Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

Ovarian cancer: homeobox genes, autocrine/paracrine growth, and kinase signaling

Epithelial ovarian cancer, the fourth leading cause of cancer deaths in American women, is currently classified by surgical and histologic appearance. However, the predictive value of this classification is limited. The risk of epithelial ovarian cancer increases with the number of ovulatory events. It is now thought that different ovarian tumors are derived from a single ovarian surface epithelial precursor cell with the degree and pattern of differentiation determined by combinatorial expression of homeobox genes normally involved in differentiation of the female genital tract. This aberrant differentiation occurs in association with histology-specific genomic aberrations, genomic instability, and resultant chromosomal changes, and may be triggered by prolonged abnormal or excessive exposure of surface epithelial cells to autocrine/paracrine stimulation by sex steroids and other growth factors. As the disease progresses, activation of kinase pathways and continued abnormal autocrine/paracrine stimulation contribute to genomic instability but also identify potential targets for novel therapeutic intervention.     

Identification of S-nitrosylated proteins after chronic exposure of colon epithelial cells to deoxycholate

Apoptosis resistance, a condition favoring genomic instability, is associated with higher risk of colorectal cancer. Deoxycholate (DOC) is a hydrophobic bile salt found in high concentrations in colon cancer patients, and induces apoptosis in cultured colonic cells and ex vivo in colonic biopsies. We showed previously that the chronic exposure of colon cancer cells to increasing concentrations of DOC leads to apoptosis resistance, and the suggested mechanism involves oxidative/nitrosative stress. Nitric oxide (NO) is a key signaling molecule that regulates cell function in a variety of physiologic and pathophysiologic states. In part, NO exerts its actions by S-nitrosylation of target thiols, and several proteins are regulated through this PTM, including the caspases, the main effectors of apoptosis. Here, we performed a proteomics study in the DOC-induced apoptosis-resistant colon cell line, HCT-116RC. Its profile of S-nitrosylated proteins was compared to a control cell line not exposed to DOC. Eighteen differentially S-nitrosylated proteins were identified in the HCT-116RC cell line, 14 of these are novel targets of S-nitrosylation not previously reported. These proteins include cytoskeletal and signaling proteins, metabolic enzymes, chaperones, and redox- and differentiation-related proteins. These results broaden our knowledge of potential signal transduction pathways that may lead to the development of new biomarkers and therapy targets.     

Discovery of DNA Hypermethylation Using a DHPLC Screening Strategy

Promoter hypermethylation is recognized as a hallmark of human cancer, in addition to conventional mechanisms of gene inactivation. As such, many new technologies have been developed over the past two decades to uncover novel targets of methylation and decipher complex epigenetic patterns. However, many of these are either labour intensive or provide limited data, confined to oligonucleotide hybridization sequences or enzyme cleavage sites and cannot be easily applied to screening large sets of sequences or samples. We present an application of denaturing high performance liquid chromatography (DHPLC), which relies on bisulfite modification of genomic DNA, for methylation screening. We validated DHPLC as a methylation screening tool using GSTP1, a well known target of methylation in prostate cancer. We developed an in silico approach to identify potential targets of promoter hypermethylation in prostate cancer. Using DHPLC, we screened two of these targets LGALS3 and SMAD4 for methylation. We show that DHPLC has an application as a fast, sensitive, quantitative and cost effective method for screening novel targets or DNA samples for DNA methylation.     

