人附睾蛋白4作为卵巢癌生物标志物的初步研究

目的:探讨人附睾蛋白4(HE4)在卵巢癌组织和血清中的表达及其临床病理意义。方法:用免疫组织化学技术检测正常卵巢,卵巢良性上皮性肿瘤,交界性上皮性肿瘤和癌组织中HE4的表达,并分析其与临床分期和预后的关系;用ELISA方法检测患者血清中HE4的含量。结果:HE4在浆液性乳头状囊腺癌组织中的阳性表达率要显著高于交界性肿瘤,良性肿瘤和正常组织,而交界性肿瘤阳性表达率显著高于良性肿瘤和正常对照。HE4表达与临床分期没有显著相关性。HE4阳性患者的平均生存期、5年生存率和中位生存期均显著低于HE4阴性患者。卵巢癌和交界性肿瘤患者血清中HE4含量显著高于良性肿瘤和正常对照组。结论:HE4可能作为卵巢癌诊断和预后的组织和血清标志物。     

IPI59: An Actionable Biomarker to Improve Treatment Response in Serous Ovarian Carcinoma Patients

Despite improvements in operative management and therapies, overall survival rates in advanced ovarian cancer have remained largely unchanged over the past three decades. Although it is possible to identify high-risk patients following surgery, the knowledge does not provide information about the genomic aberrations conferring risk, or the implications for treatment. To address these challenges, we developed an integrative pathway-index model and applied it to messenger RNA expression from 458 patients with serous ovarian carcinoma from the Cancer Genome Atlas project. The biomarker derived from this approach, IPI59, contains 59 genes from six pathways. As we demonstrate using independent datasets from six studies, IPI59 is strongly associated with overall and progression-free survival, and also identifies high-risk patients who may benefit from enhanced adjuvant therapy.     

Linkage Specific Fucosylation of Alpha-1-Antitrypsin in Liver Cirrhosis and Cancer Patients: Implications for a Biomarker of Hepatocellular Carcinoma

Background

We previously reported increased levels of protein-linked fucosylation with the development of liver cancer and identified many of the proteins containing the altered glycan structures. One such protein is alpha-1-antitrypsin (A1AT). To advance these studies, we performed N-linked glycan analysis on the five major isoforms of A1AT and completed a comprehensive study of the glycosylation of A1AT found in healthy controls, patients with hepatitis C- (HCV) induced liver cirrhosis, and in patients infected with HCV with a diagnosis of hepatocellular carcinoma (HCC).

Methodology/Principal Findings

Patients with liver cirrhosis and liver cancer had increased levels of triantennary glycan-containing outer arm (α-1,3) fucosylation. Increases in core (α-1,6) fucosylation were observed only on A1AT from patients with cancer. We performed a lectin fluorophore-linked immunosorbent assay using Aleuria Aurantia lectin (AAL), specific for core and outer arm fucosylation in over 400 patients with liver disease. AAL-reactive A1AT was able to detect HCC with a sensitivity of 70% and a specificity of 86%, which was greater than that observed with the current marker of HCC, alpha-fetoprotein. Glycosylation analysis of the false positives was performed; results indicated that these patients had increases in outer arm fucosylation but not in core fucosylation, suggesting that core fucosylation is cancer specific.

Conclusions/Significance

This report details the stepwise change in the glycosylation of A1AT with the progression from liver cirrhosis to cancer and identifies core fucosylation on A1AT as an HCC specific modification.     

PIK3CA Gene Mutations and Overexpression: Implications for Prognostic Biomarker and Therapeutic Target in Chinese Esophageal Squamous Cell Carcinoma

Aims

To evaluate PIK3CA gene mutations and PIK3CA expression status in Chinese esophageal squamous cell carcinoma (ESCC) patients, and their correlation with clinicopathological characteristics and clinical outcomes.

