Characterization of the C. elegans erlin homologue

Background

Ovarian cancer is one of the most lethal malignancies in women, as it is frequently detected at an advanced stage, and cancers often become refractory to chemotherapy. Evidence suggests that dysregulation of pro-apoptotic genes plays a key role in the onset of chemoresistance. The secreted Frizzled-Related Protein (sFRP) family is pro-apoptotic and also a negative modulator of the Wnt signalling cascade. Studies have demonstrated that the re-expression of sFRPs, in particular sFRP4, is associated with a better prognosis, and that experimentally induced expression results in cell death.

Results

In vitro experimental models determined that sFRP4 was differentially expressed in chemosensitive (A2780) and chemoresistant (A2780 ADR and A2780 Cis) ovarian cell lines, with chemosensitive cells expressing significantly higher levels of sFRP4. Transfection of the chemoresistant cell lines with sFRP4 significantly increased their sensitivity to chemotherapy. Conversely, silencing of sFRP4 expression in the chemosensitive cell line resulted in a corresponding increase in chemoresistance. Comparison of sFRP4 expression in tumour biopsies revealed a positive trend between sFRP4 expression and tumour grade, with mucinous cyst adenocarcinomas exhibiting significantly decreased sFRP4 levels compared to mucinous borderline tumours.

Conclusions

This study indicates a role for sFRP4 as a predictive marker of chemosensitivity in ovarian cancer and suggests that this pathway may be worth exploiting for novel therapies.     

Genotyping panel for assessing response to cancer chemotherapy

Background

Variants in numerous genes are thought to affect the success or failure of cancer chemotherapy. Interindividual variability can result from genes involved in drug metabolism and transport, drug targets (receptors, enzymes, etc), and proteins relevant to cell survival (e.g., cell cycle, DNA repair, and apoptosis). The purpose of the current study is to establish a flexible, cost-effective, high-throughput genotyping platform for candidate genes involved in chemoresistance and -sensitivity, and treatment outcomes.

Methods

We have adopted SNPlex for genotyping 432 single nucleotide polymorphisms (SNPs) in 160 candidate genes implicated in response to anticancer chemotherapy.

Results

The genotyping panels were applied to 39 patients with chronic lymphocytic leukemia undergoing flavopiridol chemotherapy, and 90 patients with colorectal cancer. 408 SNPs (94%) produced successful genotyping results. Additional genotyping methods were established for polymorphisms undetectable by SNPlex, including multiplexed SNaPshot for CYP2D6 SNPs, and PCR amplification with fluorescently labeled primers for the UGT1A1 promoter (TA)nTAA repeat polymorphism.

Conclusion

This genotyping panel is useful for supporting clinical anticancer drug trials to identify polymorphisms that contribute to interindividual variability in drug response. Availability of population genetic data across multiple studies has the potential to yield genetic biomarkers for optimizing anticancer therapy.     

Transcriptional Shift Identifies a Set of Genes Driving Breast Cancer Chemoresistance

Background

Distant recurrences after antineoplastic treatment remain a serious problem for breast cancer clinical management, which threats patients’ life. Systemic therapy is administered to eradicate cancer cells from the organism, both at the site of the primary tumor and at any other potential location. Despite this intervention, a significant proportion of breast cancer patients relapse even many years after their primary tumor has been successfully treated according to current clinical standards, evidencing the existence of a chemoresistant cell subpopulation originating from the primary tumor.

Methods/Findings

To identify key molecules and signaling pathways which drive breast cancer chemoresistance we performed gene expression analysis before and after anthracycline and taxane-based chemotherapy and compared the results between different histopathological response groups (good-, mid- and bad-response), established according to the Miller & Payne grading system. Two cohorts of 33 and 73 breast cancer patients receiving neoadjuvant chemotherapy were recruited for whole-genome expression analysis and validation assay, respectively. Identified genes were subjected to a bioinformatic analysis in order to ascertain the molecular function of the proteins they encode and the signaling in which they participate. High throughput technologies identified 65 gene sequences which were over-expressed in all groups (P ≤ 0·05 Bonferroni test). Notably we found that, after chemotherapy, a significant proportion of these genes were over-expressed in the good responders group, making their tumors indistinguishable from those of the bad responders in their expression profile (P ≤ 0.05 Benjamini-Hochgerg`s method).

Conclusions

These data identify a set of key molecular pathways selectively up-regulated in post-chemotherapy cancer cells, which may become appropriate targets for the development of future directed therapies against breast cancer.     

