced by physiological changes, benign and pathologic. The application of these tools has assisted in the discovery of new biomarkers and may lead to new diagnostic tests and improvements in therapeutics. These tools additionally can provide a molecular characterization of cancers, which may allow for individualized molecular therapy. Understanding the basic concepts and tools used will illustrate how best to apply these technologies for patient benefit for the early detection of cancer and improved patient care.

Functionally distinct polymorphic sequences in the human genome that are targets for p53 transactivation

The p53 tumor suppressor protein is a master regulatory transcription factor that coordinates cellular responses to DNA damage and cellular stress. Besides mutations in p53, or in proteins involved in the p53 response pathway, genetic variation in promoter response elements (REs) of p53 target genes is expected to alter biological responses to stress. To identify SNPs in p53 REs that may modify p53-controlled gene expression, we developed an approach that combines a custom bioinformatics search to identify candidate SNPs with functional yeast and mammalian cell assays to assess their effect on p53 transactivation. Among approximately 2 million human SNPs, we identified >200 that seem to disrupt functional p53 REs. Eight of these SNPs were evaluated in functional assays to determine both the activity of the putative RE and the impact of the candidate SNPs on transactivation. All eight candidate REs were functional, and in every case the SNP pair exhibited differential transactivation capacities. Additionally, six of the eight genes adjacent to these SNPs are induced by genotoxic stress or are activated directly by transfection with p53 cDNA. Thus, this strategy efficiently identifies SNPs that may differentially affect gene expression responses in the p53 regulatory pathway.

Mammaglobin a in breast cancer: existence of multiple molecular forms

Existing serum-based markers for breast cancer all lack organ specificity. Mammaglobin A (MGA) is a 93 amino acid protein expressed almost exclusively in breast tissue. The aim of our study was to investigate the different forms of MGA protein in fibroadenomas and breast carcinomas. MGA protein was measured by Western blotting in 132 breast cancers, 29 fibroadenomas and 14 nonbreast tissues. MGA protein in breast tissue was found to exist in 2 main forms. These forms migrated with approximate molecular masses of 18 and 25 kDa. Both forms of MGA were detected more frequently in breast carcinomas compared to fibroadenomas. The high molecular weight form of MGA but not the low molecular weight form was found more frequently in hormone receptor-positive than in receptor-negative cancers. Furthermore, an inverse relationship was found between the high molecular weight form of MGA and both tumour grade and proliferation index. No significant correlation was found between the MGA proteins and either tumor size or nodal status. Our results show that MGA protein exists in 2 main forms in breast tissue. As the high molecular weight form correlated positively with hormone receptors and negatively with tumor grade and proliferation rate, its presence is likely to be associated with a favourable prognosis for breast cancer. As expression of MGA is almost breast specific, it is a promising marker for breast cancer. Its most immediate use is likely to be in detecting micrometastases from breast cancer.

Secretoglobins in the human pituitary: high expression of lipophilin B and its down-regulation in pituitary adenomas

Secretoglobins are small secreted proteins, the expression of which has mostly been associated with secretory mucosal epithelia. Several secretoglobins have been implicated in the development of various human cancers. Allelic deletions of chromosome 11q13 correlates with the invasiveness of pituitary tumors. Intriguingly, several secretoglobin genes are located on 11q13; however, for most of these genes the expression in the pituitary and pituitary tumors have not been investigated. Antibodies specific for the secretoglobin lipophilin B (SCGB1D2, BU101) were developed and used in an immunohistochemical analysis of a human normal tissue microarray. Prominent lipophilin B immunoreactivity was found in the secretory cells of the anterior pituitary. Eight of nine analyzed pituitary adenomas showed a reduction in lipophilin B immunoreactivity compared to normal pituitary. However, there was no apparent association between lipophilin B immunoreactivity and hormone production or tumor invasiveness. Expression of eight different secretoglobin mRNAs were analyzed in normal pituitary and the pituitary adenoma cell line HP75 by highly specific quantitative real-time reverse transcription-PCR assays. Lipophilins B and C (SCGB2A1, mammaglobin B) were the most prominently expressed secretoglobin mRNAs in the pituitary. No secretoglobin mRNA was detected in the HP75 cells. The present report demonstrates, for the first time, lipophilin B expression in the pituitary and its apparent down-regulation in pituitary adenomas.

Proteomic patterns: their potential for disease diagnosis

Alterations in proteins abundance, structure, or function, act as useful indicators of pathological abnormalities prior to development of clinical symptoms and as such are often useful diagnostic and prognostic biomarkers. The underlying mechanism of diseases such as cancer are, however, quite complicated in that often multiple dysregulated proteins are involved. It is for this reason that recent hypotheses suggest that detection of panels of biomarkers may provide higher sensitivities and specificities for disease diagnosis than is afforded with single markers. Recently, a novel approach based on the analysis of protein patterns has emerged that may provide a more effective means to diagnose diseases, such as ovarian and prostate cancer. The method is based on the use of surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry (TOF-MS) to detect differentially captured proteins from clinical samples, such as serum and plasma. This analysis results in the detection of "proteomic" patterns that have been shown in recent investigations to distinguish diseased and unaffected subjects to varying degrees. This review will discuss the basics of SELDI protein chip technology and highlight its recent applications in disease biomarker discovery with emphasis on cancer diagnosis.