Methods

Direct sequencing was applied to investigate mutations in exons 9 and 20 of PIK3CA in 406 Chinese ESCC patients. PIK3CA expression was evaluated using immunohistochemistry analysis. The associations of PIK3CA gene mutations and PIK3CA expression with clinicopathological characteristics and clinical outcome were examined.

Results

Thirty somatic point mutations (30/406, 7.4%) were identified in exon 9 whereas no mutations were detected in exon 20. PIK3CA mutations were not correlated with clinicopathological characteristics or clinical outcomes. However in the ESCC patients with family cancer history, PIK3CA mutations were independently correlated with worse overall survival (multivariate hazard ratio (HR) = 10.493, 95% CI: 2.432–45.267, P = 0.002). Compared to normal esophageal tissue, PIK3CA was significantly overexpressed in cancer tissue (P<0.001). PIK3CA overexpression was independently associated with higher risk of local recurrence (multivariate HR  = 1.435, 95% CI: 1.040–1.979, P = 0.028). In female ESCC patients, PIK3CA overexpression was independently correlated with worse overall survival (multivariate HR  = 2.341, 95% CI: 1.073–5.108, P = 0.033).

Conclusions

Our results suggest PIK3CA gene mutation and overexpression could act as biomarkers for individualized molecular targeted therapy for Chinese ESCC patients.     

Different Subtypes of GABA-A Receptors Are Expressed in Human, Mouse and Rat T Lymphocytes

γ-aminobutyric acid (GABA) is the most prominent neuroinhibitory transmitter in the brain, where it activates neuronal GABA-A receptors (GABA-A channels) located at synapses and outside of synapses. The GABA-A receptors are primary targets of many clinically useful drugs. In recent years, GABA has been shown to act as an immunomodulatory molecule. We have examined in human, mouse and rat CD4(+) and CD8(+) T cells which subunit isoforms of the GABA-A channels are expressed. The channel physiology and drug specificity is dictated by the GABA-A receptor subtype, which in turn is determined by the subunit isoforms that make the channel. There were 5, 8 and 13 different GABA-A subunit isoforms identified in human, mouse and rat CD4(+) and CD8(+) T cells, respectively. Importantly, the γ2 subunit that imposes benzodiazepine sensitivity on the GABA-A receptors, was only detected in the mouse T cells. Immunoblots and immunocytochemistry showed abundant GABA-A channel proteins in the T cells from all three species. GABA-activated whole-cell transient and tonic currents were recorded. The currents were inhibited by picrotoxin, SR95531 and bicuculline, antagonists of GABA-A channels. Clearly, in both humans and rodents T cells, functional GABA-A channels are expressed but the subtypes vary. It is important to bear in mind the interspecies difference when selecting the appropriate animal models to study the physiological role and pharmacological properties of GABA-A channels in CD4(+) and CD8(+) T cells and when selecting drugs aimed at modulating the human T cells function.     