DNA microarray profiling of genes differentially regulated by the histone deacetylase inhibitors vorinostat and LBH589 in colon cancer cell lines

Background

Despite the significant progress made in colon cancer chemotherapy, advanced disease remains largely incurable and novel efficacious chemotherapies are urgently needed. Histone deacetylase inhibitors (HDACi) represent a novel class of agents which have demonstrated promising preclinical activity and are undergoing clinical evaluation in colon cancer. The goal of this study was to identify genes in colon cancer cells that are differentially regulated by two clinically advanced hydroxamic acid HDACi, vorinostat and LBH589 to provide rationale for novel drug combination partners and identify a core set of HDACi-regulated genes.

Methods

HCT116 and HT29 colon cancer cells were treated with LBH589 or vorinostat and growth inhibition, acetylation status and apoptosis were analyzed in response to treatment using MTS, Western blotting and flow cytometric analyses. In addition, gene expression was analyzed using the Illumina Human-6 V2 BeadChip array and Ingenuity^® Pathway Analysis.

Results

Treatment with either vorinostat or LBH589 rapidly induced histone acetylation, cell cycle arrest and inhibited the growth of both HCT116 and HT29 cells. Bioinformatic analysis of the microarray profiling revealed significant similarity in the genes altered in expression following treatment with the two HDACi tested within each cell line. However, analysis of genes that were altered in expression in the HCT116 and HT29 cells revealed cell-line-specific responses to HDACi treatment. In addition a core cassette of 11 genes modulated by both vorinostat and LBH589 were identified in both colon cancer cell lines analyzed.

Conclusion

This study identified HDACi-induced alterations in critical genes involved in nucleotide metabolism, angiogenesis, mitosis and cell survival which may represent potential intervention points for novel therapeutic combinations in colon cancer. This information will assist in the identification of novel pathways and targets that are modulated by HDACi, providing much-needed information on HDACi mechanism of action and providing rationale for novel drug combination partners. We identified a core signature of 11 genes which were modulated by both vorinostat and LBH589 in a similar manner in both cell lines. These core genes will assist in the development and validation of a common gene set which may represent a molecular signature of HDAC inhibition in colon cancer.     

Molecular network profiling of U373MG human glioblastoma cells following induction of apoptosis by novel marine-derived anti-cancer 1,2,3,4-tetrahydroisoquinoline alkaloids

Background

Glioblastoma is the most aggressive form of brain tumors showing resistance to treatment with various chemotherapeutic agents. The most effective way to eradicate glioblastoma requires the concurrent inhibition of multiple signaling pathways and target molecules involved in the progression of glioblastoma. Recently, we obtained a series of 1,2,3,4-tetrahydroisoquinoline alkaloids with potent anti-cancer activities, including ecteinascidin-770 (ET-770; the compound 1a) and renieramycin M (RM; the compound 2a) from Thai marine invertebrates, together with a 2’-N-4”-pyridinecarbonyl derivative of ET-770 (the compound 3). We attempted to characterize the molecular pathways responsible for cytotoxic effects of these compounds on a human glioblastoma cell line U373MG.

Methods

We studied the genome-wide gene expression profile on microarrays and molecular networks by using pathway analysis tools of bioinformatics.

Results

All of these compounds induced apoptosis of U373MG cells at nanomolar concentrations. The compound 3 reduced the expression of 417 genes and elevated the levels of 84 genes, while ET-770 downregulated 426 genes and upregulated 45 genes. RM decreased the expression of 274 genes and increased the expression of 9 genes. The set of 196 downregulated genes and 6 upregulated genes showed an overlap among all the compounds, suggesting an existence of the common pathways involved in induction of apoptosis. We identified the ErbB (EGFR) signaling pathway as one of the common pathways enriched in the set of downregulated genes, composed of PTK2, AKT3, and GSK3B serving as key molecules that regulate cell movement and the nervous system development. Furthermore, a GSK3B-specific inhibitor induced apoptosis of U373MG cells, supporting an anti-apoptotic role of GSK3B.

Conclusion

Molecular network analysis is a useful approach not only to characterize the glioma-relevant pathways but also to identify the network-based effective drug targets.     

Primate-specific evolution of noncoding element insertion into PLA2G4C and human preterm birth

Background

The use of biological annotation such as genes and pathways in the analysis of gene expression data has aided the identification of genes for follow-up studies and suggested functional information to uncharacterized genes. Several studies have applied similar methods to genome wide association studies and identified a number of disease related pathways. However, many questions remain on how to best approach this problem, such as whether there is a need to obtain a score to summarize association evidence at the gene level, and whether a pathway, dominated by just a few highly significant genes, is of interest.

