Gene expression profiling reveals molecular marker candidates of laryngeal squamous cell carcinoma

Laryngeal squamous cell carcinoma is very common in head and neck cancer, with high mortality rates and poor prognosis. In this study, we compared expression profiles of clinical samples from 13 larynx tumors and 10 non-neoplastic larynx tissues using a custom-built cDNA microarray containing 331 probes for 284 genes previously identified by informatics analysis of EST databases as markers of head and neck tumors. Thirty-five genes showed statistically significant differences (SNR >= 11.01, p <= 0.001) in the expression between tumor and non-tumor larynx tissue samples. Functional annotation indicated that these genes are involved in cellular processes relevant to the cancer phenotype, such as apoptosis, cell cycle, DNA repair, proteolysis, protease inhibition, signal transduction and transcriptional regulation. Six of the identified transcripts map to intronic regions of protein-coding genes and may comprise non-annotated exons or as yet uncharacterized long ncRNAs with a regulatory role in the gene expression program of larynx tissue. The differential expression of 10 of these genes (ADCY6, AES, AL2SCR3, CRR9, CSTB, DUSP1, MAP3K5, PLAT, UBL1 and ZNF706) was independently confirmed by quantitative real-time RT-PCR. Among these, the CSTB gene product has cysteine protease inhibitor activity that has been associated with an antimetastatic function. Interestingly, CSTB showed a low expression in the tumor samples analyzed (p<0.0001). The set of genes identified here contribute to a better understanding of the molecular basis of larynx cancer, and provide candidate markers for improving diagnosis, prognosis and treatment of this carcinoma.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

Expression profiling of stem cell-related genes in neoadjuvant-treated gastric cancer: a NOTCH2, GSK3B and β-catenin gene signature predicts survival

Cancer stem cell (CSC) based gene expression signatures are associated with prognosis in various tumour types and CSCs are suggested to be particularly drug resistant. The aim of our study was first, to determine the prognostic significance of CSC-related gene expression in residual tumour cells of neoadjuvant-treated gastric cancer (GC) patients. Second, we wished to examine, whether expression alterations between pre- and post-therapeutic tumour samples exist, consistent with an enrichment of drug resistant tumour cells. The expression of 44 genes was analysed in 63 formalin-fixed, paraffin embedded tumour specimens with partial tumour regression (10-50% residual tumour) after neoadjuvant chemotherapy by quantitative real time PCR low-density arrays. A signature of combined GSK3B(high), β-catenin (CTNNB1)(high) and NOTCH2(low) expression was strongly correlated with better patient survival (p<0.001). A prognostic relevance of these genes was also found analysing publically available gene expression data. The expression of 9 genes was compared between pre-therapeutic biopsies and post-therapeutic resected specimens. A significant post-therapeutic increase in NOTCH2, LGR5 and POU5F1 expression was found in tumours with different tumour regression grades. No significant alterations were observed for GSK3B and CTNNB1. Immunohistochemical analysis demonstrated a chemotherapy-associated increase in the intensity of NOTCH2 staining, but not in the percentage of NOTCH2. Taken together, the GSK3B, CTNNB1 and NOTCH2 expression signature is a novel, promising prognostic parameter for GC. The results of the differential expression analysis indicate a prominent role for NOTCH2 and chemotherapy resistance in GC, which seems to be related to an effect of the drugs on NOTCH2 expression rather than to an enrichment of NOTCH2 expressing tumour cells.

Urinary metabolite profiling reveals CYP1A2-mediated metabolism of NSC686288 (aminoflavone)