Use of a Single-Chain Antibody Library for Ovarian Cancer Biomarker Discovery

The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis.Despite many advances in the treatment of cancer, early detection and tumor removal remains the best prospect for overcoming disease. Ovarian cancer is an excellent example of the potential prognostic value of early detection because diagnosis at a localized stage has a 5-year survival rate of 93%. However, only 19% of cases are diagnosed at this stage, and by the time the disease has evolved to an advanced stage, the 5-year survival rate drops to 31% (1).Much effort has been expended to find early detection markers of ovarian cancer, and some success has been achieved. Most notable is CA125, the only approved marker for the detection of recurrence of ovarian cancer (2). Other leading targets are mesothelin and HE4, which have been examined by several groups for their efficacy as early detection markers (3–8). Nevertheless, several conditions necessitate the discovery of more specific and sensitive ovarian cancer markers: the heterogeneity of this disease, the ambiguity of its symptoms, its low incidence in the general population, and the low sensitivity and specificity of currently available markers.One of the difficulties in finding markers in blood is the complexity of the plasma/serum proteome, estimated in the tens to hundreds of thousands of proteins, as well as its large range in constituent protein concentrations, which can span 12 orders of magnitude (9). However, along with its easy accessibility, the fact that blood is in contact with virtually every tissue and contains tissue- and tumor-derived proteins makes it a preferred source for disease biomarker discovery.Our previous results (10, 11) and those of others (12–14) using high density, full-length IgG antibody microarrays to validate and discover cancer serum biomarkers demonstrated that this platform is valuable for simultaneously comparing the levels of hundreds of proteins on dozens of serum samples from cancer patients and healthy controls. We confirmed overexpression of CA125, mesothelin, and HE4 in ovarian cancer samples using this high density microarray platform, validating our array methodology for measurement of cancer serum biomarkers and yielding new putative biomarkers for this disease (10, 11).Previously reported approaches are typically limited to a few hundred antibodies. The methodology reported here allows us to exploit the specific advantages of antibodies as high affinity capture reagents to detect differential expression of thousands of tumor biomarkers using a diverse (2 × 10⁸ binding agents) single-chain variable fragment antibody (scFv)¹ library for detection of ovarian cancer markers in serum, tumor cyst fluid, and ascites fluid. Our results build on previous reports of phage display library microarrays to discover autoantibody (15–18) and other protein (12, 19, 20) cancer biomarkers. Our scFv are high affinity capture reagents consisting of the variable regions of human antibody heavy and light chains joined by a flexible linker peptide. These recombinant antibodies are able to recognize a wide variety of antigens, including many previously thought difficult, such as self-antigens and proteins that are not normally immunogenic in animals (21–24). Using a highly diverse recombinant antibody library, one has the ability to overcome the complexity of the serum proteome. It has been calculated that for an immune repertoire to be complete (at least one antibody in the repertoire has reasonable affinity for every epitope possible in nature) it requires a diversity of at least 10⁶ antibodies (25). The reported diversity of our scFv library exceeds this value by 100-fold (21).To enrich for antibodies that differentiate disease status, we performed a selection or panning of the naïve library for proteins that are differentially expressed in cyst fluid, ascites fluid, or serum of cancer patients with respect to healthy serum. We printed this sublibrary on activated hydrogel slides that were queried with three different sets of labeled case and control sera to further select those that discriminate cancer status in a statistically significant manner. Next, we identified some of the targets that bind to the individual scFv using high density nucleic acid programmable protein arrays (NAPPAs) expressing a total of over 7000 proteins. Finally, we validated the effectiveness of the selection process by confirming overexpression of these targets in cancer serum, cyst fluid, and ascites fluid as well as in tumor sections.     

Allelic Spectra of Risk SNPs Are Different for Environment/Lifestyle Dependent versus Independent Diseases

Genome-wide association studies (GWAS) have generated sufficient data to assess the role of selection in shaping allelic diversity of disease-associated SNPs. Negative selection against disease risk variants is expected to reduce their frequencies making them overrepresented in the group of minor (<50%) alleles. Indeed, we found that the overall proportion of risk alleles was higher among alleles with frequency <50% (minor alleles) compared to that in the group of major alleles. We hypothesized that negative selection may have different effects on environment (or lifestyle)-dependent versus environment (or lifestyle)-independent diseases. We used an environment/lifestyle index (ELI) to assess influence of environmental/lifestyle factors on disease etiology. ELI was defined as the number of publications mentioning “environment” or “lifestyle” AND disease per 1,000 disease-mentioning publications. We found that the frequency distributions of the risk alleles for the diseases with strong environmental/lifestyle components follow the distribution expected under a selectively neutral model, while frequency distributions of the risk alleles for the diseases with weak environmental/lifestyle influences is shifted to the lower values indicating effects of negative selection. We hypothesized that previously selectively neutral variants become risk alleles when environment changes. The hypothesis of ancestrally neutral, currently disadvantageous risk-associated alleles predicts that the distribution of risk alleles for the environment/lifestyle dependent diseases will follow a neutral model since natural selection has not had enough time to influence allele frequencies. The results of our analysis suggest that prediction of SNP functionality based on the level of evolutionary conservation may not be useful for SNPs associated with environment/lifestyle dependent diseases.     