Methods

We evaluated the performance of two pathway-based methods (Random Set, and Binomial approximation to the hypergeometric test) based on their applications to three data sets of Crohn's disease. We consider both the disease status as a phenotype as well as the residuals after conditioning on IL23R, a known Crohn's related gene, as a phenotype.

Results

Our results show that Random Set method has the most power to identify disease related pathways. We confirm previously reported disease related pathways and provide evidence for IL-2 Receptor Beta Chain in T cell Activation and IL-9 signaling as Crohn's disease associated pathways.

Conclusions

Our results highlight the need to apply powerful gene score methods prior to pathway enrichment tests, and that controlling for genes that attain genome wide significance enable further biological insight.     

Computing evolutionary distinctiveness indices in large scale analysis

Background

A combined quantitative trait loci (QTL) and microarray-based approach is commonly used to find differentially expressed genes which are then identified based on the known function of a gene in the biological process governing the trait of interest. However, a low cutoff value in individual gene analyses may result in many genes with moderate but meaningful changes in expression being missed.

Results

We modified a gene set analysis to identify intersection sets with significantly affected expression for which the changes in the individual gene sets are less significant. The gene expression profiles in liver tissues of four strains of mice from publicly available microarray sources were analyzed to detect trait-associated pathways using information on the QTL regions of blood concentrations of high density lipoproteins (HDL) cholesterol and insulin-like growth factor 1 (IGF-1). Several metabolic pathways related to HDL levels, including lipid metabolism, ABC transporters and cytochrome P450 pathways were detected for HDL QTL regions. Most of the pathways identified for the IGF-1 phenotype were signal transduction pathways associated with biological processes for IGF-1's regulation.

Conclusion

We have developed a method of identifying pathways associated with a quantitative trait using information on QTL. Our approach provides insights into genotype-phenotype relations at the level of biological pathways which may help to elucidate the genetic architecture underlying variation in phenotypic traits.     

Genome-scale identification of Caenorhabditis elegans regulatory elements by tiling-array mapping of DNase I hypersensitive sites

Background

High throughput techniques have generated a huge set of biological data, which are deposited in various databases. Efficient exploitation of these databases is often hampered by a lack of appropriate tools, which allow easy and reliable identification of genes that miss functional characterization but are correlated with specific biological conditions (e.g. organotypic expression).

Results

We have developed a simple algorithm (DGSA = Database-dependent Gene Selection and Analysis) to identify genes with unknown functions involved in organ development concentrating on the heart. Using our approach, we identified a large number of yet uncharacterized genes, which are expressed during heart development. An initial functional characterization of genes by loss-of-function analysis employing morpholino injections into zebrafish embryos disclosed severe developmental defects indicating a decisive function of selected genes for developmental processes.

Conclusion

We conclude that DGSA is a versatile tool for database mining allowing efficient selection of uncharacterized genes for functional analysis.     

Implications for health and disease in the genetic signature of the Ashkenazi Jewish population

Background

Relatively small, reproductively isolated populations with reduced genetic diversity may have advantages for genomewide association mapping in disease genetics. The Ashkenazi Jewish population represents a unique population for study based on its recent (< 1,000 year) history of a limited number of founders, population bottlenecks and tradition of marriage within the community. We genotyped more than 1,300 Ashkenazi Jewish healthy volunteers from the Hebrew University Genetic Resource with the Illumina HumanOmni1-Quad platform. Comparison of the genotyping data with that of neighboring European and Asian populations enabled the Ashkenazi Jewish-specific component of the variance to be characterized with respect to disease-relevant alleles and pathways.

Results

Using clustering, principal components, and pairwise genetic distance as converging approaches, we identified an Ashkenazi Jewish-specific genetic signature that differentiated these subjects from both European and Middle Eastern samples. Most notably, gene ontology analysis of the Ashkenazi Jewish genetic signature revealed an enrichment of genes functioning in transepithelial chloride transport, such as CFTR, and in equilibrioception, potentially shedding light on cystic fibrosis, Usher syndrome and other diseases over-represented in the Ashkenazi Jewish population. Results also impact risk profiles for autoimmune and metabolic disorders in this population. Finally, residual intra-Ashkenazi population structure was minimal, primarily determined by class 1 MHC alleles, and not related to host country of origin.

Conclusions

The Ashkenazi Jewish population is of potential utility in disease-mapping studies due to its relative homogeneity and distinct genomic signature. Results suggest that Ashkenazi-associated disease genes may be components of population-specific genomic differences in key functional pathways.     

Effect of Turkish propolis extracts on proteome of prostate cancer cell line

Background

The epidermal growth factor receptor (EGFR) is usually overexpressed in nasopharyngeal carcinoma (NPC) and is associated with pathogenesis of NPC. However, the downstream signaling proteins of EGFR in NPC have not yet been completely understood at the system level. The aim of this study was identify novel downstream proteins of EGFR signaling pathway in NPC cells.