A Photoprotein in Mouse Embryonic Stem Cells Measures Ca2+ Mobilization in Cells and in Animals

Exogenous expression of pharmacological targets in transformed cell lines has been the traditional platform for high throughput screening of small molecules. However, exogenous expression in these cells is limited by aberrant dosage, or its toxicity, the potential lack of interaction partners, and alterations to physiology due to transformation itself. Instead, primary cells or cells differentiated from precursors are more physiological, but less amenable to exogenous expression of reporter systems. To overcome this challenge, we stably expressed c-Photina, a Ca²⁺-sensitive photoprotein, driven by a ubiquitous promoter in a mouse embryonic stem (mES) cell line. The same embryonic stem cell line was also used to generate a transgenic mouse that expresses c-Photina in most tissues. We show here that these cells and mice provide an efficient source of primary cells, cells differentiated from mES cells, including cardiomyocytes, neurons, astrocytes, macrophages, endothelial cells, pancreatic islet cells, stably and robustly expressing c-Photina, and may be exploited for miniaturized high throughput screening. Moreover, we provide evidence that the transgenic mice may be suitable for ex-vivo bioimaging studies in both cells and tissues.     

Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.     

Detection of MET mRNA in gastric cancer in situ. Comparison with immunohistochemistry and sandwich immunoassays

Determination of predictive biomarkers by immunohistochemistry (IHC) relies on antibodies with high selectivity. RNA in situ hybridization (RNA ISH) may be used to confirm IHC and may potentially replace it if suitable antibodies are not available or are insufficiently selective to discriminate closely related protein isoforms. We validated RNA ISH as specificity control for IHC and as a potential alternative method for selecting patients for treatment with MET inhibitors. MET, the HGF receptor, is encoded by the MET proto-oncogene that may be activated by mutation or amplification. MET expression and activity were tested in a panel of control cell lines. MET could be detected in formalin fixed paraffin, embedded (FFPE) samples by IHC and RNA ISH, and this was confirmed by sandwich immunoassays of fresh frozen samples. Gastric cancer cell lines with high MET expression and phosphorylation of tyrosine-1349 respond to the MET inhibitor, BAY-853474. High expression and phosphorylation of MET is a predictive biomarker for response to MET inhibitors. We then analyzed MET expression and activity in a matched set of FFPE vs. fresh frozen tumor samples consisting of 20 cases of gastric cancer. Two of 20 clinical samples investigated exhibited high MET expression with RNA ISH and IHC. Both cases were shown by sandwich immunoassays to exhibits strong functional activity. Expression levels and functional activity in these two cases were in a range that predicted response to treatment. Our findings indicate that owing to its high selectivity, RNA ISH can be used to confirm findings obtained by IHC and potentially may replace IHC for certain targets if no suitable antibodies are available. RNA ISH is a valid platform for testing predictive biomarkers for patient selection.     

Protein arrays as tools for serum autoantibody marker discovery in cancer

Protein array technology has begun to play a significant role in the study of protein–protein interactions and in the identification of antigenic targets of serum autoantibodies in a variety of autoimmune disorders. More recently, this technology has been applied to the identification of autoantibody signatures in cancer.The identification of tumour-associated antigens (TAAs) recognised by the patient's immune response represents an exciting approach to identify novel diagnostic cancer biomarkers and may contribute towards a better understanding of the molecular mechanisms involved. Circulating autoantibodies have not only been used to identify TAAs as diagnostic/prognostic markers and potential therapeutic targets, they also represent excellent biomarkers for the early detection of tumours and potential markers for monitoring the efficacy of treatment. Protein array technology offers the ability to screen the humoral immune response in cancer against thousands of proteins in a high throughput technique, thus readily identifying new panels of TAAs. Such an approach should not only aid in improved diagnostics, but has already contributed to the identification of complex autoantibody signatures that may represent disease subgroups, early diagnostics and facilitated the analysis of vaccine trials.     

Linking genomics to immunotherapy by reverse immunology--'immunomics' in the new millennium

The disclosure of the human genome sequence and rapid advances in genomic expression profiling have revolutionized our knowledge about molecular changes in malignant diseases. Rapidly growing gene expression databases and improvements in bioinformatics tools set the stage for new approaches using large-scale molecular information to develop specific therapeutics in cancer. On one hand, the ability to detect clusters of genes differentially expressed in normal and malignant tissue may lead to widely applicable targeting of defined molecular structures. On the other hand, analyzing the 'molecular fingerprint' of an individual tumor raises the possibility of developing customized therapeutics. One approach to use the emerging new datasets for the development of novel therapeutics is to identify genes that are specifically expressed in tumors as targets for immune intervention. This review will focus on the process from in silico analysis of expression databases and screening of potential candidate genes by bioinformatics to the in vitro and in vivo analysis to determine the immunogenicity of candidate tumor antigens. Basic biological principles of 'reverse immunology' as well as technical advantages and difficulties will be addressed.     