Proteomic Analysis of Temporally Stimulated Ovarian Cancer Cells for Biomarker Discovery

While ovarian cancer remains the most lethal gynecological malignancy in the United States, there are no biomarkers available that are able to predict therapeutic responses to ovarian malignancies. One major hurdle in the identification of useful biomarkers has been the ability to obtain enough ovarian cancer cells from primary tissues diagnosed in the early stages of serous carcinomas, the most deadly subtype of ovarian tumor. In order to detect ovarian cancer in a state of hyperproliferation, we analyzed the implications of molecular signaling cascades in the ovarian cancer cell line OVCAR3 in a temporal manner, using a mass-spectrometry-based proteomics approach. OVCAR3 cells were treated with EGF¹, and the time course of cell progression was monitored based on Akt phosphorylation and growth dynamics. EGF-stimulated Akt phosphorylation was detected at 12 h post-treatment, but an effect on proliferation was not observed until 48 h post-exposure. Growth-stimulated cellular lysates were analyzed for protein profiles between treatment groups and across time points using iTRAQ labeling and mass spectrometry. The protein response to EGF treatment was identified via iTRAQ analysis in EGF-stimulated lysates relative to vehicle-treated specimens across the treatment time course. Validation studies were performed on one of the differentially regulated proteins, lysosomal-associated membrane protein 1 (LAMP-1), in human tissue lysates and ovarian tumor tissue sections. Further, tissue microarray analysis was performed to demarcate LAMP-1 expression across different stages of epithelial ovarian cancers. These data support the use of this approach for the efficient identification of tissue-based markers in tumor development related to specific signaling pathways. LAMP-1 is a promising biomarker for studies of the progression of EGF-stimulated ovarian cancers and might be useful in predicting treatment responses involving tyrosine kinase inhibitors or EGF receptor monoclonal antibodies.Ovarian cancer is the leading cause of death from gynecologic malignancy in the United States, and the fifth leading cause of cancer-related deaths in women (1). Epithelial ovarian cancers are extensively heterogeneous; histological sub-classification by cell type includes serous, endometrioid, clear-cell, mucinous, transitional, squamous, and undifferentiated (2). Serous epithelial cancers are the most commonly diagnosed epithelial ovarian cancer subtype and are associated with the majority of ovarian-cancer-related deaths (1).From a molecular perspective, the basic characteristic of any cancerous cell is its ability to grow uncontrollably. As a cell proliferates, a cascade of molecular and morphological changes occurs, including the activation of signaling cascades that modulate cytoskeletal dynamics, cell cycle progression, and angiogenesis (3–5). In addition to the unrestrained aberrant proliferation of cancer cells, other processes are required for disease progression, including changes in cellular adhesion to endothelial cells and in the extracellular microenvironment (6). It is important to note, however, that cancer cell progression is not an instantaneous event, and the demarcation between non-cancer and cancer is not static. It is postulated that epithelial cancer cells transition to a highly motile and invasive mesenchymal cell type, and this epithelial-to-mesenchymal transition is a critical molecular mechanism in tumor progression and metastasis (6). Several important signaling cascades have been implicated in this transition, including those mediated by EGF, PDGF, and TGFβ and those involving PI3K/Akt activation (7, 8). Thus, biomarkers of cancer progression can serve as indicators of disease etiology and potential staging, as well as predictive markers of therapeutic regimen responses. The identification of differentially expressed proteins during cancer metastasis has the potential to be utilized both prognostically with regard to metastatic development and predictively, through the implementation of pathway-specific therapies.Molecular analyses indicate the oncogenic role of the epidermal growth factor receptor (EGFR) in several human cancers, including lung cancers and Her2-amplified breast cancers (9). However, less is known