Results

We analyzed EGFR-regulated phosphoproteome in NPC CNE2 cells using 2D-DIGE and mass spectrometry analysis after phosphoprotein enrichment. As a result, 33 nonredundant phosphoproteins including five known EGFR-regulated proteins and twenty-eight novel EGFR-regulated proteins in CNE2 were identified, three differential phosphoproteins were selectively validated, and two differential phosphoproteins (GSTP1 and GRB2) were showed interacted with phospho-EGFR. Bioinformatics analysis showed that 32 of 33 identified proteins contain phosphorylation modification sites, and 17 identified proteins are signaling proteins. GSTP1, one of the EGFR-regulated proteins, associated with chemoresistance was analyzed. The results showed that GSTP1 could contribute to paclitaxel resistance in EGF-stimulated CNE2 cells. Furthermore, an EGFR signaling network based on the identified EGFR-regulated phosphoproteins were constructed using Pathway Studio 5.0 software, which includes canonical and novel EGFR-regulated proteins and implicates the possible biological roles for those proteins.

Conclusion

The data not only can extend our knowledge of canonical EGFR signaling, but also will be useful to understand the molecular mechanisms of EGFR in NPC pathogenesis and search therapeutic targets for NPC.     

Antioxidant components of naturally-occurring oils exhibit marked anti-inflammatory activity in epithelial cells of the human upper respiratory system

Background

Proteomic studies of respiratory disorders have the potential to identify protein biomarkers for diagnosis and disease monitoring. Utilisation of sensitive quantitative proteomic methods creates opportunities to determine individual patient proteomes. The aim of the current study was to determine if quantitative proteomics of bronchial biopsies from asthmatics can distinguish relevant biological functions and whether inhaled glucocorticoid treatment affects these functions.

Methods

Endobronchial biopsies were taken from untreated asthmatic patients (n = 12) and healthy controls (n = 3). Asthmatic patients were randomised to double blind treatment with either placebo or budesonide (800 μg daily for 3 months) and new biopsies were obtained. Proteins extracted from the biopsies were digested and analysed using isobaric tags for relative and absolute quantitation combined with a nanoLC-LTQ Orbitrap mass spectrometer. Spectra obtained were used to identify and quantify proteins. Pathways analysis was performed using Ingenuity Pathway Analysis to identify significant biological pathways in asthma and determine how the expression of these pathways was changed by treatment.

Results

More than 1800 proteins were identified and quantified in the bronchial biopsies of subjects. The pathway analysis revealed acute phase response signalling, cell-to-cell signalling and tissue development associations with proteins expressed in asthmatics compared to controls. The functions and pathways associated with placebo and budesonide treatment showed distinct differences, including the decreased association with acute phase proteins as a result of budesonide treatment compared to placebo.

Conclusions

Proteomic analysis of bronchial biopsy material can be used to identify and quantify proteins using highly sensitive technologies, without the need for pooling of samples from several patients. Distinct pathophysiological features of asthma can be identified using this approach and the expression of these features is changed by inhaled glucocorticoid treatment. Quantitative proteomics may be applied to identify mechanisms of disease that may assist in the accurate and timely diagnosis of asthma.

Trial registration

ClinicalTrials.gov registration NCT01378039     

Characterization of Nitrotyrosine-Modified Proteins in Cerebrospinal Fluid

Background

HIV-associated neurocognitive disorders (HAND) has been associated with the up-regulation of various oxidative stress pathways. Previous studies have linked the neuronal damage observed in individuals diagnosed with HAND to increased nitrotyrosine modification of neuronal proteins.

Materials and methods

Tyrosine nitration alters protein structure and function, affects biological half-life, and potentially prevents the phosphorylation of key tyrosine residues involved in signal transduction pathways. Therefore, in this study we employed proteomics-based experimental approaches to investigate nitrotyrosine-modified proteins in pooled cerebrospinal fluid (CSF) of individuals diagnosed with HAND. To identify specific nitrotyrosine-modified proteins in the CSF of individuals diagnosed with HAND, affinity purification and high-performance tandem mass spectrometry are utilized in a “bottom-up” proteomics approach.

Results

From tandem mass spectrometric analysis, we identified major proteins that underwent nitration as a result of nitro-oxidative stress in the CSF of individuals diagnosed with HAND. We also utilized analytical and biochemical techniques to characterize the expression and modification site of in vivo nitrated lipocalin-type prostaglandin-D synthase in HAND CSF.