NSC686288 [aminoflavone (AF)], a candidate chemotherapeutic agent, possesses a unique antiproliferative profile against tumor cells. Metabolic bioactivation of AF by drug-metabolizing enzymes, especially CYP1A monooxygenases, has been implicated as an underlying mechanism for its selective cytotoxicity in several cell culture-based studies. However, in vivo metabolism of AF has not been investigated in detail. In this study, the structural identities of 13 AF metabolites (12 of which are novel) in mouse urine or from microsomal incubations, including three monohydroxy-AFs, two dihydroxy-AFs and their sulfate and glucuronide conjugates, as well as one N-glucuronide, were determined by accurate mass measurements and liquid chromatography-tandem mass spectrometry fragmentation patterns, and a comprehensive map of the AF metabolic pathways was constructed. Significant differences between wild-type and Cyp1a2-null mice, within the relative composition of urinary metabolites of AF, demonstrated that CYP1A2-mediated regioselective oxidation was a major contributor to the metabolism of AF. Comparisons between wild-type and CYP1A2-humanized mice further revealed interspecies differences in CYP1A2-mediated catalytic activity. Incubation of AF with liver microsomes from all three mouse lines and with pooled human liver microsomes confirmed the observations from urinary metabolite profiling. Results from enzyme kinetic analysis further indicated that in addition to CYP1A P450s, CYP2C P450s may also play some role in the metabolism of AF.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Novel functional profiling approach combining reverse phase protein microarrays and human 3-D ex vivo tissue cultures: expression of apoptosis-related proteins in human colon cancer

Cancer is caused by a complex pattern of molecular perturbations. To understand the biology of cancer, it is thus important to look at the activation state of key proteins and signaling networks. The limited amount of available sample material from patients and the complexity of protein expression patterns make the use of traditional protein analysis methods particularly difficult. In addition, the only approach that is currently available for performing functional studies is the use of serial biopsies, which is limited by ethical constraints and patient acceptance. The goal of this work was to establish a 3-D ex vivo culture technique in combination with reverse-phase protein microarrays (RPPM) as a novel experimental tool for use in cancer research. The RPPM platform allows the parallel profiling of large numbers of protein analytes to determine their relative abundance and activation level. Cancer tissue and the respective corresponding normal tissue controls from patients with colorectal cancer were cultured ex vivo. At various time points, the cultured samples were processed into lysates and analyzed on RPPM to assess the expression of carcinoembryonic antigen (CEA) and 24 proteins involved in the regulation of apoptosis. The methodology displayed good robustness and low system noise. As a proof of concept, CEA expression was significantly higher in tumor compared with normal tissue (p<0.0001). The caspase 9 expression signal was lower in tumor tissue than in normal tissue (p<0.001). Cleaved Caspase 8 (p=0.014), Bad (p=0.007), Bim (p=0.007), p73 (p=0.005), PARP (p<0.001), and cleaved PARP (p=0.007) were differentially expressed in normal liver and normal colon tissue. We demonstrate here the feasibility of using RPPM technology with 3-D ex vivo cultured samples. This approach is useful for investigating complex patterns of protein expression and modification over time. It should allow functional proteomics in patient samples with various applications such as pharmacodynamic analyses in drug development.

Metabolic profiling of praziquantel enantiomers

Praziquantel (PZQ), prescribed as a racemic mixture, is the most readily available drug to treat schistosomiasis. In the present study, ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS) based metabolomics was employed to decipher the metabolic pathways and enantioselective metabolic differences of PZQ. Many phase I and four new phase II metabolites were found in urine and feces samples of mice 24h after dosing, indicating that the major metabolic reactions encompassed oxidation, dehydrogenation, and glucuronidation. Differences in the formation of all these metabolites were observed between (R)-PZQ and (S)-PZQ. In an in vitro phase I incubation system, the major involvement of CYP3A, CYP2C9, and CYP2C19 in the metabolism of PZQ, and CYP3A, CYP2C9, and CYP2C19 exhibited different catalytic activity toward the PZQ enantiomers. Apparent Km and Vmax differences were observed in the catalytic formation of three mono-oxidized metabolites by CYP2C9 and CYP3A4 further supporting the metabolic differences for PZQ enantiomers. Molecular docking showed that chirality resulted in differences in substrate location and conformation, which likely accounts for the metabolic differences. In conclusion, in silico, in vitro, and in vivo methods revealed the enantioselective metabolic profile of praziquantel.