regarding the implications of aberrant EGFR expression in ovarian cancer progression, particularly in terms of increased activation of downstream signaling cascades and efficacious therapeutic regimens. Studies illustrate overamplification of the EGFR gene in between 4% and 22% of ovarian cancers, with aberrant protein expression in up to 60% of ovarian malignancies (10–12). Aberrant EGFR expression has been associated with high tumor grade, increased cancerous cell proliferation, and poorer patient outcomes (12–15). Gene amplification and the overexpression of other EGFR family members such as Her2 and ErbB3 have also been reported in epithelial ovarian cancers (15). Further, studies performed in vitro illustrate the ability of EGF to induce DNA synthesis and stimulate cell growth in OVCAR3 cells (16).Although EGFR and downstream EGF-regulated signaling cascades have been implicated in ovarian malignancies, the treatment of ovarian tumors with anti-EGFR agents has induced minimal response. Targeted EGFR therapies fall into two categories: monoclonal antibodies that target the receptor extracellular domain to prevent ligand binding, and tyrosine kinase inhibitors (TKIs), which aim to prevent the activation of downstream signaling cascades. Although EGFR inhibitors exhibit modest success in vitro, no agents have been approved by the U.S. Food and Drug Administration for the treatment of malignant ovarian tumors (17). Among other therapeutic approaches, studies have looked at the potential efficacy of the TKIs erlotinib and gefitinib in the treatment of ovarian cancers; unfortunately, neither drug was effective in eliciting a significant response in ovarian tumor treatment (12, 15, 18, 19). However, the identification of markers of pathway-stimulated processes might help to stratify disease and select patients with EGF signaling activation. The identified markers might facilitate the prediction of treatment responses.MS-based proteomic studies have been heavily implemented in the identification of candidate biomarkers in a variety of specimen sources ranging from epithelial ovarian cancer tissue to immortalized cell lines and cultured media (20–22). The human adenocarcinoma OVCAR3 cell line is derived from an epithelial ovarian cancer with a high grade serous cell type and exhibits many of the molecular and morphological aspects of serous epithelial cancers (23, 24). This cell line can be stimulated to promote or inhibit cellular proliferation using various molecular agonists and antagonists (23–25). Because of the molecular and morphological similarities between the OVCAR3 cell line and ovarian adenocarcinoma cells, it serves as an appropriate high-throughput surrogate for candidate biomarker identification. Further, the analysis of a single cell line allows for the identification of temporal protein regulation within a single homogeneous cell population using an orthogonal approach.In the present study, the OVCAR3 cell line was treated with the hyperproliferative molecule EGF or the PI3K/Akt inhibitor {"type":"entrez-nucleotide","attrs":{"text":"LY294002","term_id":"1257998346","term_text":"LY294002"}}LY294002 over a 48-h time course. Three time points were analyzed for biochemical and molecular changes, including Akt phosphorylation status and increased proliferation. Additionally, growth-stimulated and growth-inhibited cellular lysates were analyzed using quantitative proteomics with iTRAQ and MS/MS, and these analyses illustrated comparable global protein profiles between treatment groups and across time points. Differentially expressed proteins were identified in growth-stimulated cells as opposed to control (vehicle-treated) cells. One of the differentially regulated proteins, lysosomal-associated membrane protein 1 (LAMP-1, also known as CD107a), was further verified via immunoblotting and immunohistochemical analyses in normal and ovarian cancer tissues, in addition to tissue microarray analysis. This study demonstrates that through the use of a growth-stimulated cell culture model using EGF, the rapid identification of differentially regulated proteins as proliferation progresses may be achieved via large-scale proteomic analyses. The identification of regulated proteins along the pathway of increased cellular growth and proliferation might serve a predictive role in treatment outcomes.     