Prediction of pharmacokinetic properties using experimental approaches during early drug discovery

There has been a significant increase in the number of compounds synthesized in early drug-discovery programs with the advances in combinatorial chemistry and high-throughput biological screening efforts. Various in silico, in vitro and in situ approaches have been described in literature that achieve higher throughput pharmacokinetic screening. In silico methodologies have mainly attempted to quantify the prospects of oral absorption of compounds based upon their physico-chemical properties. There is a greater availability of in vitro and in situ approaches to screen compounds for intestinal permeability (as a surrogate for absorption) and metabolic stability (as a surrogate for clearance). More recent modifications of the in vitro and in situ approaches to assess the potential of absorption and metabolism have enabled a higher throughput and an ability to correlate better with in vivo pharmacokinetics of compounds.     

New methods for finding common insertion sites and co-occurring common insertion sites in transposon- and virus-based genetic screens

Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.     

High-throughput transcriptomic and RNAi analysis identifies AIM1, ERGIC1, TMED3 and TPX2 as potential drug targets in prostate cancer

Prostate cancer is a heterogeneous group of diseases and there is a need for more efficient and targeted methods of treatment. In this study, the potential of gene expression data and RNA interference technique were combined to advance future personalized prostate cancer therapeutics. To distinguish the most promising in vivo prevalidated prostate cancer drug targets, a bioinformatic analysis was carried out using genome-wide gene expression data from 9873 human tissue samples. In total, 295 genes were selected for further functional studies in cultured prostate cancer cells due to their high mRNA expression in prostate, prostate cancer or in metastatic prostate cancer samples. Second, RNAi based cell viability assay was performed in VCaP and LNCaP prostate cancer cells. Based on the siRNA results, gene expression patterns in human tissues and novelty, endoplasmic reticulum function associated targets AIM1, ERGIC1 and TMED3, as well as mitosis regulating TPX2 were selected for further validation. AIM1, ERGIC1, and TPX2 were shown to be highly expressed especially in prostate cancer tissues, and high mRNA expression of ERGIC1 and TMED3 associated with AR and ERG oncogene expression. ERGIC1 silencing specifically regulated the proliferation of ERG oncogene positive prostate cancer cells and inhibited ERG mRNA expression in these cells, indicating that it is a potent drug target in ERG positive subgroup of prostate cancers. TPX2 expression associated with PSA failure and TPX2 silencing reduced PSA expression, indicating that TPX2 regulates androgen receptor mediated signaling. In conclusion, the combinatorial usage of microarray and RNAi techniques yielded in a large number of potential novel biomarkers and therapeutic targets, for future development of targeted and personalized approaches for prostate cancer management.     

Unique Protein Profiles of Extracellular Vesicles as Diagnostic Biomarkers for Early and Advanced Non‐Small Cell Lung Cancer