Proteomic approaches in cancer risk and response assessment

Proteomics is more than just a list-generating exercise where increases or decreases in protein expression are identified. Proteomic technologies will ultimately characterize information-flow through the protein circuitry that interconnects the extracellular microenvironment to the serum or plasma macroenvironment through intracellular signaling systems and their control of gene transcription. The nature of this information can be a cause or a consequence of disease processes and how patients respond to therapy. Analysis of human cancer as a model for how proteomics can have an impact at the bedside can take advantage of several promising new proteomic technologies. These technologies are being developed for early detection and risk assessment, therapeutic targeting and patient-tailored therapy.

NB. Mammaglobin as a novel breast cancer biomarker: multigene reverse transcription-PCR assay and sandwich ELISA

BACKGROUND

The aim of this study was to examine the potential usefulness of a mammaglobin multigene reverse transcription-PCR (RT-PCR) assay and a mammaglobin sandwich ELISA as diagnostic tools in breast cancer.

METHODS

We studied peripheral blood samples from 147 untreated Senegalese women with biopsy-confirmed breast cancer and gathered patient information regarding demographic, and clinical staging of disease. The samples were tested for mammaglobin and three breast cancer-associated gene transcripts by a multigene real-time RT-PCR assay and for serum mammaglobin protein by a sandwich ELISA assay.

RESULTS

In 77% of the breast cancer blood samples, a positive signal was obtained in the multigene RT-PCR assay detecting mammaglobin and three complementary transcribed genes. Fifty samples from healthy female donors tested negative. Significant correlations were found between mammaglobin protein in serum, presence of mammaglobin mRNA-expressing cells in blood, stage of disease, and tumor size. Circulating mammaglobin protein was detected in 68% of the breast cancer sera, and was increased in 38% in comparison with a mixed control population. The RT-PCR assay and the ELISA for mammaglobin produced a combined sensitivity of 84% and specificity of 97%.

CONCLUSION

The ELISA and RT-PCR for mammaglobin and mammaglobin-producing cells could be valuable tools for diagnosis and prognosis of breast cancer.

Clinical proteomics: revolutionizing disease detection and patient tailoring therapy

The evolving discipline of Clinical Proteomics is more than simply describing and enumerating the systematic changes in the protein constituency of a cell, or just generating lists of proteins that increase or decrease in expression as a cause or consequence of disease. Clinical applications of proteomics involve the use of proteomic technologies at the bedside with the ultimate goal to characterize the information flow through the intra- and extracellular molecular protein networks that interconnect organ and circulatory systems together. These networks are both new targets for therapeutics themselves as well as underpin the dynamic changes that give rise to cascades of new diagnostic biomarkers. The analysis of human cancer can be used as a model for how clinical proteomics is having an impact at the bedside for early detection, rational therapeutic targeting, and patient-tailored therapy.

Mammaglobin: a candidate diagnostic marker for breast cancer

Mammaglobin, known for its mammary tissue specificity, has been discussed as a promising diagnostic marker in breast cancer for almost 10 years. In particular, the application of mammaglobin RT-PCR to detect disseminated breast cancer cells has been reported. More than 25 publications evaluate the detection of mammaglobin mRNA in lymph node, blood, and bone marrow specimens of breast cancer patients. Recently, structural details about the mammaglobin complex have been discovered, and these findings can be implemented to optimize detection of the secreted protein. This review summarizes the findings of almost 50 published studies and the current knowledge about the diagnostic utility of mammaglobin.

Rapid discovery and identification of a tissue-specific tumor biomarker from 39 human cancer cell lines using the SELDI ProteinChip platform

Useful biomarkers are needed for early detection of cancers. To demonstrate the potential diagnostic usefulness of a new proteomic technology, we performed Expression Difference Mapping analysis on 39 cancer cell lines from 9 different tissues using ProteinChip technology. A protein biomarker candidate of 12kDa was found in colon cancer cells. We then optimized the purification conditions for this biomarker by utilizing Retentate Chromatography mass spectrometry (RC-MS). The optimized purification conditions developed "on-chip" were directly transferred to conventional chromatography to purify the biomarker, which was identified as prothymosin-alpha by ProteinChip time-of-flight mass spectrometry (TOF MS) and ProteinChip-Tandem MS systems. The relative expression level of prothymosin-alpha between colon cancer cells and normal colon mucosal cells was evaluated on the same ProteinChip platform. Prothymosin-alpha expression in colon cancer cells was clearly higher than in normal colon cells. These results indicate that prothymosin-alpha could be a potential biomarker for colon cancer, and that the ProteinChip platform could perform the whole process of biomarker discovery from screening to evaluation of the identified marker.