Identification of Novel Biomarker Candidates for the Immunohistochemical Diagnosis of Cholangiocellular Carcinoma

The aim of this study was the identification of novel biomarker candidates for the diagnosis of cholangiocellular carcinoma (CCC) and its immunohistochemical differentiation from benign liver and bile duct cells. CCC is a primary cancer that arises from the epithelial cells of bile ducts and is characterized by high mortality rates due to its late clinical presentation and limited treatment options. Tumorous tissue and adjacent non-tumorous liver tissue from eight CCC patients were analyzed by means of two-dimensional differential in-gel electrophoresis and mass-spectrometry-based label-free proteomics. After data analysis and statistical evaluation of the proteins found to be differentially regulated between the two experimental groups (fold change ≥ 1.5; p value ≤ 0.05), 14 candidate proteins were chosen for determination of the cell-type-specific expression profile via immunohistochemistry in a cohort of 14 patients. This confirmed the significant up-regulation of serpin H1, 14-3-3 protein sigma, and stress-induced phosphoprotein 1 in tumorous cholangiocytes relative to normal hepatocytes and non-tumorous cholangiocytes, whereas some proteins were detectable specifically in hepatocytes. Because stress-induced phosphoprotein 1 exhibited both sensitivity and specificity of 100%, an immunohistochemical verification examining tissue sections of 60 CCC patients was performed. This resulted in a specificity of 98% and a sensitivity of 64%. We therefore conclude that this protein should be considered as a potential diagnostic biomarker for CCC in an immunohistochemical application, possibly in combination with other candidates from this study in the form of a biomarker panel. This could improve the differential diagnosis of CCC and benign bile duct diseases, as well as metastatic malignancies in the liver.Cholangiocellular carcinoma (CCC)¹ is a malignant neoplasm that arises from the cholangiocytes, the epithelial cells lining the bile ducts. The tumors, consisting of a significant amount of fibrous stroma, are classified as intrahepatic, extrahepatic, or hilar according to their anatomic location. Most common are the Klatskin tumors, originating from the confluence of the right and left hepatic ducts (1). Compared with other types of cancer, CCC is a relatively rare disease, accounting for about 3% of all gastrointestinal malignancies (2). However, its incidence is increasing, and as a result of poor patient outcomes it has overtaken hepatocellular carcinoma as the main cause of death from a primary hepatobiliary tumor (3). Reasons for the high mortality rate (5-year survival rate of about 5%) (4) are the difficult diagnosis and limited treatment options. At present, extensive surgical resection of the extrahepatic bile ducts and parts of the liver or liver transplantation remain the only potentially curative treatment options, although most patients are considered inoperable at the time of diagnosis (5).In general, the diagnosis of CCC is made based on histomorphological evaluation of core biopsies or cytological specimens. However, distinction between CCC and benign diseases such as reactive bile ductules or bile duct adenomas can be challenging when based on conventional histology alone. Additionally, it may be difficult to distinguish CCC from metastatic adenocarcinoma in the liver, especially when it originates from the pancreas like pancreatic ductal adenocarcinoma. Therefore, specific immunohistochemical tissue markers for CCC would be highly beneficial for further validation of the diagnosis. In routine immunohistochemical diagnosis of CCC, so far, the detection of p53 (a product of a tumor suppressor gene) has proven useful, although its application is limited because of low sensitivity (6). The cytokeratins Ck7, Ck8, Ck18, and Ck19 have been reported to have sensitivities of between 80% and 97% for CCC cells, but at low specificities and a similar expression as in non-tumorous cholangiocytes (7). In addition, the tumor marker carcinoembryonic antigen, which is a commonly applied serum marker, has been used for immunohistochemical staining of CCC tissue. Although this was reported to be positive in 100% of the tested CCC sections, it also was immunoreactive in 60% of hepatocellular carcinomas (8). Recently, it has been shown that the polycomb group protein EZH2 may be useful for differential diagnosis of cholangiolocellular carcinoma (a subtype of CCC), bile duct adenomas, and ductular reaction. This, however, applies only to this certain type of CCC (9). Establishing reliable immunohistochemical tumor markers specific for CCC therefore remains a challenge.Several proteomic studies using different sample types and various techniques have been performed in order to identify CCC-specific proteins. The analysis of CCC cell lines, for example, has led to the identification of potential diagnostic and prognostic biomarker candidates (10–12). In addition, cell lines have been used to discover proteins predictive of the response to chemotherapy (13). Because results from cell culture experiments do not always reflect the actual conditions in the tumor, the use of patient samples can be advantageous. The most appropriate source of tumor-specific signals is tumor tissue, which in the past has been analyzed via two-dimensional electrophoresis (14) and mass-spectrometry-based proteomic approaches such as histology-directed MALDI-TOF-MS (15), Surface-enhanced laser desorption/ionization (SELDI) TOF-MS (16), or LC-MS/MS (17). So far, however, none of the potential biomarkers have been successfully implemented into clinical routine.Recently, we demonstrated that the application of two complementary techniques, two-dimensional differential in-gel electrophoresis (2D-DIGE) and mass-spectrometry-based label-free LC-MS/MS, is an auspicious tactic for the discovery of novel biomarker candidates in hepatocellular carcinoma tissue (18). Here, we applied this well-established workflow as the initial step for the discovery of tissue markers that improve the differential diagnosis of intrahepatic CCC from benign bile duct diseases. In these experiments, CCC tumor tissue was compared with non-tumorous liver tissue (n = 8). Because this does not allow discrimination among different cell types such as hepatocytes, cholangiocytes, and tumor cells, an immunohistochemical determination of the cell-type-specific expression was subsequently performed for the most promising biomarker candidates. Stress-induced phosphoprotein 1, the protein showing the greatest specificity and sensitivity for CCC tumor cells, was verified as a suitable biomarker candidate for CCC in a larger patient cohort (n = 60).     