Bridged bicyclic peptides as potential drug scaffolds: synthesis, structure, protein binding and stability

Double cyclization of short linear peptides obtained by solid phase peptide synthesis was used to prepare bridged bicyclic peptides (BBPs) corresponding to the topology of bridged bicyclic alkanes such as norbornane. Diastereomeric norbornapeptides were investigated by 1H-NMR, X-ray crystallography and CD spectroscopy and found to represent rigid globular scaffolds stabilized by intramolecular backbone hydrogen bonds with scaffold geometries determined by the chirality of amino acid residues and sharing structural features of β-turns and α-helices. Proteome profiling by capture compound mass spectrometry (CCMS) led to the discovery of the norbornapeptide 27c binding selectively to calmodulin as an example of a BBP protein binder. This and other BBPs showed high stability towards proteolytic degradation in serum.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

Paediatric drug development:reformulation, in vitro, genomic and in vivo evaluation

Angiotensin converting enzyme (ACE) inhibitors lisinopril and ramipril were selected from EMA/480197/2010 and the potassium-sparing diuretic spironolactone was selected from the NHS specials list for November 2011 drug tariff with the view to produce oral liquid formulations providing dosage forms targeting paediatrics. Lisinopril, ramipril and spironolactone were chosen for their interaction with transporter proteins in the small intestine. Formulation limitations such as poor solubility or pH sensitivity needed consideration. Lisinopril was formulated without extensive development as drug and excipients were water soluble. Ramipril and spironolactone are both insoluble in water and strategies combating this were employed. Ramipril was successfully solubilised using low concentrations of acetic acid in a co-solvent system and also via complexation with hydroxypropyl-β-cyclodextrin. A ramipril suspension was produced to take formulation development in a third direction. Spironolactone dosages were too high for solubilisation techniques to be effective so suspensions were developed. A buffer controlled pH for the sensitive drug whilst a precisely balanced surfactant and suspending agent mix provided excellent physical stability. Characterisation, stability profiling and permeability assessment were performed following formulation development. The formulation process highlighted current shortcomings in techniques for taste assessment of pharmaceutical preparations resulting in early stage research into a novel in vitro cell based assay. The formulations developed in the initial phase of the research were used as model formulations investigating microarray application in an in vitro-in vivo correlation for carrier mediated drug absorption. Caco-2 cells were assessed following transport studies for changes in genetic expression of the ATP-binding cassette and solute carrier transporter superfamilies. Findings of which were compared to in vitro and in vivo permeability findings. It was not possible to ascertain a correlation between in vivo drug absorption and the expression of individual genes or even gene families, however there was a correlation (R2 = 0.9934) between the total number of genes with significantly changed expression levels and the predicted human absorption.

Impurity profiling and synthesis of precursors to the hallucinogenic amphetamine DOB

DOB (4‐bromo‐2,5‐dimethoxyamphetamine) is a newly emerging hallucinogenic amphetamine that sparked serious health warnings in Ireland, following its first seizure back in 2003. Known more commonly as “snowball”, this drug is highly potent and may be used as a substitute to ecstasy (MDMA) and lysergic acid diethylamide (LSD). To date, the work carried out on the impurity profiling of DOB is limited in comparison to amphetamine, methamphetamine and MDMA. In this work, the impurity profile of 4‐bromo‐2,5‐dimethoxyphenyl‐2‐propanone (4‐Br‐2,5‐P2P) is explored. This ketone is a direct precursor to DOB. Its more versatile non‐bromo analogue, 2,5‐ dimethoxyphenyl‐2‐propanone (2,5‐P2P) is also examined, as in addition to DOB, it may be used in the synthesis of a range of several other hallucinogenic amphetamines. A number of different routes to both 2,5‐P2P and 4‐Br‐2,5‐P2P were investigated. For each of these routes, the impurities produced were carefully isolated. Following isolation, the impurities were fully characterised (by 1H‐NMR/13C‐NMR spectroscopy, IR, MS), in order to aid structure elucidation. Compounds not easily resolved by flash column chromatography were analysed by LC‐MS and/or independently synthesised for the purpose of attaining reference standards. Adaptation of the well‐known ‘phenylacetic acid route’ to synthesis of both 2,5‐P2P and 4‐Br‐2,5‐P2P, was found to provide low yields of the expected ketone products. Four impurities were isolated during the preparation of both ketones. The yield of one of these impurities (possessing a dibenzylketone core), was greatly influenced by the amount of acetic anhydride reagent used during the reaction. Having carried out the reaction with several different equivalents of acetic anhydride, it was found that formation of the ‘dibenzylketone’ could not be eliminated. This may increase its likelihood of being detected in the final drug product. The ‘Darzens route’, having very recently emerged as a synthetic route to amphetamine and MDMA precursors, was discovered to be a viable route for manufacture of 2,5‐P2P and 4‐Br‐2,5‐P2P. Despite execution of the reaction being more tedious, the route provides superior yields (≈50–60%) to those achieved using the ‘phenylacetic acid route’ (≈35–38%). Incorporation of a bromine atom (at the aromatic 4‐position) is required at some stage during synthesis of DOB. The bromination of many intermediates/starting materials was therefore also examined in detail. Bromination of the acid starting material 2,5‐dimethoxyphenylacetic acid (2,5‐PAA) was found to be clean and high yielding. This was in stark contrast to the bromination of the benzaldehyde starting material, the ketone precursor 2,5‐P2P and the dibenzylketone‐based impurity. Numerous brominated products were isolated from each of these reactions, many of which were novel compounds, and previously unreported as impurities in the literature. The unpredictable/nondescript nature of these brominations is likely to have a significant impact on the impurity profile of illicitly produced DOB.