Extracellular vesicles (EVs) mediate intercellular communication via transferring proteins and other biological molecules and have been recently investigated as biomarkers of disease. Sensitive and specific biomarkers are required for lung cancer diagnosis and prognosis. The present study screens for abnormal EV proteins in non‐small cell lung cancer (NSCLC) using a quantitative proteomics strategy involving LC‐MS/MS to identify ideal biomarkers for NSCLC diagnosis. EVs are enriched from the sera of early and advanced NSCLC patients and healthy controls and from cell culture supernatants of lung adenocarcinoma and bronchial epithelial cell lines. In the sera and supernatants, 279 and 632 differentially expressed proteins, respectively, are associated with signaling pathways including extracellular membrane–receptor interaction, focal adhesion, and regulation of the actin cytoskeleton. Thirty‐two EV proteins are identified at the intersection of differentially expressed proteins between the NSCLC groups and cell lines. Based on bioinformatics analysis, in silico immunohistochemical, and PRM verification, fibronectin is selected for following in vitro studies and validation with an independent cohort. Fibronectin on EVs is estimated to perform well in the diagnosis of NSCLC patients based on AUC, showing great potential for clinical use and demonstrating the efficacy of this method for EV‐associated biomarker screening.     

Identifying Tumor Cell Growth Inhibitors by Combinatorial Chemistry and Zebrafish Assays

Cyclin-dependent kinases (CDKs) play important roles in regulating cell cycle progression, and altered cell cycles resulting from over-expression or abnormal activation of CDKs observed in many human cancers. As a result, CDKs have become extensive studied targets for developing chemical inhibitors for cancer therapies; however, protein kinases share a highly conserved ATP binding pocket at which most chemical inhibitors bind, therefore, a major challenge in developing kinase inhibitors is achieving target selectivity. To identify cell growth inhibitors with potential applications in cancer therapy, we used an integrated approach that combines one-pot chemical synthesis in a combinatorial manner to generate diversified small molecules with new chemical scaffolds coupled with growth inhibition assay using developing zebrafish embryos. We report the successful identification of a novel lead compound that displays selective inhibitory effects on CDK2 activity, cancer cell proliferation, and tumor progression in vivo. Our approaches should have general applications in developing cell proliferation inhibitors using an efficient combinatorial chemical genetic method and integrated biological assays. The novel cell growth inhibitor we identified should have potential as a cancer therapeutic agent.     

Applications of biotechnology to pharmacology and toxicology.

Strategies for the development of new more efficient drugs at a lower cost and for the evaluation of the effects of chemicals and metals on tissue and cell function are changing considerably. This is made possible by recent progress in various areas, particularly biotechnology and bioinformatics. The recent sequencing of the human genome and the design of more and more sophisticated technologies will largely influence the fields of pharmacology and toxicology. Thus, identification of new molecular targets, development of more powerful cell models, design of miniaturized and automated tests for high throughput screening of thousands of compounds synthesized by combinatorial chemistry and progress in genomic and proteomic technologies that permit simultaneous analysis of thousands of genes and their products, offer new investigative ways that will still widely be extended in the next future.     

Inhibition of telomerase activity and human telomerase reverse transcriptase gene expression by histone deacetylase inhibitor in human brain cancer cells

The aim of the present study is to investigate the effect of histone deacetylase inhibitor, trichostatin A (TSA) on the cell growth, apoptosis, genomic DNA damage and the expression of telomerase and associated factors in human normal and brain cancer cells. Here, human normal un-transformed fibroblasts (MRC-5), human normal hTERT-immortalised fibroblasts (hTERT-BJ1) and human brain cancer cell lines (glioblastoma cell line, A-172 and medulloblastoma cell line, ONS-76) were treated with 0.5–3.0 μM TSA for 24 h. Exposure to TSA resulted in apoptosis in a dose-dependent manner in the brain cancer cells. Glioblastoma cell line (A-172) displayed higher sensitivity to TSA-induced cell killing effect and apoptosis than the medulloblastoma cell line (ONS-76). The brain cancer cell lines and hTERT-BJ1 cell line displayed significant inhibition in telomerase activity and hTERT mRNA level after 2 μM TSA treatment. Elevated expressions of p53 and p21 with a decrease in cyclin-D level supported the observation on cell cycle arrest following TSA treatment. Upregulation of Bax and cytochrome c correlated with the apoptotic events in TSA-treated cells. This study suggests that telomerase and hTERT might be the primary targets of TSA which may have the potential to be used as a telomerase inhibitor in cancer therapy.