Identification of Circulating Biomarker Candidates for Hepatocellular Carcinoma (HCC): An Integrated Prioritization Approach

Hepatocellular carcinoma (HCC) is the world’s third most widespread cancer. Currently available circulating biomarkers for this silently progressing malignancy are not sufficiently specific and sensitive to meet all clinical needs. There is an imminent and pressing need for the identification of novel circulating biomarkers to increase disease-free survival rate. In order to facilitate the selection of the most promising circulating protein biomarkers, we attempted to define an objective method likely to have a significant impact on the analysis of vast data generated from cutting-edge technologies. Current study exploits data available in seven publicly accessible gene and protein databases, unveiling 731 liver-specific proteins through initial enrichment analysis. Verification of expression profiles followed by integration of proteomic datasets, enriched for the cancer secretome, filtered out 20 proteins including 6 previously characterized circulating HCC biomarkers. Finally, interactome analysis of these proteins with midkine (MDK), dickkopf-1 (DKK-1), current standard HCC biomarker alpha-fetoprotein (AFP), its interacting partners in conjunction with HCC-specific circulating and liver deregulated miRNAs target filtration highlighted seven novel statistically significant putative biomarkers including complement component 8, alpha (C8A), mannose binding lectin (MBL2), antithrombin III (SERPINC1), 11β-hydroxysteroid dehydrogenase type 1 (HSD11B1), alcohol dehydrogenase 6 (ADH6), beta-ureidopropionase (UPB1) and cytochrome P450, family 2, subfamily A, polypeptide 6 (CYP2A6). Our proposed methodology provides a swift assortment process for biomarker prioritization that eventually reduces the economic burden of experimental evaluation. Further dedicated validation studies of potential putative biomarkers on HCC patient blood samples are warranted. We hope that the use of such integrative secretome, interactome and miRNAs target filtration approach will accelerate the selection of high-priority biomarkers for other diseases as well, that are more amenable to downstream clinical validation experiments.     

Behavioral Studies with Electromagnetic Fields: Implications for Psychobiology

Research In the behavioral effects of non-ionizing radiation has progressed very slowly over the past twenty years. Of the little that has been done, much of it has been in imitation of Soviet work using archaic, insensitive behavioral techniques. Much of this work has been done by scientists not qualified in experimental psychology and they seem to be unaware of the elegance and sensitivity of behavioral techniques that have been developed in the United States. A critical review of the literature available, though, reveals that (1) effects are most clearly and reliably discerned when time-based schedules of reinforced behavior are used; (2) pulsed or modulated fields have more impact than CW fields, something that can be observed only if the behavioral measure is reliable and sensitive; and (3) magnetic fields may be especially potent for some species, if not all. Directions for future research are suggested.     