Comprehensive metabolite profiling of Plantaginis Semen using ultra high performance liquid chromatography with electrospray ionization quadrupole time-of-flight tandem mass spectrometry coupled with elevated energy technique

Plantaginis Semen is commonly used in traditional medicine to treat edema, hypertension, and diabetes. The commercially available Plantaginis Semen in China mainly comes from three species. To clarify the chemical composition and distinct different species of Plantaginis Semen, we established a metabolite profiling method based on ultra high performance liquid chromatography with electrospray ionization quadrupole time-of-flight tandem mass spectrometry coupled with elevated energy technique. A total of 108 compounds, including phenylethanoid glycosides, flavonoids, guanidine derivatives, terpenoids, organic acids, and fatty acids, were identified from Plantago asiatica L., P. depressa Willd., and P. major L. Results showed significant differences in chemical components among the three species, particularly flavonoids. This study is the first to provide a comprehensive chemical profile of Plantaginis Semen, which could be involved into the quality control, medication guide, and developing new drug of Plantago seeds.

Development of advanced analytical methodologies for Alzheimer’s disease drug discovery

Advanced analytical methodologies were developed to characterize new potential active MTDLs on isolated targets involved in the first stages of Alzheimer’s disease (AD). In addition, the methods investigated drug-protein bindings and evaluated protein-protein interactions involved in the neurodegeneration. A high-throughput luminescent assay allowed the study of the first in class GSK-3β/ HDAC dual inhibitors towards the enzyme GSK-3β. The method was able to identify an innovative disease-modifying agent with an activity in the micromolar range both on GSK-3β, HDAC1 and HDAC6. Then, the same assay reliably and quickly selected true positive hit compounds among natural Amaryllidaceae alkaloids tested against GSK-3β. Hence, given the central role of the amyloid pathway in the multifactorial nature of AD, a multi-methodological approach based on mass spectrometry (MS), circular dichroism spectroscopy (CD) and ThT assay was applied to characterize the potential interaction of CO releasing molecules (CORMs) with Aβ1-42 peptide. The comprehensive method provided reliable information on the different steps of the fibrillation process and regarding CORMs mechanism of action. Therefore, the optimal CORM-3/Aβ1−42 ratio in terms of inhibitory effect was identified by mass spectrometry. CD analysis confirmed the stabilizing effect of CORM-3 on the Aβ1−42 peptide soluble form and the ThT Fluorescent Analysis ensured that the entire fibrillation process was delayed. Then the amyloid aggregation process was studied in view of a possible correlation with AD lipid brain alterations. Therefore, SH-SY5Y cells were treated with increasing concentration of Aß1-42 at different times and the samples were analysed by a RP-UHPLC system coupled with a high-resolution quadrupole TOF mass spectrometer in comprehensive data-independent SWATH acquisition mode. Each lipid class profiling in SH-SY5Y cells treated with Aß1-42 was compared to the one obtained from the untreated. The approach underlined some peculiar lipid alterations, suitable as biomarkers, that might be correlated to Aß1-42 different aggregation species.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.