REG4 Is Highly Expressed in Mucinous Ovarian Cancer: A Potential Novel Serum Biomarker

Preoperative diagnostics of ovarian neoplasms rely on ultrasound imaging and the serum biomarkers CA125 and HE4. However, these markers may be elevated in non-neoplastic conditions and may fail to identify most non-serous epithelial cancer subtypes. The objective of this study was to identify histotype-specific serum biomarkers for mucinous ovarian cancer. The candidate genes with mucinous histotype specific expression profile were identified from publicly available gene-expression databases and further in silico data mining was performed utilizing the MediSapiens database. Candidate biomarker validation was done using qRT-PCR, western blotting and immunohistochemical staining of tumor tissue microarrays. The expression level of the candidate gene in serum was compared to the serum CA125 and HE4 levels in a patient cohort of prospectively collected advanced ovarian cancer. Database searches identified REG4 as a potential biomarker with specificity for the mucinous ovarian cancer subtype. The specific expression within epithelial ovarian tumors was further confirmed by mRNA analysis. Immunohistochemical staining of ovarian tumor tissue arrays showed distinctive cytoplasmic expression pattern only in mucinous carcinomas and suggested differential expression between benign and malignant mucinous neoplasms. Finally, an ELISA based serum biomarker assay demonstrated increased expression only in patients with mucinous ovarian cancer. This study identifies REG4 as a potential serum biomarker for histotype-specific detection of mucinous ovarian cancer and suggests serum REG4 measurement as a non-invasive diagnostic tool for postoperative follow-up of patients with mucinous ovarian cancer.     

Ovarian Cancer Cell Line Panel (OCCP): Clinical Importance of In Vitro Morphological Subtypes

Epithelial ovarian cancer is a highly heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Therapeutic approaches need to account for inter-patient and intra-tumoural heterogeneity and detailed characterization of in vitro models representing the different histological and molecular ovarian cancer subtypes is critical to enable reliable preclinical testing. There are approximately 100 publicly available ovarian cancer cell lines but their cellular and molecular characteristics are largely undescribed. We have characterized 39 ovarian cancer cell lines under uniform conditions for growth characteristics, mRNA/microRNA expression, exon sequencing, drug response for clinically-relevant therapeutics and collated all available information on the original clinical features and site of origin. We tested for statistical associations between the cellular and molecular features of the lines and clinical features. Of the 39 ovarian cancer cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes: Epithelial (n = 21), Round (n = 7) and Spindle (n = 12) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes in the Spindle subtype. Comparison with the original clinical data showed association of the spindle-like tumours with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the expression profiles of Spindle, Round and Epithelial morphologies clustered with the previously described C1-stromal, C5-mesenchymal and C4 ovarian subtype expression profiles respectively. Comprehensive profiling of 39 ovarian cancer cell lines under controlled, uniform conditions demonstrates clinically relevant cellular and genomic characteristics. This data provides a rational basis for selecting models to develop specific treatment approaches for histological and molecular subtypes of ovarian cancer.     

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research.     

Biomarker Studies in Multiple Sclerosis: From Proteins to Noncoding RNAs

Multiple sclerosis (MS) is a neuroimmunological disorder characterized by central nervous system demyelination, axonal injury and loss. Considering the complexity of its aetiopathogenesis, early diagnosis of MS and individualized management are challenging in clinical practice. As the pathophysiologic and pharmacological indicators, studies on biomarkers in MS are useful for early prediction and diagnosis, monitoring of disease activity and predicting treatment response. In this review, we will summarize recent development of biomarker studies in MS from protein molecules to noncoding RNAs.